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

Ontology Alignment using Biologically-inspired Optimisation Algorithms

It is investigated how biologically-inspired optimisation methods can be used to compute alignments between ontologies. Independent of particular similarity metrics, the developed techniques demonstrate anytime behaviour and high scalability. Due to the inherent parallelisability of these population-based algorithms it is possible to exploit dynamically scalable cloud infrastructures - a step towards the provisioning of Alignment-as-a-Service solutions for future semantic applications

ENABLING EFFICIENT AND STREAMLINED ACCESS TO LARGE SCALE GENOMIC EXPRESSION AND SPLICING DATA

As more and larger genomics studies appear, there is a growing need for comprehensive and queryable cross-study summaries. We focus primarily on nearly 20,000 RNA-sequencing studies in human and mouse, consisting of more than 750,000 sequencing runs, and the coverage summaries derived from their alignment to their respective gnomes. In addition to the summarized RNA-seq derived data itself we present tools (Snaptron, Monorail, Megadepth, and recount3) that can be used by downstream researchers both to process their own data into comparable summaries as well as access and query our processed, publicly available data. Additionally we present a related study of errors in the splicing of long read transcriptomic alignments, including comparison to the existing splicing summaries from short reads already described (LongTron)

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