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Bioinformatics : an introduction / Jeremy Ramsden
Cham : Springer, 2023
402 pages. : illustrations (color) ; cm.
Ký hiệu phân loại (DDC): 570.285
This invaluable textbook presents a self-contained introduction to the field of bioinformatics. Providing a comprehensive breadth of coverage while remaining accessibly concise, the text promotes a deep understanding of the field, supported by basic mathematical concepts, an emphasis on biological knowledge, and a holistic approach that highlights the connections unifying bioinformatics with other areas of science. The thoroughly revised and enhanced fourth edition features new chapters focusing on regulation and control networks, the origins of life, evolution, statistics and causation, viruses, the microbiome, single cell analysis, drug discovery and forensic applications. This edition additionally includes new and updated material on the ontology of bioinformatics, data mining, ecosystems, and phenomics. Also covered are new developments in sequencing technologies, gene editing methods, and modelling of the brain, as well as state-of-the-art medical applications. Of special topicality is a new chapter on bioinformatics aspects of the coronavirus pandemic. Topics and features: Explains the fundamentals of set theory, combinatorics, probability, likelihood, causality, clustering, pattern recognition, randomness, complexity, systems, and networks Discusses topics on ontogeny, phylogeny, genome structure, and regulation, as well as aspects of molecular biology Critically examines the most significant practical applications, offering detailed descriptions of both the experimental process and the analysis of the data Provides a varied selection of problems throughout the book, to stimulate further thinking Encourages further reading through the inclusion of an extensive bibliography This classic textbook builds upon the successful formula of previous editions with coverage of the latest advances in this exciting and fast-moving field. With its interdisciplinary scope, this unique guide will prove to be an essential study companion to a broad audience of undergraduate and beginning graduate students, spanning computer scientists focusing on bioinformatics, students of the physical sciences seeking a helpful primer on biology, and biologists desiring to better understand the theory underlying important applications of information science in biology
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Bioinformatics algorithms : design and implementation in Python / Miguel P Rocha; Pedro G Ferreira
London, United Kingdom ; San Diego, CA, United States : Academic Press, an imprint of Elsevier,2018
395 pages. : illustrations ; 24 cm.
Ký hiệu phân loại (DDC): 570.285
Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications.
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Bioinformatics for evolutionary biologists / Bernhard Haubold; Angelika Börsch-Haubold
Switzerland : Springer Berlin Heidelberg, 2017.
323 pages. : illustrations
Ký hiệu phân loại (DDC): 570.285
This self-contained textbook covers fundamental aspects of sequence analysis in evolutionary biology, including sequence alignment, phylogeny reconstruction, and coalescent simulation. It addresses these aspects through a series of over 400 computer problems, ranging from elementary to research level to enable learning by doing. Students solve the problems in the same computational environment used for decades in science? the UNIX command line. This is available on all three major operating systems for PCs: Microsoft Windows, Mac-OSX, and Linux. To learn using this powerful system, students analyze sample sequence data by applying generic tools, bioinformatics software, and over 40 programs specifically written for this course. The solutions for all problems are included, making the book ideal for self-study. Problems are grouped into sections headed by an introduction and a list of new concepts and programs. By using practical computing to explore evolutionary concepts and sequence data, the book enables readers to tackle their own computational problems.
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4
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Bioinformatics with Python cookbook : use modern Python libraries and applications to solve real-world computational biology / Tiago Antao
Birmingham, UK : Packt Publishing Ltd., 2022
359 pages. : illustrations ; cm.
Ký hiệu phân loại (DDC): 572.8
Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python. This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you'll explore the application of machine learning algorithms in bioinformatics. By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale
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Computational genomics with R / Altuna Akalin
Boca Raton, FL : CRC Press, 2021
xxii, 440 pages. : illustrations (chiefly color) ; 26 cm.
Ký hiệu phân loại (DDC): 572.86
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology
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