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description Publicationkeyboard_double_arrow_right Article 2021 AustriaPublisher:Springer Science and Business Media LLC Sebastian Pirch; Felix Müller; Eugenia Iofinova; Julia Pazmandi; Christiane V. R. Hütter; Martin Chiettini; Celine Sin; Kaan Boztug; Iana Podkosova; Hannes Kaufmann; Jörg Menche;Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality (VR) platform that overcomes these limitations by facilitating the thorough visual, and interactive, exploration of large networks. Our platform allows maximal customization and extendibility, through the import of custom code for data analysis, integration of external databases, and design of arbitrary user interface elements, among other features. As a proof of concept, we show how our platform can be used to interactively explore genome-scale molecular networks to identify genes associated with rare diseases and understand how they might contribute to disease development. Our platform represents a general purpose, VR-based data exploration platform for large and diverse data types by providing an interface that facilitates the interaction between human intuition and state-of-the-art analysis methods. Data-rich networks can be difficult to interpret beyond a certain size. Here, the authors introduce a platform that uses virtual reality to allow the visual exploration of large networks, while interfacing with data repositories and other analytical methods to improve the interpretation of big data.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8065164Data sources: PubMed CentralPermanent Hosting, Archiving and Indexing of Digital Resources and Assets; Nature CommunicationsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-021-22570-w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 28 citations 28 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8065164Data sources: PubMed CentralPermanent Hosting, Archiving and Indexing of Digital Resources and Assets; Nature CommunicationsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-021-22570-w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 BelgiumPublisher:Springer Science and Business Media LLC Funded by:EC | MANGOEC| MANGOAuthors: Nikolaos N. Louros; Gabriele Orlando; Matthias De Vleeschouwer; Frederic Rousseau; +1 AuthorsNikolaos N. Louros; Gabriele Orlando; Matthias De Vleeschouwer; Frederic Rousseau; Joost Schymkowitz;The amyloid conformation can be adopted by a variety of sequences, but the precise boundaries of amyloid sequence space are still unclear. The currently charted amyloid sequence space is strongly biased towards hydrophobic, beta-sheet prone sequences that form the core of globular proteins and by Q/N/Y rich yeast prions. Here, we took advantage of the increasing amount of high-resolution structural information on amyloid cores currently available in the protein databank to implement a machine learning approach, named Cordax (https://cordax.switchlab.org), that explores amyloid sequence beyond its current boundaries. Clustering by t-Distributed Stochastic Neighbour Embedding (t-SNE) shows how our approach resulted in an expansion away from hydrophobic amyloid sequences towards clusters of lower aliphatic content and higher charge, or regions of helical and disordered propensities. These clusters uncouple amyloid propensity from solubility representing sequence flavours compatible with surface-exposed patches in globular proteins, functional amyloids or sequences associated to liquid-liquid phase transitions. An increasing number of amyloid structures are determined. Here, the authors present the structure-based amyloid core sequence prediction method Cordax that is based on machine learning and allows the detection of aggregation-prone regions with higher solubility, disorder and surface exposure, and furthermore predicts the structural topology, orientation and overall architecture of the resulting putative fibril core.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7335209Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-020-17207-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 46 citations 46 popularity Top 1% influence Average impulse Top 1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7335209Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-020-17207-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2020 NetherlandsPublisher:Cold Spring Harbor Laboratory Funded by:NWO | BRAINSCAPES: A Roadmap fr..., EC | PAVENWO| BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology ,EC| PAVEAuthors: Lieke Michielsen; Marcel J. T. Reinders; Ahmed Mahfouz;Lieke Michielsen; Marcel J. T. Reinders; Ahmed Mahfouz;Supervised methods are increasingly used to identify cell populations in single-cell data. Yet, current methods are limited in their ability to learn from multiple datasets simultaneously, are hampered by the annotation of datasets at different resolutions, and do not preserve annotations when retrained on new datasets. The latter point is especially important as researchers cannot rely on downstream analysis performed using earlier versions of the dataset. Here, we present scHPL, a hierarchical progressive learning method which allows continuous learning from single-cell data by leveraging the different resolutions of annotations across multiple datasets to learn and continuously update a classification tree. We evaluate the classification and tree learning performance using simulated as well as real datasets and show that scHPL can successfully learn known cellular hierarchies from multiple datasets while preserving the original annotations. scHPL is available at https://github.com/lcmmichielsen/scHPL. Classification methods for scRNA-seq data are limited in their ability to learn from multiple datasets simultaneously. Here the authors present scHPL, a hierarchical progressive learning method that automatically finds relationships between cell populations across multiple datasets and constructs a classification tree.
NARCIS; TU Delft Rep... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8121839Data sources: PubMed CentralbioRxivPreprint . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.27.010124&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 18 citations 18 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 21visibility views 21 download downloads 50 Powered bymore_vert NARCIS; TU Delft Rep... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8121839Data sources: PubMed CentralbioRxivPreprint . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.27.010124&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2020 FrancePublisher:Cold Spring Harbor Laboratory Funded by:EC | IGNITE, EC | SynarchiCEC| IGNITE ,EC| SynarchiCCyril Matthey-Doret; Lyam Baudry; Axel Breuer; Rémi Montagne; Nadège Guiglielmoni; Vittore F. Scolari; Etienne Jean; Arnaud Campeas; Philippe Henri Chanut; Edgar Oriol; Adrien Meot; Laurent Politis; Antoine Vigouroux; Pierrick Moreau; Romain Koszul; Axel Cournac;Chromosomes of all species studied so far display a variety of higher-order organisational features, such as self-interacting domains or loops. These structures, which are often associated to biological functions, form distinct, visible patterns on genome-wide contact maps generated by chromosome conformation capture approaches such as Hi-C. Here we present Chromosight, an algorithm inspired from computer vision that can detect patterns in contact maps. Chromosight has greater sensitivity than existing methods on synthetic simulated data, while being faster and applicable to any type of genomes, including bacteria, viruses, yeasts and mammals. Our method does not require any prior training dataset and works well with default parameters on data generated with various protocols. Chromatin loops bridging distant loci within chromosomes can be detected by a variety of techniques such as Hi-C. Here the authors present Chromosight, an algorithm applied on mammalian, bacterial, viral and yeast genomes, able to detect various types of pattern in chromosome contact maps, including chromosomal loops.
Nature Communication... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7670471Data sources: PubMed CentralHAL Descartes; HAL-Pasteur; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2020License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.08.981910&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 60 citations 60 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert Nature Communication... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7670471Data sources: PubMed CentralHAL Descartes; HAL-Pasteur; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2020License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.08.981910&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 Denmark, Italy, Norway, Denmark, Netherlands, Denmark, Spain, France, Netherlands, Sweden, Netherlands EnglishPublisher:Springer Science and Business Media LLC Funded by:EC | OLISSIPO, EC | ELIXIR-EXCELERATE, WTEC| OLISSIPO ,EC| ELIXIR-EXCELERATE ,WTJon Ison; Hans Ienasescu; Piotr Jaroslaw Chmura; Emil Karol Rydza; Hervé Ménager; Matúš Kalaš; Veit Schwämmle; Björn Grüning; Niall Beard; Rodrigo Lopez; Séverine Duvaud; Heinz Stockinger; Bengt Persson; Radka Svobodová Vařeková; Tomáš Raček; Jiří Vondrášek; Hedi Peterson; Ahto Salumets; Inge Jonassen; Rob Hooft; Tommi Nyrönen; Alfonso Valencia; Salvador Capella; Josep Lluís Gelpí; Federico Zambelli; Babis Savakis; Brane Leskošek; Kristoffer Rapacki; Christophe Blanchet; Rafael C. Jimenez; Arlindo L. Oliveira; Gert Vriend; Olivier Collin; Jacques van Helden; Peter Løngreen; Søren Brunak;Bioinformaticians and biologists rely increasingly upon workflows for the flexible utilization of the many life science tools that are needed to optimally convert data into knowledge. We outline a pan-European enterprise to provide a catalogue ( https://bio.tools ) of tools and databases that can be used in these workflows. bio.tools not only lists where to find resources, but also provides a wide variety of practical information. Contains fulltext : 208582.pdf (Publisher’s version ) (Open Access)
NARCIS arrow_drop_down Genome BiologyArticle . 2019Full-Text: http://europepmc.org/articles/PMC6691543Data sources: PubMed CentralRadboud Repository; Genome Biology; Archivio Istituzionale della Ricerca dell'Università degli Studi di MilanoOther literature type . Article . 2019 . Peer-reviewedLicense: CC BYDiposit Digital de la Universitat de Barcelona; Recolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BYOnline Research Database In TechnologyArticle . 2019Data sources: Online Research Database In TechnologyCopenhagen University Research Information SystemArticle . 2019Data sources: Copenhagen University Research Information SystemUniversity of Southern Denmark Research OutputArticle . 2019Data sources: University of Southern Denmark Research OutputBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s13059-019-1772-6&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 34 citations 34 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!visibility 56visibility views 56 download downloads 103 Powered bymore_vert NARCIS arrow_drop_down Genome BiologyArticle . 2019Full-Text: http://europepmc.org/articles/PMC6691543Data sources: PubMed CentralRadboud Repository; Genome Biology; Archivio Istituzionale della Ricerca dell'Università degli Studi di MilanoOther literature type . Article . 2019 . Peer-reviewedLicense: CC BYDiposit Digital de la Universitat de Barcelona; Recolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BYOnline Research Database In TechnologyArticle . 2019Data sources: Online Research Database In TechnologyCopenhagen University Research Information SystemArticle . 2019Data sources: Copenhagen University Research Information SystemUniversity of Southern Denmark Research OutputArticle . 2019Data sources: University of Southern Denmark Research OutputBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s13059-019-1772-6&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Preprint 2018 United States, FrancePublisher:Cold Spring Harbor Laboratory Funded by:NIH | Leveraging Novel Multivar...NIH| Leveraging Novel Multivariate Methods of Subphenotypes in Genetic Association Studies of Sjogren?s SyndromeAuthors: Hanna Julienne; Huwenbo Shi; Bogdan Pasaniuc; Hugues Aschard;Hanna Julienne; Huwenbo Shi; Bogdan Pasaniuc; Hugues Aschard;Abstract Motivation Multi-trait analyses using public summary statistics from genome-wide association studies (GWASs) are becoming increasingly popular. A constraint of multi-trait methods is that they require complete summary data for all traits. Although methods for the imputation of summary statistics exist, they lack precision for genetic variants with small effect size. This is benign for univariate analyses where only variants with large effect size are selected a posteriori. However, it can lead to strong p-value inflation in multi-trait testing. Here we present a new approach that improve the existing imputation methods and reach a precision suitable for multi-trait analyses. Results We fine-tuned parameters to obtain a very high accuracy imputation from summary statistics. We demonstrate this accuracy for variants of all effect sizes on real data of 28 GWAS. We implemented the resulting methodology in a python package specially designed to efficiently impute multiple GWAS in parallel. Availability and implementation The python package is available at: https://gitlab.pasteur.fr/statistical-genetics/raiss, its accompanying documentation is accessible here http://statistical-genetics.pages.pasteur.fr/raiss/. Supplementary information Supplementary data are available at Bioinformatics online.
bioRxiv arrow_drop_down bioRxivPreprint . 2018eScholarship - University of CaliforniaArticle . 2019Data sources: eScholarship - University of CaliforniaBioinformaticsArticle . 2019 . Peer-reviewedLicense: OUP Standard Publication ReuseData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/502880&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 16 citations 16 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert bioRxiv arrow_drop_down bioRxivPreprint . 2018eScholarship - University of CaliforniaArticle . 2019Data sources: eScholarship - University of CaliforniaBioinformaticsArticle . 2019 . Peer-reviewedLicense: OUP Standard Publication ReuseData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/502880&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Other literature type 2018 FrancePublisher:Cold Spring Harbor Laboratory Funded by:ANR | GENMEDANR| GENMEDThibord, Florian; Perret, Claire; Roux, Maguelonne; Suchon, Pierre; Germain, Marine; Deleuze, Jean-François; Morange, Pierre-Emmanuel; Trégouët, David-Alexandre;AbstractNext-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs’ detection and quantification still remain a challenge as they can undergo different post transcriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy.OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers.OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).
bioRxiv arrow_drop_down bioRxivPreprint . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/479097&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 4 citations 4 popularity Average influence Average impulse Average Powered by BIP!visibility 33visibility views 33 download downloads 79 Powered bymore_vert bioRxiv arrow_drop_down bioRxivPreprint . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/479097&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2018 United Kingdom Funded by:UKRI | High Throughput Fluoresce..., UKRI | The Oxford Interdisciplin..., UKRI | 13 ERA-CAPS Plant Endopla...UKRI| High Throughput Fluorescence Imaging for Plant Sciences ,UKRI| The Oxford Interdisciplinary Bioscience Doctoral Training Partnership ,UKRI| 13 ERA-CAPS Plant Endoplasmic Reticulum Architecture and Seed ProductivityHawes, C; Kriechbaumer, V; Pain, C; Kittlemann, M; Fricker, M;pmid: 30816109
pmc: PMC6395764
The endoplasmic reticulum (ER) is a highly dynamic polygonal membrane network composed of interconnected tubules and sheets (cisternae) that forms the first compartment in the secretory pathway involved in protein translocation, folding, glycosylation, quality control, lipid synthesis, calcium signalling, and metabolon formation. Despite its central role in this plethora of biosynthetic, metabolic and physiological processes, there is little quantitative information on ER structure, morphology or dynamics. Here we describe a software package (AnalyzER) to automatically extract ER tubules and cisternae from multi-dimensional fluorescence images of plant ER. The structure, topology, protein-localisation patterns, and dynamics are automatically quantified using spatial, intensity and graph-theoretic metrics. We validate the method against manually-traced ground-truth networks, and calibrate the sub-resolution width estimates against ER profiles identified in serial block-face SEM images. We apply the approach to quantify the effects on ER morphology of drug treatments, abiotic stress and over-expression of ER tubule-shaping and cisternal-modifying proteins. Quantitative study of endoplasmic reticulum (ER) structure and dynamics has been a challenge. Here, the authors introduce software to automatically extract ER network elements from multi-dimensional fluorescence images of plant ER and to quantify structure, topology, protein localization and dynamics.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6395764Data sources: PubMed CentralOxford University Research ArchiveOther literature type . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6395764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 22 citations 22 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 2visibility views 2 download downloads 7 Powered bymore_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6395764Data sources: PubMed CentralOxford University Research ArchiveOther literature type . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6395764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2018 FrancePublisher:Cold Spring Harbor Laboratory Funded by:ANR | LocalEndoProbes, EC | Dyn-Syn-MemANR| LocalEndoProbes ,EC| Dyn-Syn-MemMorgane Rosendale; Thi Nhu Ngoc Van; Dolors Grillo-Bosch; Silvia Sposini; Léa Claverie; Isabel Gauthereau; Stéphane Claverol; Daniel Choquet; Matthieu Sainlos; David Perrais;During clathrin mediated endocytosis (CME), the concerted action of dynamin and its interacting partners drives membrane scission. Essential interactions occur between the proline/arginine-rich domain of dynamin (dynPRD) and the Src-homology domain 3 (SH3) of various proteins including amphiphysins. Here we show that multiple SH3 domains must bind simultaneously to dynPRD through three adjacent motifs for dynamin’s efficient recruitment and function. First, we show that mutant dynamins modified in a single motif, including the central amphiphysin SH3 (amphSH3) binding motif, partially rescue CME in dynamin triple knock-out cells. However, mutating two motifs largely prevents that ability. Furthermore, we designed divalent dynPRD-derived peptides. These ligands bind multimers of amphSH3 with >100-fold higher affinity than monovalent ones in vitro. Accordingly, dialyzing living cells with these divalent peptides through a patch-clamp pipette blocks CME much more effectively than with monovalent ones. We conclude that dynamin drives vesicle scission via multivalent interactions in cells. During clathrin mediated endocytosis (CME), membrane scission is achieved by the concerted action of dynamin and its interacting partners such as amphiphysins. Here authors show that efficient recruitment and function of dynamin requires simultaneous binding of multiple amphiphysin SH3 domains.
Nature Communication... arrow_drop_down bioRxivPreprint . 2018Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6773865Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/309245&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 28 citations 28 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Nature Communication... arrow_drop_down bioRxivPreprint . 2018Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6773865Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/309245&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article , Preprint , External research report 2018 FrancePublisher:Informa UK Limited Funded by:ANR | MixStatSeqANR| MixStatSeqAuthors: Antoine Godichon-Baggioni; Cathy Maugis-Rabusseau; Andrea Rau;Antoine Godichon-Baggioni; Cathy Maugis-Rabusseau; Andrea Rau;arXiv - Mathematics - Statistics Theory; Although there is no shortage of clustering algorithms proposed in the literature, the question of the most relevant strategy for clustering composi- tional data (i.e., data made up of profiles, whose rows belong to the simplex) re- mains largely unexplored in cases where the observed value of an observation is equal or close to zero for one or more samples. This work is motivated by the analysis of two sets of compositional data, both focused on the categorization of profiles but arising from considerably different applications: (1) identifying groups of co-expressed genes from high-throughput RNA sequencing data, in which a given gene may be completely silent in one or more experimental con- ditions; and (2) finding patterns in the usage of stations over the course of one week in the Velib’ bicycle sharing system in Paris, France. For both of these ap- plications, we focus on the use of appropriately chosen data transformations, including the Centered Log Ratio and a novel extension we propose called the Log Centered Log Ratio, in conjunction with the K -means algorithm. We use a nonasymptotic penalized criterion, whose penalty is calibrated with the slope heuristics, to select the number of clusters present in the data. Finally, we illus- trate the performance of this clustering strategy, which is implemented in the Bioconductor package coseq , on both the gene expression and bicycle sharing system data.
figshare arrow_drop_down HAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018 . 2019Mémoires en Sciences de l'Information et de la Communication; Hal-Diderot; HAL-INSA ToulousePreprint . 2018License: CC BYFull-Text: https://hal.inrae.fr/hal-02789763/documenthttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/02664763.2018.1454894&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 31 citations 31 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert figshare arrow_drop_down HAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018 . 2019Mémoires en Sciences de l'Information et de la Communication; Hal-Diderot; HAL-INSA ToulousePreprint . 2018License: CC BYFull-Text: https://hal.inrae.fr/hal-02789763/documenthttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/02664763.2018.1454894&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Article 2021 AustriaPublisher:Springer Science and Business Media LLC Sebastian Pirch; Felix Müller; Eugenia Iofinova; Julia Pazmandi; Christiane V. R. Hütter; Martin Chiettini; Celine Sin; Kaan Boztug; Iana Podkosova; Hannes Kaufmann; Jörg Menche;Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality (VR) platform that overcomes these limitations by facilitating the thorough visual, and interactive, exploration of large networks. Our platform allows maximal customization and extendibility, through the import of custom code for data analysis, integration of external databases, and design of arbitrary user interface elements, among other features. As a proof of concept, we show how our platform can be used to interactively explore genome-scale molecular networks to identify genes associated with rare diseases and understand how they might contribute to disease development. Our platform represents a general purpose, VR-based data exploration platform for large and diverse data types by providing an interface that facilitates the interaction between human intuition and state-of-the-art analysis methods. Data-rich networks can be difficult to interpret beyond a certain size. Here, the authors introduce a platform that uses virtual reality to allow the visual exploration of large networks, while interfacing with data repositories and other analytical methods to improve the interpretation of big data.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8065164Data sources: PubMed CentralPermanent Hosting, Archiving and Indexing of Digital Resources and Assets; Nature CommunicationsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-021-22570-w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 28 citations 28 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8065164Data sources: PubMed CentralPermanent Hosting, Archiving and Indexing of Digital Resources and Assets; Nature CommunicationsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-021-22570-w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 BelgiumPublisher:Springer Science and Business Media LLC Funded by:EC | MANGOEC| MANGOAuthors: Nikolaos N. Louros; Gabriele Orlando; Matthias De Vleeschouwer; Frederic Rousseau; +1 AuthorsNikolaos N. Louros; Gabriele Orlando; Matthias De Vleeschouwer; Frederic Rousseau; Joost Schymkowitz;The amyloid conformation can be adopted by a variety of sequences, but the precise boundaries of amyloid sequence space are still unclear. The currently charted amyloid sequence space is strongly biased towards hydrophobic, beta-sheet prone sequences that form the core of globular proteins and by Q/N/Y rich yeast prions. Here, we took advantage of the increasing amount of high-resolution structural information on amyloid cores currently available in the protein databank to implement a machine learning approach, named Cordax (https://cordax.switchlab.org), that explores amyloid sequence beyond its current boundaries. Clustering by t-Distributed Stochastic Neighbour Embedding (t-SNE) shows how our approach resulted in an expansion away from hydrophobic amyloid sequences towards clusters of lower aliphatic content and higher charge, or regions of helical and disordered propensities. These clusters uncouple amyloid propensity from solubility representing sequence flavours compatible with surface-exposed patches in globular proteins, functional amyloids or sequences associated to liquid-liquid phase transitions. An increasing number of amyloid structures are determined. Here, the authors present the structure-based amyloid core sequence prediction method Cordax that is based on machine learning and allows the detection of aggregation-prone regions with higher solubility, disorder and surface exposure, and furthermore predicts the structural topology, orientation and overall architecture of the resulting putative fibril core.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7335209Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-020-17207-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 46 citations 46 popularity Top 1% influence Average impulse Top 1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7335209Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41467-020-17207-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2020 NetherlandsPublisher:Cold Spring Harbor Laboratory Funded by:NWO | BRAINSCAPES: A Roadmap fr..., EC | PAVENWO| BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology ,EC| PAVEAuthors: Lieke Michielsen; Marcel J. T. Reinders; Ahmed Mahfouz;Lieke Michielsen; Marcel J. T. Reinders; Ahmed Mahfouz;Supervised methods are increasingly used to identify cell populations in single-cell data. Yet, current methods are limited in their ability to learn from multiple datasets simultaneously, are hampered by the annotation of datasets at different resolutions, and do not preserve annotations when retrained on new datasets. The latter point is especially important as researchers cannot rely on downstream analysis performed using earlier versions of the dataset. Here, we present scHPL, a hierarchical progressive learning method which allows continuous learning from single-cell data by leveraging the different resolutions of annotations across multiple datasets to learn and continuously update a classification tree. We evaluate the classification and tree learning performance using simulated as well as real datasets and show that scHPL can successfully learn known cellular hierarchies from multiple datasets while preserving the original annotations. scHPL is available at https://github.com/lcmmichielsen/scHPL. Classification methods for scRNA-seq data are limited in their ability to learn from multiple datasets simultaneously. Here the authors present scHPL, a hierarchical progressive learning method that automatically finds relationships between cell populations across multiple datasets and constructs a classification tree.
NARCIS; TU Delft Rep... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8121839Data sources: PubMed CentralbioRxivPreprint . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.27.010124&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 18 citations 18 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 21visibility views 21 download downloads 50 Powered bymore_vert NARCIS; TU Delft Rep... arrow_drop_down Europe PubMed CentralArticle . 2021 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC8121839Data sources: PubMed CentralbioRxivPreprint . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.27.010124&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2020 FrancePublisher:Cold Spring Harbor Laboratory Funded by:EC | IGNITE, EC | SynarchiCEC| IGNITE ,EC| SynarchiCCyril Matthey-Doret; Lyam Baudry; Axel Breuer; Rémi Montagne; Nadège Guiglielmoni; Vittore F. Scolari; Etienne Jean; Arnaud Campeas; Philippe Henri Chanut; Edgar Oriol; Adrien Meot; Laurent Politis; Antoine Vigouroux; Pierrick Moreau; Romain Koszul; Axel Cournac;Chromosomes of all species studied so far display a variety of higher-order organisational features, such as self-interacting domains or loops. These structures, which are often associated to biological functions, form distinct, visible patterns on genome-wide contact maps generated by chromosome conformation capture approaches such as Hi-C. Here we present Chromosight, an algorithm inspired from computer vision that can detect patterns in contact maps. Chromosight has greater sensitivity than existing methods on synthetic simulated data, while being faster and applicable to any type of genomes, including bacteria, viruses, yeasts and mammals. Our method does not require any prior training dataset and works well with default parameters on data generated with various protocols. Chromatin loops bridging distant loci within chromosomes can be detected by a variety of techniques such as Hi-C. Here the authors present Chromosight, an algorithm applied on mammalian, bacterial, viral and yeast genomes, able to detect various types of pattern in chromosome contact maps, including chromosomal loops.
Nature Communication... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7670471Data sources: PubMed CentralHAL Descartes; HAL-Pasteur; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2020License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.08.981910&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 60 citations 60 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert Nature Communication... arrow_drop_down Europe PubMed CentralArticle . 2020 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC7670471Data sources: PubMed CentralHAL Descartes; HAL-Pasteur; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2020License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2020.03.08.981910&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 Denmark, Italy, Norway, Denmark, Netherlands, Denmark, Spain, France, Netherlands, Sweden, Netherlands EnglishPublisher:Springer Science and Business Media LLC Funded by:EC | OLISSIPO, EC | ELIXIR-EXCELERATE, WTEC| OLISSIPO ,EC| ELIXIR-EXCELERATE ,WTJon Ison; Hans Ienasescu; Piotr Jaroslaw Chmura; Emil Karol Rydza; Hervé Ménager; Matúš Kalaš; Veit Schwämmle; Björn Grüning; Niall Beard; Rodrigo Lopez; Séverine Duvaud; Heinz Stockinger; Bengt Persson; Radka Svobodová Vařeková; Tomáš Raček; Jiří Vondrášek; Hedi Peterson; Ahto Salumets; Inge Jonassen; Rob Hooft; Tommi Nyrönen; Alfonso Valencia; Salvador Capella; Josep Lluís Gelpí; Federico Zambelli; Babis Savakis; Brane Leskošek; Kristoffer Rapacki; Christophe Blanchet; Rafael C. Jimenez; Arlindo L. Oliveira; Gert Vriend; Olivier Collin; Jacques van Helden; Peter Løngreen; Søren Brunak;Bioinformaticians and biologists rely increasingly upon workflows for the flexible utilization of the many life science tools that are needed to optimally convert data into knowledge. We outline a pan-European enterprise to provide a catalogue ( https://bio.tools ) of tools and databases that can be used in these workflows. bio.tools not only lists where to find resources, but also provides a wide variety of practical information. Contains fulltext : 208582.pdf (Publisher’s version ) (Open Access)
NARCIS arrow_drop_down Genome BiologyArticle . 2019Full-Text: http://europepmc.org/articles/PMC6691543Data sources: PubMed CentralRadboud Repository; Genome Biology; Archivio Istituzionale della Ricerca dell'Università degli Studi di MilanoOther literature type . Article . 2019 . Peer-reviewedLicense: CC BYDiposit Digital de la Universitat de Barcelona; Recolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BYOnline Research Database In TechnologyArticle . 2019Data sources: Online Research Database In TechnologyCopenhagen University Research Information SystemArticle . 2019Data sources: Copenhagen University Research Information SystemUniversity of Southern Denmark Research OutputArticle . 2019Data sources: University of Southern Denmark Research OutputBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s13059-019-1772-6&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 34 citations 34 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!visibility 56visibility views 56 download downloads 103 Powered bymore_vert NARCIS arrow_drop_down Genome BiologyArticle . 2019Full-Text: http://europepmc.org/articles/PMC6691543Data sources: PubMed CentralRadboud Repository; Genome Biology; Archivio Istituzionale della Ricerca dell'Università degli Studi di MilanoOther literature type . Article . 2019 . Peer-reviewedLicense: CC BYDiposit Digital de la Universitat de Barcelona; Recolector de Ciencia Abierta, RECOLECTAArticle . 2019License: CC BYOnline Research Database In TechnologyArticle . 2019Data sources: Online Research Database In TechnologyCopenhagen University Research Information SystemArticle . 2019Data sources: Copenhagen University Research Information SystemUniversity of Southern Denmark Research OutputArticle . 2019Data sources: University of Southern Denmark Research OutputBergen Open Research Archive - UiBArticle . 2019 . Peer-reviewedLicense: CC BYData sources: Bergen Open Research Archive - UiBadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s13059-019-1772-6&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Preprint 2018 United States, FrancePublisher:Cold Spring Harbor Laboratory Funded by:NIH | Leveraging Novel Multivar...NIH| Leveraging Novel Multivariate Methods of Subphenotypes in Genetic Association Studies of Sjogren?s SyndromeAuthors: Hanna Julienne; Huwenbo Shi; Bogdan Pasaniuc; Hugues Aschard;Hanna Julienne; Huwenbo Shi; Bogdan Pasaniuc; Hugues Aschard;Abstract Motivation Multi-trait analyses using public summary statistics from genome-wide association studies (GWASs) are becoming increasingly popular. A constraint of multi-trait methods is that they require complete summary data for all traits. Although methods for the imputation of summary statistics exist, they lack precision for genetic variants with small effect size. This is benign for univariate analyses where only variants with large effect size are selected a posteriori. However, it can lead to strong p-value inflation in multi-trait testing. Here we present a new approach that improve the existing imputation methods and reach a precision suitable for multi-trait analyses. Results We fine-tuned parameters to obtain a very high accuracy imputation from summary statistics. We demonstrate this accuracy for variants of all effect sizes on real data of 28 GWAS. We implemented the resulting methodology in a python package specially designed to efficiently impute multiple GWAS in parallel. Availability and implementation The python package is available at: https://gitlab.pasteur.fr/statistical-genetics/raiss, its accompanying documentation is accessible here http://statistical-genetics.pages.pasteur.fr/raiss/. Supplementary information Supplementary data are available at Bioinformatics online.
bioRxiv arrow_drop_down bioRxivPreprint . 2018eScholarship - University of CaliforniaArticle . 2019Data sources: eScholarship - University of CaliforniaBioinformaticsArticle . 2019 . Peer-reviewedLicense: OUP Standard Publication ReuseData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/502880&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 16 citations 16 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert bioRxiv arrow_drop_down bioRxivPreprint . 2018eScholarship - University of CaliforniaArticle . 2019Data sources: eScholarship - University of CaliforniaBioinformaticsArticle . 2019 . Peer-reviewedLicense: OUP Standard Publication ReuseData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/502880&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Other literature type 2018 FrancePublisher:Cold Spring Harbor Laboratory Funded by:ANR | GENMEDANR| GENMEDThibord, Florian; Perret, Claire; Roux, Maguelonne; Suchon, Pierre; Germain, Marine; Deleuze, Jean-François; Morange, Pierre-Emmanuel; Trégouët, David-Alexandre;AbstractNext-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs’ detection and quantification still remain a challenge as they can undergo different post transcriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy.OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers.OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).
bioRxiv arrow_drop_down bioRxivPreprint . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/479097&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 4 citations 4 popularity Average influence Average impulse Average Powered by BIP!visibility 33visibility views 33 download downloads 79 Powered bymore_vert bioRxiv arrow_drop_down bioRxivPreprint . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/479097&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2018 United Kingdom Funded by:UKRI | High Throughput Fluoresce..., UKRI | The Oxford Interdisciplin..., UKRI | 13 ERA-CAPS Plant Endopla...UKRI| High Throughput Fluorescence Imaging for Plant Sciences ,UKRI| The Oxford Interdisciplinary Bioscience Doctoral Training Partnership ,UKRI| 13 ERA-CAPS Plant Endoplasmic Reticulum Architecture and Seed ProductivityHawes, C; Kriechbaumer, V; Pain, C; Kittlemann, M; Fricker, M;pmid: 30816109
pmc: PMC6395764
The endoplasmic reticulum (ER) is a highly dynamic polygonal membrane network composed of interconnected tubules and sheets (cisternae) that forms the first compartment in the secretory pathway involved in protein translocation, folding, glycosylation, quality control, lipid synthesis, calcium signalling, and metabolon formation. Despite its central role in this plethora of biosynthetic, metabolic and physiological processes, there is little quantitative information on ER structure, morphology or dynamics. Here we describe a software package (AnalyzER) to automatically extract ER tubules and cisternae from multi-dimensional fluorescence images of plant ER. The structure, topology, protein-localisation patterns, and dynamics are automatically quantified using spatial, intensity and graph-theoretic metrics. We validate the method against manually-traced ground-truth networks, and calibrate the sub-resolution width estimates against ER profiles identified in serial block-face SEM images. We apply the approach to quantify the effects on ER morphology of drug treatments, abiotic stress and over-expression of ER tubule-shaping and cisternal-modifying proteins. Quantitative study of endoplasmic reticulum (ER) structure and dynamics has been a challenge. Here, the authors introduce software to automatically extract ER network elements from multi-dimensional fluorescence images of plant ER and to quantify structure, topology, protein localization and dynamics.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6395764Data sources: PubMed CentralOxford University Research ArchiveOther literature type . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6395764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 22 citations 22 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 2visibility views 2 download downloads 7 Powered bymore_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6395764Data sources: PubMed CentralOxford University Research ArchiveOther literature type . 2019License: CC BYData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6395764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint 2018 FrancePublisher:Cold Spring Harbor Laboratory Funded by:ANR | LocalEndoProbes, EC | Dyn-Syn-MemANR| LocalEndoProbes ,EC| Dyn-Syn-MemMorgane Rosendale; Thi Nhu Ngoc Van; Dolors Grillo-Bosch; Silvia Sposini; Léa Claverie; Isabel Gauthereau; Stéphane Claverol; Daniel Choquet; Matthieu Sainlos; David Perrais;During clathrin mediated endocytosis (CME), the concerted action of dynamin and its interacting partners drives membrane scission. Essential interactions occur between the proline/arginine-rich domain of dynamin (dynPRD) and the Src-homology domain 3 (SH3) of various proteins including amphiphysins. Here we show that multiple SH3 domains must bind simultaneously to dynPRD through three adjacent motifs for dynamin’s efficient recruitment and function. First, we show that mutant dynamins modified in a single motif, including the central amphiphysin SH3 (amphSH3) binding motif, partially rescue CME in dynamin triple knock-out cells. However, mutating two motifs largely prevents that ability. Furthermore, we designed divalent dynPRD-derived peptides. These ligands bind multimers of amphSH3 with >100-fold higher affinity than monovalent ones in vitro. Accordingly, dialyzing living cells with these divalent peptides through a patch-clamp pipette blocks CME much more effectively than with monovalent ones. We conclude that dynamin drives vesicle scission via multivalent interactions in cells. During clathrin mediated endocytosis (CME), membrane scission is achieved by the concerted action of dynamin and its interacting partners such as amphiphysins. Here authors show that efficient recruitment and function of dynamin requires simultaneous binding of multiple amphiphysin SH3 domains.
Nature Communication... arrow_drop_down bioRxivPreprint . 2018Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6773865Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/309245&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 28 citations 28 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Nature Communication... arrow_drop_down bioRxivPreprint . 2018Europe PubMed CentralArticle . 2019 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC6773865Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/309245&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article , Preprint , External research report 2018 FrancePublisher:Informa UK Limited Funded by:ANR | MixStatSeqANR| MixStatSeqAuthors: Antoine Godichon-Baggioni; Cathy Maugis-Rabusseau; Andrea Rau;Antoine Godichon-Baggioni; Cathy Maugis-Rabusseau; Andrea Rau;arXiv - Mathematics - Statistics Theory; Although there is no shortage of clustering algorithms proposed in the literature, the question of the most relevant strategy for clustering composi- tional data (i.e., data made up of profiles, whose rows belong to the simplex) re- mains largely unexplored in cases where the observed value of an observation is equal or close to zero for one or more samples. This work is motivated by the analysis of two sets of compositional data, both focused on the categorization of profiles but arising from considerably different applications: (1) identifying groups of co-expressed genes from high-throughput RNA sequencing data, in which a given gene may be completely silent in one or more experimental con- ditions; and (2) finding patterns in the usage of stations over the course of one week in the Velib’ bicycle sharing system in Paris, France. For both of these ap- plications, we focus on the use of appropriately chosen data transformations, including the Centered Log Ratio and a novel extension we propose called the Log Centered Log Ratio, in conjunction with the K -means algorithm. We use a nonasymptotic penalized criterion, whose penalty is calibrated with the slope heuristics, to select the number of clusters present in the data. Finally, we illus- trate the performance of this clustering strategy, which is implemented in the Bioconductor package coseq , on both the gene expression and bicycle sharing system data.
figshare arrow_drop_down HAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018 . 2019Mémoires en Sciences de l'Information et de la Communication; Hal-Diderot; HAL-INSA ToulousePreprint . 2018License: CC BYFull-Text: https://hal.inrae.fr/hal-02789763/documenthttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/02664763.2018.1454894&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 31 citations 31 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert figshare arrow_drop_down HAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018 . 2019Mémoires en Sciences de l'Information et de la Communication; Hal-Diderot; HAL-INSA ToulousePreprint . 2018License: CC BYFull-Text: https://hal.inrae.fr/hal-02789763/documenthttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/02664763.2018.1454894&type=result"></script>'); --> </script>
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