Estimation Of Species Tree Using Approximate Bayesian Computation
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Author | : Osvaldo A. Martin |
Publisher | : CRC Press |
Total Pages | : 420 |
Release | : 2021-12-28 |
Genre | : Computers |
ISBN | : 1000520048 |
Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory. The book starts with a refresher of the Bayesian Inference concepts. The second chapter introduces modern methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian Computation, end to end case studies showing how to apply Bayesian modelling in different settings, and a chapter about the internals of probabilistic programming languages. Finally the last chapter serves as a reference for the rest of the book by getting closer into mathematical aspects or by extending the discussion of certain topics. This book is written by contributors of PyMC3, ArviZ, Bambi, and Tensorflow Probability among other libraries.
Author | : Ming-Hui Chen |
Publisher | : CRC Press |
Total Pages | : 398 |
Release | : 2014-05-27 |
Genre | : Mathematics |
ISBN | : 1466500794 |
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.
Author | : Alexei J. Drummond |
Publisher | : Cambridge University Press |
Total Pages | : 263 |
Release | : 2015-08-06 |
Genre | : Science |
ISBN | : 1316298345 |
What are the models used in phylogenetic analysis and what exactly is involved in Bayesian evolutionary analysis using Markov chain Monte Carlo (MCMC) methods? How can you choose and apply these models, which parameterisations and priors make sense, and how can you diagnose Bayesian MCMC when things go wrong? These are just a few of the questions answered in this comprehensive overview of Bayesian approaches to phylogenetics. This practical guide: • Addresses the theoretical aspects of the field • Advises on how to prepare and perform phylogenetic analysis • Helps with interpreting analyses and visualisation of phylogenies • Describes the software architecture • Helps developing BEAST 2.2 extensions to allow these models to be extended further. With an accompanying website providing example files and tutorials (http://beast2.org/), this one-stop reference to applying the latest phylogenetic models in BEAST 2 will provide essential guidance for all users – from those using phylogenetic tools, to computational biologists and Bayesian statisticians.
Author | : David J. Balding |
Publisher | : John Wiley & Sons |
Total Pages | : 1740 |
Release | : 2019-07-09 |
Genre | : Science |
ISBN | : 1119429250 |
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
Author | : Ziheng Yang |
Publisher | : Oxford University Press |
Total Pages | : 509 |
Release | : 2014 |
Genre | : Science |
ISBN | : 0199602603 |
Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods. The flood of genomic data has generated an acute need for powerful statistical methods and efficient computational algorithms to enable their effective analysis and interpretation. Molecular Evolution: a statistical approach presents and explains modern statistical methods and computational algorithms for the comparative analysis of genetic sequence data in the fields of molecular evolution, molecular phylogenetics, statistical phylogeography, and comparative genomics. Written by an expert in the field, the book emphasizes conceptual understanding rather than mathematical proofs. The text is enlivened with numerous examples of real data analysis and numerical calculations to illustrate the theory, in addition to the working problems at the end of each chapter. The coverage of maximum likelihood and Bayesian methods are in particular up-to-date, comprehensive, and authoritative. This advanced textbook is aimed at graduate level students and professional researchers (both empiricists and theoreticians) in the fields of bioinformatics and computational biology, statistical genomics, evolutionary biology, molecular systematics, and population genetics. It will also be of relevance and use to a wider audience of applied statisticians, mathematicians, and computer scientists working in computational biology.
Author | : Gina M. Cannarozzi |
Publisher | : Oxford University Press |
Total Pages | : 297 |
Release | : 2012-02-23 |
Genre | : Mathematics |
ISBN | : 019960116X |
The second part of the book focuses on codon usage bias.
Author | : Ziheng Yang |
Publisher | : Oxford University Press, USA |
Total Pages | : 374 |
Release | : 2006-10-05 |
Genre | : Medical |
ISBN | : 0198566999 |
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.
Author | : Mourad Elloumi |
Publisher | : John Wiley & Sons |
Total Pages | : 654 |
Release | : 2015-12-24 |
Genre | : Technology & Engineering |
ISBN | : 1119078865 |
A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.
Author | : Haixu Tang |
Publisher | : Springer Nature |
Total Pages | : 297 |
Release | : 2023-04-02 |
Genre | : Computers |
ISBN | : 3031291190 |
This book constitutes the refereed proceedings of the 27th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2023, held in Istanbul, Turkey, during April 16–19, 2023. The 11 regular and 33 short papers presented in this book were carefully reviewed and selected from 188 submissions. The papers report on original research in all areas of computational molecular biology and bioinformatics.
Author | : Laszlo Patthy |
Publisher | : John Wiley & Sons |
Total Pages | : 392 |
Release | : 2009-03-12 |
Genre | : Science |
ISBN | : 1444308882 |
This book provides an up-to-date summary of the principles of protein evolution and discusses both the methods available to analyze the evolutionary history of proteins as well as those for predicting their structure-function relationships. Includes a significantly expanded chapter on genome evolution to cover genomes of model organisms sequenced since the completion of the first edition, and organelle genome evolution Retains its reader-friendly, accessible style and organization Contains an updated glossary and new references, including a list of online reference sites