Essential computing skills for biologists / Ziling Wang, Lishu Zhang.
Material type:
TextSeries: Series on advances in bioinformatics and computational biology ; v. 11.Publisher: Beijing, China : Higher Education Press Limited Company ; London ; Hackensack, NJ : World Scientific Publishing Europe Ltd., [2018]Description: ix, 293 pages : illustrations ; 24 cmContent type: - text
- unmediated
- volume
- 9781848169241
- QH 324.2 .W184 2018
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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DLSU-D GRADUATE STUDIES Graduate Studies | Graduate Studies | QH 324.2 .W184 2018 (Browse shelf(Opens below)) | 1 | Available | 3CIR2019067958 |
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| QH 324.2 .C420 2018 Systems evolutionary biology : | QH 324.2 .In81 2018 Integration of omics approaches and systems biology for clinical applications / | QH 324.2 .T685 2016 Emerging trends in applications and infrastructures for computational biology, bioinformatics, and systems biology : | QH 324.2 .W184 2018 Essential computing skills for biologists / | QH 366.2 .P935 2017 The Princeton guide to evolution / | QH 430 .At43 1999 The science of genetics. / | QH 430 .G172 1984 Principles of Genetics. / |
Includes bibliographical references and index.
Part I. Databases and bioinformatics tools. Online sequence databases -- Sequence alignment -- Molecular phylogeny and evolution -- Predicting DNA and protein function from sequence -- Protein structure -- Part II. Bioinformatics for omics data. Human genetic variation and human disease -- Gene expression profiling with microarray : online resources and data management -- Bioinformatics for qualitative and quantitative proteomics -- Bioinformatics for metabolomics -- Gene ontology database and KEGG database -- Part III. Statistics and programming. Basic algorithms for bioinformatics -- An introduction to R.
This is a handbook of methods and protocols for biologists. It aimed at undergraduate, graduate students and researchers originally trained in biological or medical sciences who need to know how to access the data archives of genomes, proteins, metabolites, gene expression profiles and the questions these data and tools can answer. For each chapter, the conceptual and experimental background is provided, together with specific guidelines for handling raw data, including preprocessing and analysis.
The content is structured into three parts. Part one introduces basic knowledge about popular bioinformatics tools, databases and web resources. Part two presents examples of omics bioinformatics applications. Part three provides basic statistical analysis skills and programming skills needed to handle and analyze omics datasets.-- Provided by the Publisher
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