Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

PROTEIN FUNCTION, DIVERISTY AND FUNCTIONAL INTERPLAY

Functional annotations of novel or unknown proteins is one of the central problems in post-genomics bioinformatics research. With the vast expansion of genomic and proteomic data and technologies over the last decade, development of automated function prediction (AFP) methods for large-scale identification of protein function has be-come imperative in many aspects. In this research, we address two important divergences from the “one protein – one function” concept on which all existing AFP methods are developed

Clonal Expansion and Epigenetic Inheritance Shape Long-Lasting NK cell Memory

Die Selektion klonal expandierender Zellen mit einzigartigen, somatisch rekombinierten Anti-gen-Rezeptoren und die Langlebigkeit der daraus hervorgehenden Gedächtniszellen sind definierende Eigenschaften adaptiver Immunität. Dahingegen ist das angeborene Immunsystem da-rauf programmiert, mittels einer breiten Palette konservierter Rezeptoren möglichst schnell auf Pathogene zu reagieren und wird dabei auf Populationsebene epigenetisch geprägt. In dieser Arbeit möchte ich dieses Paradigma auf der Basis von Natürlichem Killer (NK) Zell-Gedächtnis an das humane Zytomegalievirus (HCMV) als Beispiel für Pathogen-spezifische Anpassung innerhalb des angeborenen Immunsystems herausfordern. Indem wir multiparametrische Einzel-zellanalysen zur Kartierung von ex vivo NK Zellen mit endogenen Barcodes in Form von soma-tischen Mutationen in mitochondrialer DNA (mtDNA) verknüpfen, können wir drastische klonale Expansionen adaptiver NK Zellen in HCMV+ Spendern nachweisen. NK-Zell-Klonotypen waren durch eine ihnen gemeinsame, inflammatorische Gedächtnissignatur mit AP1 Motiven gekennzeichnet, die eine Reihe einzigartiger Chromatin-Regionen mit Klon-spezifischer Zugänglichkeit überlagerte. NK-Zell-Klone wurden über einen Zeitraum von bis zu 19 Monaten stabil aufrechterhalten und behielten dabei ihre charakteristischen, Klon-spezifischen epigenetischen Signaturen, was die entscheidende Rolle klonaler Vererbung von Chromatin-Zugänglichkeit für die Prägung des epigenetischen Gedächtnis-Repertoires unterstreicht. Insgesamt identifiziert diese Arbeit zum ersten Mal klonale Expansion und Persistenz innerhalb des angeborenen Immunsystems im Menschen und deutet daraufhin, dass diese zentralen Mechanismen zur Ausbildung von immunologischem Gedächtnis evolutionär unabhängig von diversifizierten Antigen-Rezeptoren entstanden sind.A hallmark of adaptive immunity is the clonal selection and expansion of cells with somatically diversified receptors and their long-term maintenance as memory cells. The innate immune system, in contrast, is wired to rapidly respond to pathogens via a broad set of germline-encoded receptors, acquiring epigenetic imprinting at the population level. The presented work challenges this paradigm by studying Natural Killer (NK) cell memory to human Cytomegalovirus (HCMV) infection as an example of pathogen-specific adaptation within the innate immune system. Leveraging single-cell multi-omic maps of ex vivo NK cells and somatic mitochondrial DNA (mtDNA) mutations as endogenous barcodes, we reveal drastic clonal expansions of adaptive NK cells in HCMV+ individuals. NK cell clonotypes were characterized by a convergent inflammatory memory signature driven by AP1 transcription factor activity, superimposed on a private set of clone-specific accessible chromatin regions. Strikingly, NK cell clones were stably maintained in their specific epigenetic states for up to 19 months, revealing that clonal inheritance of chromatin accessibility shapes the epigenetic memory repertoire. Together, this work presents the first identification of clonal expansion and persistence within the human innate immune system, suggesting these central mechanisms of immune memory have evolved independently of antigen-receptor diversification

Infobiotics : computer-aided synthetic systems biology

Until very recently Systems Biology has, despite its stated goals, been too reductive in terms of the models being constructed and the methods used have been, on the one hand, unsuited for large scale adoption or integration of knowledge across scales, and on the other hand, too fragmented. The thesis of this dissertation is that better computational languages and seamlessly integrated tools are required by systems and synthetic biologists to enable them to meet the significant challenges involved in understanding life as it is, and by designing, modelling and manufacturing novel organisms, to understand life as it could be. We call this goal, where everything necessary to conduct model-driven investigations of cellular circuitry and emergent effects in populations of cells is available without significant context-switching, “one-pot” in silico synthetic systems biology in analogy to “one-pot” chemistry and “one-pot” biology. Our strategy is to increase the understandability and reusability of models and experiments, thereby avoiding unnecessary duplication of effort, with practical gains in the efficiency of delivering usable prototype models and systems. Key to this endeavour are graphical interfaces that assists novice users by hiding complexity of the underlying tools and limiting choices to only what is appropriate and useful, thus ensuring that the results of in silico experiments are consistent, comparable and reproducible. This dissertation describes the conception, software engineering and use of two novel software platforms for systems and synthetic biology: the Infobiotics Workbench for modelling, in silico experimentation and analysis of multi-cellular biological systems; and DNA Library Designer with the DNALD language for the compact programmatic specification of combinatorial DNA libraries, as the first stage of a DNA synthesis pipeline, enabling methodical exploration biological problem spaces. Infobiotics models are formalised as Lattice Population P systems, a novel framework for the specification of spatially-discrete and multi-compartmental rule-based models, imbued with a stochastic execution semantics. This framework was developed to meet the needs of real systems biology problems: hormone transport and signalling in the root of Arabidopsis thaliana, and quorum sensing in the pathogenic bacterium Pseudomonas aeruginosa. Our tools have also been used to prototype a novel synthetic biological system for pattern formation, that has been successfully implemented in vitro. Taken together these novel software platforms provide a complete toolchain, from design to wet-lab implementation, of synthetic biological circuits, enabling a step change in the scale of biological investigations that is orders of magnitude greater than could previously be performed in one in silico “pot”

Infobiotics : computer-aided synthetic systems biology

Until very recently Systems Biology has, despite its stated goals, been too reductive in terms of the models being constructed and the methods used have been, on the one hand, unsuited for large scale adoption or integration of knowledge across scales, and on the other hand, too fragmented. The thesis of this dissertation is that better computational languages and seamlessly integrated tools are required by systems and synthetic biologists to enable them to meet the significant challenges involved in understanding life as it is, and by designing, modelling and manufacturing novel organisms, to understand life as it could be. We call this goal, where everything necessary to conduct model-driven investigations of cellular circuitry and emergent effects in populations of cells is available without significant context-switching, “one-pot” in silico synthetic systems biology in analogy to “one-pot” chemistry and “one-pot” biology. Our strategy is to increase the understandability and reusability of models and experiments, thereby avoiding unnecessary duplication of effort, with practical gains in the efficiency of delivering usable prototype models and systems. Key to this endeavour are graphical interfaces that assists novice users by hiding complexity of the underlying tools and limiting choices to only what is appropriate and useful, thus ensuring that the results of in silico experiments are consistent, comparable and reproducible. This dissertation describes the conception, software engineering and use of two novel software platforms for systems and synthetic biology: the Infobiotics Workbench for modelling, in silico experimentation and analysis of multi-cellular biological systems; and DNA Library Designer with the DNALD language for the compact programmatic specification of combinatorial DNA libraries, as the first stage of a DNA synthesis pipeline, enabling methodical exploration biological problem spaces. Infobiotics models are formalised as Lattice Population P systems, a novel framework for the specification of spatially-discrete and multi-compartmental rule-based models, imbued with a stochastic execution semantics. This framework was developed to meet the needs of real systems biology problems: hormone transport and signalling in the root of Arabidopsis thaliana, and quorum sensing in the pathogenic bacterium Pseudomonas aeruginosa. Our tools have also been used to prototype a novel synthetic biological system for pattern formation, that has been successfully implemented in vitro. Taken together these novel software platforms provide a complete toolchain, from design to wet-lab implementation, of synthetic biological circuits, enabling a step change in the scale of biological investigations that is orders of magnitude greater than could previously be performed in one in silico “pot”

Cognitive Maps

undefine

Evolutionary genomics : statistical and computational methods

This open access book addresses the challenge of analyzing and understanding the evolutionary dynamics of complex biological systems at the genomic level, and elaborates on some promising strategies that would bring us closer to uncovering of the vital relationships between genotype and phenotype. After a few educational primers, the book continues with sections on sequence homology and alignment, phylogenetic methods to study genome evolution, methodologies for evaluating selective pressures on genomic sequences as well as genomic evolution in light of protein domain architecture and transposable elements, population genomics and other omics, and discussions of current bottlenecks in handling and analyzing genomic data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that lead to the best results. Authoritative and comprehensive, Evolutionary Genomics: Statistical and Computational Methods, Second Edition aims to serve both novices in biology with strong statistics and computational skills, and molecular biologists with a good grasp of standard mathematical concepts, in moving this important field of study forward