Models and Algorithms for Whole-genome Evolution and Their Use in Phylogenetic Inference - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Models and Algorithms for Whole-genome Evolution and Their Use in Phylogenetic Inference write by Yu Lin. This book was released on 2012. Models and Algorithms for Whole-genome Evolution and Their Use in Phylogenetic Inference available in PDF, EPUB and Kindle.
Models and Algorithms for Genome Evolution
Models and Algorithms for Genome Evolution - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Models and Algorithms for Genome Evolution write by Cedric Chauve. This book was released on 2013-09-17. Models and Algorithms for Genome Evolution available in PDF, EPUB and Kindle. This authoritative text/reference presents a review of the history, current status, and potential future directions of computational biology in molecular evolution. Gathering together the unique insights of an international selection of prestigious researchers, this must-read volume examines the latest developments in the field, the challenges that remain, and the new avenues emerging from the growing influx of sequence data. These viewpoints build upon the pioneering work of David Sankoff, one of the founding fathers of computational biology, and mark the 50th anniversary of his first scientific article. The broad spectrum of rich contributions in this essential collection will appeal to all computer scientists, mathematicians and biologists involved in comparative genomics, phylogenetics and related areas.
Enhance the Understanding of Whole-genome Evolution by Designing, Accelerating and Parallelizing Phylogenetic Algorithms
Enhance the Understanding of Whole-genome Evolution by Designing, Accelerating and Parallelizing Phylogenetic Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Enhance the Understanding of Whole-genome Evolution by Designing, Accelerating and Parallelizing Phylogenetic Algorithms write by Zhaoming Yin. This book was released on 2014. Enhance the Understanding of Whole-genome Evolution by Designing, Accelerating and Parallelizing Phylogenetic Algorithms available in PDF, EPUB and Kindle. The advent of new technology enhance the speed and reduce the cost for sequencing biological data. Making biological sense of this genomic data is a big challenge to the algorithm design as well as the high performance computing society. There are many problems in Bioinformatics, such as how new functional genes arise, why genes are organized into chromosomes, how species are connected through the evolutionary tree of life, or why arrangements are subject to change. Phylogenetic analyses have become essential to research on the evolutionary tree of life. It can help us to track the history of species and the relationship between different genes or genomes through millions of years. One of the fundamentals for phylogenetic construction is the computation of distances between genomes. Since there are much more complicated combinatoric patterns in rearrangement events, the distance computation is still a hot topic as much belongs to mathematics as to biology. For the distance computation with input of two genomes containing unequal gene contents (with insertions/deletions and duplications) the problem is especially hard. In this thesis, we will discuss about our contributions to the distance estimation for unequal gene order data. The problem of finding the median of three genomes is the key process in building the most parsimonious phylogenetic trees from genome rearrangement data. For genomes with unequal contents, to the best of our knowledge, there is no algorithm that can help to find the median. In this thesis, we make our contributions to the median computation in two aspects. 1) Algorithm engineering aspect, we harness the power of streaming graph analytics methods to implement an exact DCJ median algorithm which run as fast as the heuristic algorithm and can help construct a better phylogenetic tree. 2) Algorithmic aspect, we theoretically formulate the problem of finding median with input of genomes having unequal gene content, which leads to the design and implementation of an efficient Lin-Kernighan heuristic based median algorithm. Inferring phylogenies (evolutionary history) of a set of given species is the ultimate goal when the distance and median model are chosen. For more than a decade, biologists and computer scientists have studied how to infer phylogenies by the measurement of genome rearrangement events using gene order data. While evolution is not an inherently parsimonious process, maximum parsimony (MP) phylogenetic analysis has been supported by widely applied to the phylogeny inference to study the evolutionary patterns of genome rearrangements. There are generally two problems with the MP phylogenetic arose by genome rearrangement: One is, given a set of modern genomes, how to compute the topologies of the according phylogenetic tree; Another is, given the topology of a model tree, how to infer the gene orders of the ancestor species. To assemble a MP phylogenetic tree constructor, there are multiple NP hard problems involved, unfortunately, they organized as one problem on top of other problems. Which means, to solve a NP hard problem, we need to solve multiple NP hard sub-problems. For phylogenetic tree construction with the input of unequal content genomes, there are three layers of NP hard problems. In this thesis, we will mainly discuss about our contributions to the design and implementation of the software package DCJUC (Phylogeny Inference using DCJ model to cope with Unequal Content Genomes), that can help to achieve both of these two goals. Aside from the biological problems, another issue we need to concern is about the use of the power of parallel computing to assist accelerating algorithms to handle huge data sets, such as the high resolution gene order data. For one thing, all of the method to tackle with phylogenetic problems are based on branch and bound algorithms, which are quite irregular and unfriendly to parallel computing. To parallelize these algorithms, we need to properly enhance the efficiency for localized memory access and load balance methods to make sure that each thread can put their potentials into full play. For the other, there is a revolution taking place in computing with the availability of commodity graphical processors such as Nvidia GPU and with many-core CPUs such as Cray-XMT, or Intel Xeon Phi Coprocessor with 60 cores. These architectures provide a new way for us to achieve high performance at much lower cost. However, code running on these machines are not so easily programmed, and scientific computing is hard to tune well on them. We try to explore the potentials of these architectures to help us accelerate branch and bound based phylogenetic algorithms.
Distance-aware Algorithms for Scalable Evolutionary and Ecological Analyses
Distance-aware Algorithms for Scalable Evolutionary and Ecological Analyses - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Distance-aware Algorithms for Scalable Evolutionary and Ecological Analyses write by Metin Balaban. This book was released on 2022. Distance-aware Algorithms for Scalable Evolutionary and Ecological Analyses available in PDF, EPUB and Kindle. Thanks to the advances in sequencing technologies in the last two decades, the set of available whole-genome sequences has been expanding rapidly. One of the challenges in phylogenetics is accurate large-scale phylogenetic inference based on whole-genome sequences. A related challenge is using incomplete genome-wide data in an assembly-free manner for accurate sample identification with reference to phylogeny. This dissertation proposes new scalable and accurate algorithms to address these two challenges. First, I present a family of scalable methods called TreeCluster for breaking a large set of sequences into evolutionary homogeneous clusters. Second, I present two algorithms for accurate phylogenetic placement of genomic sequences on ultra-large single-gene and whole-genome based trees. The first version, APPLES, scales linearly with the reference size while APPLES-2 scales sub-linearly thanks to a divide-and-conquer strategy based on the TreeCluster method. Third, I develop a solution for assembly-free sample phylogenetic placement for a particularly challenging case when the specimen is a mixture of two cohabiting species or a hybrid of two species. Fourth, I address one limitation of assembly-free methods--their reliance on simple models of sequence evolution--by developing a technique to compute evolutionary distances under a complex 4-parameter model called TK4. Finally, I introduce a divide-and-conquer workflow for incrementally growing and updating ultra-large phylogenies using many of the ingredients developed in other chapters. This workflow (uDance) is accurate in simulations and can build a 200,000-genome microbial tree-of-life based on 388 marker genes.
Reconstructing Evolution
Reconstructing Evolution - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reconstructing Evolution write by Olivier Gascuel. This book was released on 2007-06-28. Reconstructing Evolution available in PDF, EPUB and Kindle. Evolution is a complex process, acting at multiple scales, from DNA sequences and proteins to populations of species. Understanding and reconstructing evolution is of major importance in numerous subfields of biology. For example, phylogenetics and sequence evolution is central to comparative genomics, attempts to decipher genomes, and molecular epidemiology. Phylogenetics is also the focal point of large-scale international biodiversity assessment initiatives such as the 'Tree of Life' project, which aims to build the evolutionary tree for all extant species. Since the pioneering work in phylogenetics in the 1960s, models have become increasingly sophisticated to account for the inherent complexity of evolution. They rely heavily on mathematics and aim at modelling and analyzing biological phenomena such as horizontal gene transfer, heterogeneity of mutation, and speciation and extinction processes. This book presents these recent models, their biological relevance, their mathematical basis, their properties, and the algorithms to infer them from data. A number of subfields from mathematics and computer science are involved: combinatorics, graph theory, stringology, probabilistic and Markov models, information theory, statistical inference, Monte Carlo methods, continuous and discrete algorithmics. This book arises from the Mathematics of Evolution & Phylogenetics meeting at the Mathematical Institute Henri Poincaré, Paris, in June 2005 and is based on the outstanding state-of-the-art reports presented by the conference speakers. Ten chapters - based around five themes - provide a detailed overview of key topics, from the underlying concepts to the latest results, some of which are at the forefront of current research.
