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Essentials of bioinformatics.Volume ...
~
Shaik, Noor Ahmad.
Essentials of bioinformatics.Volume I,Understanding bioinformatics: genes to proteins
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Essentials of bioinformatics.edited by Noor Ahmad Shaik ... [et al.].
其他題名:
Understanding bioinformatics: genes to proteins
其他作者:
Shaik, Noor Ahmad.
出版者:
Cham :Springer International Publishing :2019.
面頁冊數:
xiv, 405 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Bioinformatics.
電子資源:
https://doi.org/10.1007/978-3-030-02634-9
ISBN:
9783030026349$q(electronic bk.)
Essentials of bioinformatics.Volume I,Understanding bioinformatics: genes to proteins
Essentials of bioinformatics.
Volume I,Understanding bioinformatics: genes to proteins[electronic resource] /Understanding bioinformatics: genes to proteinsedited by Noor Ahmad Shaik ... [et al.]. - Cham :Springer International Publishing :2019. - xiv, 405 p. :ill., digital ;24 cm.
Introduction to biological data -- Computers and bioinformatics -- Sequence biological databases -- Biological databases -- Other biological databases -- Nucleic acid sequencing -- Tools and methods in analysis of simple sequences -- Tools and methods in analysis of complex sequences -- Structural bioinformatics -- Protein structure annotations -- Introduction to functional bioinformatics -- Biological networks - tools, methods and analysis -- Metabolomics -- Drug discovery: concepts and approaches -- Drug designing methods and analysis -- Molecular molecular docking -- Insilico pcr -- Modeling and optimization of molecular bio-systems to generate predictive models -- Index.
Bioinformatics is an integrative field of computer science, genetics, genomics, proteomics, and statistics, which has undoubtedly revolutionized the study of biology and medicine in past decades. It mainly assists in modeling, predicting and interpreting large multidimensional biological data by utilizing advanced computational methods. Despite its enormous potential, bioinformatics is not widely integrated into the academic curriculum as most life science students and researchers are still not equipped with the necessary knowledge to take advantage of this powerful tool. Hence, the primary purpose of our book is to supplement this unmet need by providing an easily accessible platform for students and researchers starting their career in life sciences. This book aims to avoid sophisticated computational algorithms and programming. Instead, it mostly focuses on simple DIY analysis and interpretation of biological data with personal computers. Our belief is that once the beginners acquire these basic skillsets, they will be able to handle most of the bioinformatics tools for their research work and to better understand their experimental outcomes. Unlike other bioinformatics books which are mostly theoretical, this book provides practical examples for the readers on state-of-the-art open source tools to solve biological problems. Flow charts of experiments, graphical illustrations, and mock data are included for quick reference. Volume I is therefore an ideal companion for students and early stage professionals wishing to master this blooming field.
ISBN: 9783030026349$q(electronic bk.)
Standard No.: 10.1007/978-3-030-02634-9doiSubjects--Topical Terms:
194415
Bioinformatics.
LC Class. No.: QH324.2 / .E874 2019
Dewey Class. No.: 570.285
Essentials of bioinformatics.Volume I,Understanding bioinformatics: genes to proteins
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Introduction to biological data -- Computers and bioinformatics -- Sequence biological databases -- Biological databases -- Other biological databases -- Nucleic acid sequencing -- Tools and methods in analysis of simple sequences -- Tools and methods in analysis of complex sequences -- Structural bioinformatics -- Protein structure annotations -- Introduction to functional bioinformatics -- Biological networks - tools, methods and analysis -- Metabolomics -- Drug discovery: concepts and approaches -- Drug designing methods and analysis -- Molecular molecular docking -- Insilico pcr -- Modeling and optimization of molecular bio-systems to generate predictive models -- Index.
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