Computational methods for integrating and analyzing human systems biology data

The combination of heterogeneous biological datasets is a key requirement for modern molecular systems biology. Of particular importance for our understanding of complex biological systems like the human cell are data about the interactions of proteins with other molecules. In this thesis, we develop and apply methods to improve the availability and the quality of such interaction data. We also demonstrate how these data can be used in interdisciplinary studies to discover new biological results. First, we develop technical systems for the instant integration of interaction data that are stored and maintained in separate online repositories. Second, we implement a computational framework for the application of multiple scoring algorithms to qualitatively assess different aspects of interaction data. Our methods are based on distributed client-server systems, ensuring that the services can be updated continuously. This promotes equal access to interaction data and allows researchers to expand the client-server systems with their own service. Third, we focus our application studies on integrative network-based analyses of human host factors for viral infections. Our applications provide new biological insights into the life cycle of the hepatitis C virus and identify new potential candidates for antiviral drug therapy.Die Kombination verschiedener biologischer Datensätze ist für die moderne molekulare Systembiologie unumgänglich. Eine besondere Bedeutung für unser Verständnis von komplexen biologischen Systemen wie der Zelle haben dabei Daten über die Wechselwirkungen von Proteinen mit anderen Molekülen. In dieser Arbeit entwickeln und verwenden wir Methoden zur Verbesserung der Verfügbarkeit und Bewertbarkeit von solchen Interaktionsdaten. Wir zeigen auch, wie diese Daten in interdisziplinären Studien genutzt werden können, um neue biologische Erkenntnisse zu gewinnen. Zuerst entwickeln wir technische Systeme, um Interaktionsdaten von verschiedenen Quellen des Internets zusammenzuführen. Danach entwickeln wir ein computergestütztes System, welches die Anwendung verschiedener Algorithmen ermöglicht, um unterschiedliche Aspekte von Wechselwirkungen qualitativ zu bewerten. Unsere Methoden basieren auf verteilten Client-Server-Systemen, die sicherstellen, dass einzelne Dienste dauerhaft aktuell gehalten werden können. Zudem fördert dies einen gleichberechtigten Zugang zu Interaktionsdaten, und Wissenschaftler können die Systeme mit eigenen Diensten erweitern. Unser Anwendungsschwerpunkt liegt auf der netzwerkbasierten Analyse humaner Wirtsfaktoren für virale Infektionen. Unsere Auswertungen tragen zu einem besseren Verständnis des Lebenszyklus des Hepatitis-C-Virus bei und zeigen Ansatzpunkte für die Entwicklung neuer antiviraler Medikamente auf

Computational methods for integrating and analyzing human systems biology data

The combination of heterogeneous biological datasets is a key requirement for modern molecular systems biology. Of particular importance for our understanding of complex biological systems like the human cell are data about the interactions of proteins with other molecules. In this thesis, we develop and apply methods to improve the availability and the quality of such interaction data. We also demonstrate how these data can be used in interdisciplinary studies to discover new biological results. First, we develop technical systems for the instant integration of interaction data that are stored and maintained in separate online repositories. Second, we implement a computational framework for the application of multiple scoring algorithms to qualitatively assess different aspects of interaction data. Our methods are based on distributed client-server systems, ensuring that the services can be updated continuously. This promotes equal access to interaction data and allows researchers to expand the client-server systems with their own service. Third, we focus our application studies on integrative network-based analyses of human host factors for viral infections. Our applications provide new biological insights into the life cycle of the hepatitis C virus and identify new potential candidates for antiviral drug therapy.Die Kombination verschiedener biologischer Datensätze ist für die moderne molekulare Systembiologie unumgänglich. Eine besondere Bedeutung für unser Verständnis von komplexen biologischen Systemen wie der Zelle haben dabei Daten über die Wechselwirkungen von Proteinen mit anderen Molekülen. In dieser Arbeit entwickeln und verwenden wir Methoden zur Verbesserung der Verfügbarkeit und Bewertbarkeit von solchen Interaktionsdaten. Wir zeigen auch, wie diese Daten in interdisziplinären Studien genutzt werden können, um neue biologische Erkenntnisse zu gewinnen. Zuerst entwickeln wir technische Systeme, um Interaktionsdaten von verschiedenen Quellen des Internets zusammenzuführen. Danach entwickeln wir ein computergestütztes System, welches die Anwendung verschiedener Algorithmen ermöglicht, um unterschiedliche Aspekte von Wechselwirkungen qualitativ zu bewerten. Unsere Methoden basieren auf verteilten Client-Server-Systemen, die sicherstellen, dass einzelne Dienste dauerhaft aktuell gehalten werden können. Zudem fördert dies einen gleichberechtigten Zugang zu Interaktionsdaten, und Wissenschaftler können die Systeme mit eigenen Diensten erweitern. Unser Anwendungsschwerpunkt liegt auf der netzwerkbasierten Analyse humaner Wirtsfaktoren für virale Infektionen. Unsere Auswertungen tragen zu einem besseren Verständnis des Lebenszyklus des Hepatitis-C-Virus bei und zeigen Ansatzpunkte für die Entwicklung neuer antiviraler Medikamente auf

How to understand the cell by breaking it: network analysis of gene perturbation screens

Modern high-throughput gene perturbation screens are key technologies at the forefront of genetic research. Combined with rich phenotypic descriptors they enable researchers to observe detailed cellular reactions to experimental perturbations on a genome-wide scale. This review surveys the current state-of-the-art in analyzing perturbation screens from a network point of view. We describe approaches to make the step from the parts list to the wiring diagram by using phenotypes for network inference and integrating them with complementary data sources. The first part of the review describes methods to analyze one- or low-dimensional phenotypes like viability or reporter activity; the second part concentrates on high-dimensional phenotypes showing global changes in cell morphology, transcriptome or proteome.Comment: Review based on ISMB 2009 tutorial; after two rounds of revisio

Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

Systems analysis of host-parasite interactions.

Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput -omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies