Bücher der Reihe Computational Biology

This unique text describes the state-of-the-art in computational gene finding, with a particular focus on comparative approaches. It summarizes advances in the field and includes detailed descriptions of the models and algorithms and how to implement them.

This volume presents a compelling collection of state-of-the-art work in algorithmic computational biology, honoring the legacy of Professor Bernard M.E. Moret in this field. Reflecting the wide-ranging influences of Prof. Moret's research, the coverage encompasses such areas as phylogenetic tree and network estimation, genome rearrangements, cancer phylogeny, species trees, divide-and-conquer strategies, and integer linear programming. Each self-contained chapter provides an introduction to a cutting-edge problem of particular computational and mathematical interest.Topics and features: addresses the challenges in developing accurate and efficient software for the NP-hard maximum likelihood phylogeny estimation problem; describes the inference of species trees, covering strategies to scale phylogeny estimation methods to large datasets, and the construction of taxonomic supertrees; discusses the inference of ultrametric distances from additive distance matrices, and the inference of ancestral genomes under genome rearrangement events; reviews different techniques for inferring evolutionary histories in cancer, from the use of chromosomal rearrangements to tumor phylogenetics approaches; examines problems in phylogenetic networks, including questions relating to discrete mathematics, and issues of statistical estimation; highlights how evolution can provide a framework within which to understand comparative and functional genomics; provides an introduction to Integer Linear Programming and its use in computational biology, including its use for solving the Traveling Salesman Problem.Offering an invaluable source of insights for computer scientists, applied mathematicians, and statisticians, this illuminating volume will also prove useful for graduate courses on computational biology and bioinformatics.

This book presents a focus on proteins and their structures. The text describes various scalable solutions for protein structure similarity searching, carried out at main representation levels and for prediction of 3D structures of proteins. Emphasis is placed on techniques that can be used to accelerate similarity searches and protein structure modeling processes.The content of the book is divided into four parts. The first part provides background information on proteins and their representation levels, including a formal model of a 3D protein structure used in computational processes, and a brief overview of the technologies used in the solutions presented in the book. The second part of the book discusses Cloud services that are utilized in the development of scalable and reliable cloud applications for 3D protein structure similarity searching and protein structure prediction. The third part of the book shows the utilization of scalable Big Data computational frameworks, like Hadoop and Spark, in massive 3D protein structure alignments and identification of intrinsically disordered regions in protein structures. The fourth part of the book focuses on finding 3D protein structure similarities, accelerated with the use of GPUs and the use of multithreading and relational databases for efficient approximate searching on protein secondary structures.The book introduces advanced techniques and computational architectures that benefit from recent achievements in the field of computing and parallelism. Recent developments in computer science have allowed algorithms previously considered too time-consuming to now be efficiently used for applications in bioinformatics and the life sciences. Given its depth of coverage, the book will be of interest to researchers and software developers working in the fields of structural bioinformatics and biomedical databases.

This book describes core processes of replication, mutation, neutral evolution and natural selection, genome evolution in prokaryotes, eukaryotes, vertebrates and humans, genome sequencing amd more, offering worked-out examples and extensive appendices.

To help perform such navigation tasks successfully, this book starts by providing an extremely useful overview of existing tools for ?nding (or designing) and inv- tigating metabolic, genetic, signaling, and other network databases, addressing also user-relevant practical questions like * Is the database viewable through a web browser?

The advances of live cell video imaging and high-throughput technologies for functional and chemical genomics provide unprecedented opportunities to understand how biological processes work in subcellularand multicellular systems. The interdisciplinary research field of Video Bioinformatics is defined by BirBhanu as the automated processing, analysis, understanding, data mining, visualization, query-basedretrieval/storage of biological spatiotemporal events/data and knowledge extracted from dynamic imagesand microscopic videos. Video bioinformatics attempts to provide a deeper understanding of continuousand dynamic life processes.Genome sequences alone lack spatial and temporal information, and video imaging of specific moleculesand their spatiotemporal interactions, using a range of imaging methods, are essential to understandhow genomes create cells, how cells constitute organisms, and how errant cells cause disease. The bookexamines interdisciplinary research issues and challenges with examples that deal with organismal dynamics,intercellular and tissue dynamics, intracellular dynamics, protein movement, cell signaling and softwareand databases for video bioinformatics.Topics and Features¿ Covers a set of biological problems, their significance, live-imaging experiments, theory andcomputational methods, quantifiable experimental results and discussion of results.¿ Provides automated methods for analyzing mild traumatic brain injury over time, identifying injurydynamics after neonatal hypoxia-ischemia and visualizing cortical tissue changes during seizure

This unique textbook/reference presents unified coverage of bioinformatics topics relating to both biological sequences and biological networks, providing an in-depth analysis of cutting-edge distributed algorithms, as well as of relevant sequential algorithms.

This book explores association mapping in experimental populations and genome-wide association studies (GWAS), emphasizing methods based on modifications of Bayesian information criterion, for handling testing problems in large-scale scans for trait loci.

discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques;

discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques;

Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology.

This interpretation enables a remarkably unified view of the entire field of biology to be taken and hence offers an excellent entry point into the life sciences for those for whom biology is unfamiliar.

This book describes core processes of replication, mutation, neutral evolution and natural selection, genome evolution in prokaryotes, eukaryotes, vertebrates and humans, genome sequencing amd more, offering worked-out examples and extensive appendices.

The biological interactions of living organisms, and protein-protein interactions in particular, are astonishingly diverse.

A comprehensive account of genomic rearrangement, focusing on the mechanisms of inversion, translocation, gene and genome duplication and gene transfer and on the patterns that result from them in comparative maps.

The biological interactions of living organisms, and protein-protein interactions in particular, are astonishingly diverse.

This book provides a timely and first-of-its-kind collection of papers on anatomy ontologies. The book aims to provide readers with a comprehensive understanding of the foundations of anatomical ontologies and the-state-of-the-art in terms of existing tools and applications.

Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology.

This book provides a comprehensive look at supertrees, ranging from the methods used to build supertrees to the significance of supertrees to bioinformatic and biological research.

Biomolecular sequence comparison is the origin of bioinformatics. This book gives a complete in-depth treatment of the study of sequence comparison. The book examines alignment methods and techniques, and features a new issue of sequence comparison.

This book provides a comprehensive look at supertrees, ranging from the methods used to build supertrees to the significance of supertrees to bioinformatic and biological research.

This authoritative textbook/reference presents a comprehensive introduction to the field of evolutionary genomics. The opening chapters describe the fundamental concepts in molecular biology and genome evolution for readers without any prior background in this area. This is followed by a detailed examination of genome evolution in various different groups of organisms. The text then concludes with a review of practical methods essential to researchers in the field.This updated and revised new edition also features historical perspectives on contributions to evolutionary genomics from related fields such as molecular evolution, genetics, and numerical taxonomy.Topics and features: introduces the basics of molecular biology, covering protein structure and diversity, as well as DNA replication, transcription, and translation; examines the phylogenetic relationships of DNA sequences, and the processes of mutation, neutral evolution, and natural selection; presents a briefevolutionary history of life, surveying the key features of the genomes of prokaryotes, eukaryotes, viruses and phages, vertebrates, and humans; reviews the various biological ¿omic¿ databases, and discusses the analysis of homologous nucleotide and amino acid sequences; provides an overview of the experimental sequencing of genomes and transcriptomes, and the construction of phylogenetic trees; describes methods for estimating of evolutionary distances, and performing studies of population genetics; supplies additional supporting material at an associated website.Serving as an indispensable textbook for graduate and advanced undergraduate courses on evolutionary genomics, this accessible overview will also prove invaluable to researchers from both computer science and the biological sciences seeking a primer on the field.

Specifically, it discusses an array of techniques related to biological network clustering, network summarization, and differential network analysis which enable readers to uncover the functional and topological organization hidden in a large biological network.

This authoritative text/reference presents a review of the history, current status, and potential future directions of computational biology in molecular evolution.

This authoritative text/reference presents a review of the history, current status, and potential future directions of computational biology in molecular evolution.

A comprehensive account of genomic rearrangement, focusing on the mechanisms of inversion, translocation, gene and genome duplication and gene transfer and on the patterns that result from them in comparative maps.

The problem many microbiologists face is simply that of too much information. Built around teaching computational and bioinformatic methodology, this book details published methods for comparing genomes and provides examples of how to make custom comparisons.

Gives a thorough and systematic introduction to probabilistic modeling in bioinformatics. This book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. It also gives examples of known architectures (such as, profile HMM) used in genome analysis.