Download or read book Computational Methods in Phylogenetic Analysis written by Arun K. Jagota and published by Arun Jagota. This book was released on 2005-04-01 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of phylogenetic analysis is to reconstruct the phylogeny (evolutionary history) of a set of organisms or genes from present-day data. Since this involves inferring past events from present-day data, this is a difficult endeavor. Even so, it must be done, for it is scientifically important and practically useful to do so. Phylogeneticists – those who do this for a living – are finding modern computational methods to be quite useful in this arduous task. This short book presents the main computational methods in present use in this field, as well as some on the cutting edge. These methods are presented in the setting of building binary trees (rooted or unrooted) from molecular sequence data. Some of these methods are applicable to other types of data as well. This book is written from the quantitative perspective. The author has aimed to present the algorithms and ideas in sufficient depth and at a formal level for someone to be able to implement them, or even adapt them to new situations. This book may also be used in a graduate or upper-division undergraduate course on the topic (one in which the computational perspective is emphasized) or as an adjunct in a course on bioinformatics. Towards this use, there are a number of pictures and examples included to assist student readers in understanding the ideas. There are also exercise questions included at the end of several chapters. The first chapter is on substitution models, stochastic processes, and substitution matrices, the second on distance-based tree-building methods, the third on parsimony-based tree-building methods, the fourth on probabilistic tree-building methods, and the fifth on finding consensus features in built trees. The sixth and the seventh chapters present more cutting edge material, on sequence graphs and aligning them, and on using sequence graphs for building a phylogenetic tree from unaligned sequences. The eighth chapter is on comparing and aligning trees. The ninth chapter presents some other interesting computational problems in phylogenetic analysis — for instance, phylogenetic networks for handling convergent evolution.

Download or read book Computational Phylogenetics written by Tandy Warnow and published by Cambridge University Press. This book was released on 2018 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the foundations of phylogeny estimation and technical material enabling researchers to develop improved computational methods.

Download or read book Bioinformatics and Phylogenetics written by Tandy Warnow and published by Springer. This book was released on 2019-04-08 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Computational Methods to Resolve Deep Species Phylogenies written by Jeremy Mark Jian Ming Levy and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Molecular Evolution written by Ziheng Yang and published by Oxford University Press, USA. This book was released on 2006-10-05 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes.

Download or read book Bayesian Phylogenetics written by Ming-Hui Chen and published by CRC Press. This book was released on 2014-05-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods, Algorithms, and Applications presents a snapshot of current trends in Bayesian phylogenetic research. Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the-art Bayesian statistics to the phylogenetics community. The book emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. It also discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. In addition, the book covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.

Download or read book Molecular Evolution and Phylogenetics written by Masatoshi Nei and published by Oxford University Press. This book was released on 2000-07-27 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last ten years, remarkable progress has occurred in the study of molecular evolution. Among the most important factors that are responsible for this progress are the development of new statistical methods and advances in computational technology. In particular, phylogenetic analysis of DNA or protein sequences has become a powerful tool for studying molecular evolution. Along with this developing technology, the application of the new statistical and computational methods has become more complicated and there is no comprehensive volume that treats these methods in depth. Molecular Evolution and Phylogenetics fills this gap and present various statistical methods that are easily accessible to general biologists as well as biochemists, bioinformatists and graduate students. The text covers measurement of sequence divergence, construction of phylogenetic trees, statistical tests for detection of positive Darwinian selection, inference of ancestral amino acid sequences, construction of linearized trees, and analysis of allele frequency data. Emphasis is given to practical methods of data analysis, and methods can be learned by working through numerical examples using the computer program MEGA2 that is provided.

Download or read book Computational Methods in Protein Evolution written by Tobias Sikosek and published by Humana. This book was released on 2018-10-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a diverse collection of methodologies used to study various problems at the protein sequence and structure level. The chapters in this book look at issues ranging from broad concepts like protein space to specifics like antibody modeling. Topics include point mutations, gene duplication, de novo emergence of new genes, pairwise correlated mutations, ancestral protein reconstruction, homology modelling, protein stability and dynamics, and protein-protein interactions. The book also covers a wide range of computational approaches, including sequence and structure alignments, phylogenies, physics-based and mathematical approaches, machine learning, and more. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and prerequisites, step-by-step, readily reproducible computational protocols (using command line or graphical user interfaces, sometimes including computer code), and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and authoritative, Computational Methods in Protein Evolution is a valuable resource that offers useful workflows and techniques that will help both novice and expert researchers working with proteins computationally.

Download or read book Computational Molecular Evolution written by Ziheng Yang and published by OUP Oxford. This book was released on 2006-10-05 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods. The increasing availability of large genomic data sets requires powerful statistical methods to analyse and interpret them, generating both computational and conceptual challenges for the field. Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics. Yang describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes. The book emphasizes essential concepts rather than mathematical proofs. It includes detailed derivations and implementation details, as well as numerous illustrations, worked examples, and exercises. It will be of relevance and use to students and professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, population genetics, mathematics, statistics and computer science. Biologists who have used phylogenetic software programs to analyze their own data will find the book particularly rewarding, although it should appeal to anyone seeking an authoritative overview of this exciting area of computational biology.

Download or read book Computational Methods for Microbiome Analysis written by Joao Carlos Setubal and published by Frontiers Media SA. This book was released on 2021-02-02 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Tree with Many Branches written by Tommy Rodriguez and published by iUniverse. This book was released on 2020-08-20 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Want to build an evolutionary tree? Here’s your chance to learn how. The field of bioinformatics was born out of the need to manage, analyze, and examine raw genomic data in meaningful and exciting ways, such as the discipline of computational phylogenetics would provide. The evolutionary inferences reached among the several peer-reviewed articles contained in this book are neither novel nor breakthrough. However, it is in the application of computational techniques, experiment design, and probabilistic models where this research finds a stronghold. As a matter of practicality, the original manuscripts have been edited for a broader audience due to its highly technical language. The essays compiled in these pages have undergone a facelift, from their original scientific format into a more reader-friendly layout, as to better accommodate two different perspectives – both experts and non-experts alike.

Download or read book Analysis of Phylogenetics and Evolution with R written by Emmanuel Paradis and published by Springer Science & Business Media. This book was released on 2006-11-25 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.

Download or read book Computational Frameworks for Indel aware Evolutionary Analysis Using Large scale Genomic Sequence Data written by Wei Wang and published by . This book was released on 2021 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the development of sequencing techniques, genetic sequencing data has been extensively used in evolutionary studies. The phylogenetic reconstruction problem, which is the reconstruction of evolutionary history from biomolecular sequences, is a fundamental problem. The evolutionary relationship between organisms is often represented by phylogeny, which is a tree or network representation. The most widely-used approach for reconstructing phylogenies from sequencing data involves two phases: multiple sequence alignment and phylogenetic reconstruction from the aligned sequences. As the amount of biomolecular sequence data increases, it has become a major challenge to develop efficient and accurate computational methods for phylogenetic analyses of large-scale sequencing data. Due to the complexity of the phylogenetic reconstruction problem in modern phylogenetic studies, the traditional sequence-based phylogenetic analysis methods involve many over-simplified assumptions. In this thesis, we describe our contribution in relaxing some of these over-simplified assumptions in the phylogenetic analysis.Insertion and deletion events, referred to as indels, carry much phylogenetic information but are often ignored in the reconstruction process of phylogenies. We take into account the indel uncertainties in multiple phylogenetic analyses by applying resampling and re-estimation. Another over-simplified assumption that we contributed to is adopted by many commonly used non-parametric algorithms for the resampling of biomolecular sequences, all sites in an MSA are evolved independently and identically distributed (i.i.d). Many evolution events, such as recombination and hybridization, may produce intra-sequence and functional dependence in biomolecular sequences that violate this assumption. We introduce SERES, a resampling algorithm for biomolecular sequences that can produce resampled replicates that preserve the intra-sequence dependence. We describe the application of the SERES resampling and re-estimation approach to two classical problems: the multiple sequence alignment support estimation and recombination-aware local genealogical inference. We show that these two statistical inference problems greatly benefit from the indel-aware resampling and re-estimation approach and the reservation of intra-sequence dependence.A major drawback of SERES is that it requires parameters to ensure the synchronization of random walks on unaligned sequences. We introduce RAWR, a non-parametric resampling method designed for phylogenetic tree support estimation that does not require extra parameters. We show that the RAWR-based resampling and re-estimation method produces comparable or typically better performance than the traditional bootstrap approach on the phylogenetic tree support estimation problem.We further relax the commonly used assumption of phylogeny. Evolutionary history is usually considered as a tree structure. Evolutionary events that cause reticulated gene flow are ignored. Previous studies show that alignment uncertainty greatly impacts downstream tree inference and learning. However, there is little discussion about the impact of MSA uncertainties on the phylogenetic network reconstruction. We show evidence that the errors introduced in MSA estimation decrease the accuracy of the inferred phylogenetic network, and an indel-aware reconstruction method is needed for phylogenetic network analysis.In this dissertation, we introduce our contribution to phylogenetic estimation using biomolecular sequence data involving complex evolutionary histories, such as sequence insertion and deletion processes and non-tree-like evolution.

Download or read book Bayesian Phylogenetics written by Ming-Hui Chen and published by CRC Press. This book was released on 2014-05-27 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods, Algorithms, and Applications presents a snapshot of c

Download or read book Big data Computational Methods for Studying Molecular Evolution written by 余光创 and published by . This book was released on 2017 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Biology written by Scott T. Kelley and published by John Wiley & Sons. This book was released on 2020-08-06 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the world of bioinformatics Massive increases in computing power and the ability to routinely sequence whole genomes of living organisms have begun to fundamentally alter our understanding of biology, medicine, and agriculture. At the intersection of the growing information and genomics revolutions sits bioinformatics, which uses modern computational power to reveal patterns in biological data sets, especially DNA, RNA, and protein sequences. Computational Biology: A Hypertextbook, by Scott Kelley and Dennis Didulo, provides a wonderful introduction for anyone who wants to learn the basics of bioinformatics. This book is more than a textbook because of the wealth of online ancillary materials and how the print and electronic components are integrated to form a complete educational resource. Aspects that make Computational Biology: A Hypertextbook a unique and valuable tool for teaching and learning bioinformatics include Clear explanations of the basic biology of DNA, RNA, and proteins and how the related bioinformatics algorithms work Extensive exercises that enable students to practice with the same bioinformatics applications that are used by scientists worldwide Tutorials, sample data sets, and interactive learning tools developed with teachers in mind and field-tested by hundreds of students Online tutorials and curated web links that are accurate (instead of frustrating!) and won't lead to dead ends Online resources that work on multiple platforms and electronic devices Computational Biology: A Hypertextbook is written in an accessible voice, punctuated with humor, and designed to significantly increase computational competencies. Biology and computer science undergraduate and graduate students will thoroughly enjoy learning from this unique hypertextbook, as will anyone with an interest in exploring this burgeoning topic.

Download or read book Computational Methods For Understanding Bacterial And Archaeal Genomes written by Ying Xu and published by World Scientific. This book was released on 2008-08-06 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative view of bacterial and archaeal genomes, and how information is encoded differently in them, is also presented. Combining theoretical discussions and computational techniques, the book serves as a valuable introductory textbook for graduate-level microbial genomics and informatics courses./a