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This thesis presents new methods for the analysis of high-throughput data from modern sources in the context of complex human diseases, at the example of a bioinformatics analysis workflow. New measurement techniques improve the resolution with which cellular and molecular processes can be monitored. While RNA sequencing (RNA-seq) measures mRNA expression, single-cell RNA-seq (scRNA-seq) resolves this on a per-cell basis. Long-read sequencing is increasingly used in genomics. With imaging mass spectrometry (IMS) the protein level in tissues is measured spatially resolved. All these techniques induce specific challenges, which need to be addressed with new computational methods. Collecting knowledge with contextual annotations is important for integrative data analyses. Such knowledge is available through large literature repositories, from which information, such as miRNA-gene interactions, can be extracted using text mining methods. After aggregating this information in new databases, specific questions can be answered with traceable evidence. The combination of experimental data with these databases offers new possibilities for data integrative methods and for answering questions relevant for complex human diseases. Several data sources are made available, such as literature for text mining miRNA-gene interactions (Chapter 2), next- and third-generation sequencing data for genomics and transcriptomics (Chapters 4.1, 5), and IMS for spatially resolved proteomics (Chapter 4.4). For these data sources new methods for information extraction and pre-processing are developed. For instance, third-generation sequencing runs can be monitored and evaluated using the poreSTAT and sequ-into methods. The integrative (down-stream) analyses make use of these (heterogeneous) data sources. The cPred method (Chapter 4.2) for cell type prediction from scRNA-seq data was successfully applied in the context of the SARS-CoV-2 pandemic. The robust differential expression (DE) analysis pipeline RoDE (Chapter 6.1) contains a large set of methods for (differential) data analysis, reporting and visualization of RNA-seq data. Topics of accessibility of bioinformatics software are discussed along practical applications (Chapter 3). The developed miRNA-gene interaction database gives valuable insights into atherosclerosis-relevant processes and serves as regulatory network for the prediction of active miRNA regulators in RoDE (Chapter 6.1). The cPred predictions, RoDE results, scRNA-seq and IMS data are unified as input for the 3D-index Aorta3D (Chapter 6.2), which makes atherosclerosis related datasets browsable. Finally, the scRNA-seq analysis with subsequent cPred cell type prediction, and the robust analysis of bulk-RNA-seq datasets, led to novel insights into COVID-19. Taken all discussed methods together, the integrative analysis methods for complex human disease contexts have been improved at essential positions. Die Dissertation beschreibt Methoden zur Prozessierung von aktuellen Hochdurchsatzdaten, sowie Verfahren zu deren weiterer integrativen Analyse. Diese findet Anwendung vor allem im Kontext von komplexen menschlichen Krankheiten. Neue Messtechniken erlauben eine detailliertere Beobachtung biomedizinischer Prozesse. Mit RNA-Sequenzierung (RNA-seq) wird mRNA-Expression gemessen, mit Hilfe von moderner single-cell-RNA-seq (scRNA-seq) sogar für (sehr viele) einzelne Zellen. Long-Read-Sequenzierung wird zunehmend zur Sequenzierung ganzer Genome eingesetzt. Mittels bildgebender Massenspektrometrie (IMS) können Proteine in Geweben räumlich aufgelöst quantifiziert werden. Diese Techniken bringen spezifische Herausforderungen mit sich, die mit neuen bioinformatischen Methoden angegangen werden müssen. Für die integrative Datenanalyse ist auch die Gewinnung von geeignetem Kontextwissen wichtig. Wissenschaftliche Erkenntnisse werden in Artikeln veröffentlicht, die über große Literaturdatenbanken zugänglich sind. Mittels Textmining können daraus Informationen extrahiert werden, z.B. miRNA-Gen-Interaktionen, die in eigenen Datenbank aggregiert werden um spezifische Fragen mit nachvollziehbaren Belegen zu beantworten. In Kombination mit experimentellen Daten bieten sich so neue Möglichkeiten für integrative Methoden. Durch die Extraktion von Rohdaten und deren Vorprozessierung werden mehrere Datenquellen erschlossen, wie z.B. Literatur für Textmining von miRNA-Gen-Interaktionen (Kapitel 2), Long-Read- und RNA-seq-Daten für Genomics und Transcriptomics (Kapitel 4.2, 5) und IMS für Protein-Messungen (Kapitel 4.4). So dienen z.B. die poreSTAT und sequ-into Methoden der Vorprozessierung und Auswertung von Long-Read-Sequenzierungen. In der integrativen (down-stream) Analyse werden diese (heterogenen) Datenquellen verwendet. Für die Bestimmung von Zelltypen in scRNA-seq-Experimenten wurde die cPred-Methode (Kapitel 4.2) erfolgreich im Kontext der SARS-CoV-2-Pandemie eingesetzt. Auch die robuste Pipeline RoDE fand dort Anwendung, die viele Methoden zur (differentiellen) Datenanalyse, zum Reporting und zur Visualisierung bereitstellt (Kapitel 6.1). Themen der Benutzbarkeit von (bioinformatischer) Software werden an Hand von praktischen Anwendungen diskutiert (Kapitel 3). Die entwickelte miRNA-Gen-Interaktionsdatenbank gibt wertvolle Einblicke in Atherosklerose-relevante Prozesse und dient als regulatorisches Netzwerk für die Vorhersage von aktiven miRNA-Regulatoren in RoDE (Kapitel 6.1). Die cPred-Methode, RoDE-Ergebnisse, scRNA-seq- und IMS-Daten werden im 3D-Index Aorta3D (Kapitel 6.2) zusammengeführt, der relevante Datensätze durchsuchbar macht. Die diskutierten Methoden führen zu erheblichen Verbesserungen für die integrative Datenanalyse in komplexen menschlichen Krankheitskontexten.

The debate between the US and China about the responsibility for the COVID-19 pandemic raises important questions about the obligations of national governments in the global health care domain. Whereas the US attempts to put the blame on China do not have any serious legal or moral justifications, there is certainly a rationale for the establishment of certain minimal standards in the provision of health care for particular countries. Externalities in the global health care protection are too obvious – costs of underinvestment into the national health care system are borne not only by the country in question, but by the whole world. It is argued that countries should have certain obligations in providing health care services and protecting the population from diseases, especially infectious diseases, similar to the obligations in the framework of the responsibility to protect (R2P) concept that requires countries to protect their citizens from human rights violations. From the point of view of ensuring high life expectancy at a given level of per capita income and spending on health care, China is doing better than many other countries, including the United States that has high per capita income, spends 17% of GDP on health care, but does not provide universal access to health care and lags behind countries with a similar level of economic development in terms of life expectancy (79 years).

Am 4./5. Mai 2020 fand der 10. KIM Workshop statt. Durch die COVID-19-Pandemie konnte die Veranstaltung nicht wie gewohnt in Mannheim abgehalten werden, sondern wurde kurzerhand in eine Online-Veranstaltung umgewandelt. Im Folgenden möchten wir auf einige organisatorische Punkte dieser Online-Veranstaltung eingehen und unsere Erfahrungen dabei für andere Online-Veranstalter teilen. Zudem haben wir gegen Ende des Online-Workshops auch einige Fragen an die TeilnehmerInnen gestellt, welche hier zusammen mit den Antworten integriert werden.

In times of increasing digitization, the protection of individual data privacy becomes more important than ever before. To craft privacy policies that do not only meet legal requirements, but also address the public’s concerns, understanding individual privacy attitudes is key. Previous research suggests that privacy attitudes depend on a set of parameters related to the data type, data collector and other situational characteristics. However, the importance of single situational characteristics may possibly be altered by changes in the environment. This circumstance becomes apparent and even more important with the outbreak of the COVID-19 pandemic. The pandemic constitutes an exceptional situation in which individuals may be willing to transmit more personal data than usual for the sake of public health and safety. In this study, we analyze how attitudes towards acceptable data use shift in times of crisis. In July 2019, long before the pandemic, we conducted a survey in Germany in which we measured respondents’ acceptance of the collection and use of health data for public health purposes including preventing the spread of a virus. As the pandemic set in, we replicated this survey in the spring of 2020 to investigate changes in respondents’ willingness to share data for public health purposes in response to the crisis. Using data from 3,502 respondents, we demonstrate and quantify the shift in privacy attitudes with situational characteristics. Public acceptance of the use of personal health data to combat an infectious disease outbreak increased notably, while acceptance of personal data use in several other scenarios barely changed over time. We conclude that policymakers need to carefully consider the intended purpose of and appropriate limitations on data use for public health and argue that the design of data collection tools should meet both public health and privacy concerns.

A growing body of literature on the 2019 novel coronavirus (SARS-CoV-2) is becoming available, but a synthesis of available data has not been conducted. We performed a scoping review of currently available clinical, epidemiological, laboratory, and chest imaging data related to the SARS-CoV-2 infection. We searched MEDLINE, Cochrane CENTRAL, EMBASE, Scopus and LILACS from 01 January 2019 to 24 February 2020. Study selection, data extraction and risk of bias assessment were performed by two independent reviewers. Qualitative synthesis and meta-analysis were conducted using the clinical and laboratory data, and random-e ects models were applied to estimate pooled results. A total of 61 studies were included (59,254 patients). The most common disease-related symptoms were fever (82%, 95% confidence interval (CI) 56%–99%; n = 4410), cough (61%, 95% CI 39%–81%; n = 3985), muscle aches and/or fatigue (36%, 95% CI 18%–55%; n = 3778), dyspnea (26%, 95% CI 12%–41%; n = 3700), headache in 12% (95% CI 4%–23%, n = 3598 patients), sore throat in 10% (95% CI 5%–17%, n = 1387) and gastrointestinal symptoms in 9% (95% CI 3%–17%, n=1744). Laboratory findings were described in a lower number of patients and revealed lymphopenia (0.93 109/L, 95% CI 0.83–1.03 109/L, n = 464) and abnormal C-reactive protein (33.72 mg/dL, 95% CI 21.54–45.91 mg/dL; n = 1637). Radiological findings varied, but mostly described ground-glass opacities and consolidation. Data on treatment options were limited. All-cause mortality was 0.3% (95% CI 0.0%–1.0%; n = 53,631). Epidemiological studies showed that mortality was higher in males and elderly patients. The majority of reported clinical symptoms and laboratory findings related to SARS-CoV-2 infection are non-specific. Clinical suspicion, accompanied by a relevant epidemiological history, should be followed by early imaging and virological assay.

Radka Kunderová, Principal Investigator of the "Theatre ReDefined" research project, interviews Professor Christopher Balme (Ludwig-Maxmilians-Universität München) about the pre- and post-1989 developments in the German theatre. The interview discusses the period of the 1990s and the change of the theatre's functioning after 1989 and German reunification, as well as current crisis of German theatre in the context of the COVID-19 pandemic.