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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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2
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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Computational systems bioinformatics :methods and biomedical applications /Xiaobo Zhou, Stephen T. C. Wong
New Jersey : World Scientific, 2008
x, 387 pages. : illustrations (some color) ; 24 cm
Ký hiệu phân loại (DDC): 572.8
"This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research."--Jacket
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Next generation sequencing and data analysis / Melanie Kappelmann-Fenzl (editor)
Cham : Springer, 2021
xii, 218 pages. : illustrations (chiefly color) ; 25 cm.
Ký hiệu phân loại (DDC): 572.8633
This textbook provides step-by-step protocols and detailed explanations for RNA Sequencing, ChIP-Sequencing and Epigenetic Sequencing applications. The reader learns how to perform Next Generation Sequencing data analysis, how to interpret and visualize the data, and acquires knowledge on the statistical background of the used software tools. Written for biomedical scientists and medical students, this textbook enables the end user to perform and comprehend various Next Generation Sequencing applications and their analytics without prior understanding in bioinformatics or computer sciences
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