Integer Linear Programming In Computational And Systems Biology
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Integer Linear Programming In Computational And Systems Biology
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Author : Dan Gusfield
language : en
Publisher: Cambridge University Press
Release Date : 2019-06-13
Integer Linear Programming In Computational And Systems Biology written by Dan Gusfield and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-13 with Computers categories.
This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.
Computational Phylogenetics
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Author : Tandy Warnow
language : en
Publisher: Cambridge University Press
Release Date : 2018
Computational Phylogenetics written by Tandy Warnow and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computers categories.
This book presents the foundations of phylogeny estimation and technical material enabling researchers to develop improved computational methods.
Algorithms For Computational Biology
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Author : Carlos Martín-Vide
language : en
Publisher: Springer Nature
Release Date : 2020-03-23
Algorithms For Computational Biology written by Carlos Martín-Vide and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-23 with Computers categories.
This book constitutes the proceedings of the 7th International Conference on Algorithms for Computational Biology, AlCoB 2020, was planned to be held in Missoula, MT, USA in April 2020. Due to the corona pandemic the conference was postponed to be held together with AlCoB 2021. The 15 full papers included in this volume were carefully reviewed and selected from 24 submissions. They were organized in topical sections on genomics, phylogenetics, and RNA-Seq and other biological processes.
Linear And Integer Optimization
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Author : Gerard Sierksma
language : en
Publisher: CRC Press
Release Date : 2015-05-01
Linear And Integer Optimization written by Gerard Sierksma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-01 with Business & Economics categories.
Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig's simplex algorithm, duality, sensitivity analysis, integer optimization models
Application Of Linear And Integer Programming To Three Challenging Problems In Computational Biology
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Author : Hooman Zabeti
language : en
Publisher:
Release Date : 2021
Application Of Linear And Integer Programming To Three Challenging Problems In Computational Biology written by Hooman Zabeti and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Linear Programming (LP) and Integer Linear Programming (ILP) have increasingly been used in computational and systems biology methods in the past 24 years. From RNA and protein structure prediction to analyzing biological networks, ILP and ILP-based methods provide natural, easy to maintain, and extendable solutions for many NP-hard biological optimization problems. This thesis aims to provide solutions to three challenging problems in system biology, infectious disease, and epidemiology. First, we present a four-step framework to verify and diagnose elemental balance violation in metabolic networks. Identifying such violations can be specifically challenging since chemical formulas of the metabolites in a metabolic network are often partially or entirely left unspecified. However, our framework is able to detect such violations efficiently and makes suggestions for correction without the need for specifying the chemical formula for each metabolite. We have applied our framework to a collection of 94 previously published metabolic network models and successfully detected elemental balance violations in 46 of them. Next, we introduce INGOT-DR, an interpretable classifier for predicting drug resistance. Our classifier utilizes group testing and Boolean compressed sensing to provide highly accurate and interpretable predictions, which could be helpful to investigate the mechanism of drug resistance in pathogenic bacteria such as Mycobacterium tuberculosis. Our method is also flexible enough to be optimized for various evaluation metrics at the same time. INGOT- DR has been tested for predicting drug resistance on five first-line and seven second-line antibiotics used for treating tuberculosis and showed higher or comparable accuracy to commonly used machine learning models for phenotype-genotype prediction. Our method was also able to identify variants located in genes previously reported to be associated with drug resistance. Finally, we present GroupTesing, a modular software platform for a comprehensive evaluation of non-adaptive group testing strategies. This software can perform the evaluation in both a noiseless setting and in the presence of single or multiple realistic noise sources modeled on published experimental observations, which makes them applicable to polymerase chain reaction (PCR) tests, the dominant type of tests for SARS-CoV-2.
Bioinformatics And Phylogenetics
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Author : Tandy Warnow
language : en
Publisher: Springer
Release Date : 2019-04-08
Bioinformatics And Phylogenetics written by Tandy Warnow and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-08 with Science categories.
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.
Applied Integer Programming
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Author : Der-San Chen
language : en
Publisher: John Wiley & Sons
Release Date : 2010-01-12
Applied Integer Programming written by Der-San Chen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-12 with Mathematics categories.
An accessible treatment of the modeling and solution of integer programming problems, featuring modern applications and software In order to fully comprehend the algorithms associated with integer programming, it is important to understand not only how algorithms work, but also why they work. Applied Integer Programming features a unique emphasis on this point, focusing on problem modeling and solution using commercial software. Taking an application-oriented approach, this book addresses the art and science of mathematical modeling related to the mixed integer programming (MIP) framework and discusses the algorithms and associated practices that enable those models to be solved most efficiently. The book begins with coverage of successful applications, systematic modeling procedures, typical model types, transformation of non-MIP models, combinatorial optimization problem models, and automatic preprocessing to obtain a better formulation. Subsequent chapters present algebraic and geometric basic concepts of linear programming theory and network flows needed for understanding integer programming. Finally, the book concludes with classical and modern solution approaches as well as the key components for building an integrated software system capable of solving large-scale integer programming and combinatorial optimization problems. Throughout the book, the authors demonstrate essential concepts through numerous examples and figures. Each new concept or algorithm is accompanied by a numerical example, and, where applicable, graphics are used to draw together diverse problems or approaches into a unified whole. In addition, features of solution approaches found in today's commercial software are identified throughout the book. Thoroughly classroom-tested, Applied Integer Programming is an excellent book for integer programming courses at the upper-undergraduate and graduate levels. It also serves as a well-organized reference for professionals, software developers, and analysts who work in the fields of applied mathematics, computer science, operations research, management science, and engineering and use integer-programming techniques to model and solve real-world optimization problems.
Advances In Computing And Data Sciences
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Author : Mayank Singh
language : en
Publisher: Springer Nature
Release Date : 2023-08-23
Advances In Computing And Data Sciences written by Mayank Singh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-23 with Computers categories.
This book constitutes the refereed proceedings of the 7th International Conference on Advances in Computing and Data Sciences, ICACDS 2023, held in Kolkata, India, during April 27–28, 2023. The 47 full papers included in this book were carefully reviewed and selected from 22 submissions. The papers focus on advances of next generation computing technologies in the areas of advanced computing and data sciences.
Feasibility And Infeasibility In Optimization
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Author : John W. Chinneck
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-25
Feasibility And Infeasibility In Optimization written by John W. Chinneck and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-25 with Mathematics categories.
Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.
Algorithms In Structural Molecular Biology
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Author : Bruce R. Donald
language : en
Publisher: MIT Press
Release Date : 2023-08-15
Algorithms In Structural Molecular Biology written by Bruce R. Donald and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-15 with Science categories.
An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field.