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Data processing handbook for complex...

Misra, Gauri,

Data processing handbook for complex biological data sources

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data processing handbook for complex biological data sourcesedited by Gauri Misra.
其他作者:	Misra, Gauri,
出版者:	London :Academic Press,2019.
面頁冊數:	1 online resource.
附註:	Includes index.
標題:	BioinformaticsData processing.
電子資源:	https://www.sciencedirect.com/science/book/9780128165485
ISBN:	9780128172803 (electronic bk.)

Data processing handbook for complex biological data sources
Data processing handbook for complex biological data sources[electronic resource] /edited by Gauri Misra. - London :Academic Press,2019. - 1 online resource.

Includes index.

Includes bibliographical references and index.

Front Cover; Data Processing Handbook for Complex Biological Data Sources; Copyright Page; Dedication; Contents; List of contributors; Foreword by Jeremy C. Smith; Foreword by M.R.N. Murthy; Foreword by Aatto Laaksonen; Preface; Acknowledgments; 1 Mass spectroscopy; 1.1 Introduction; 1.1.1 Principle; 1.1.2 Instrumentation; 1.1.3 Types of ionization techniques; 1.1.3.1 Electron ionization; 1.1.3.2 Chemical ionization; 1.1.3.3 Fast atom bombardment; 1.1.3.4 Matrix assisted laser desorption ionization; 1.1.3.5 Electrospray ionization; 1.1.3.6 Fragmentation; 1.1.4 Analyzers

"[This book] provides relevant and to the point content for those who need to understand the different types of biological data and the techniques to process and interpret them. The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers. In order to succeed in data processing for biological data sources, it is necessary to master the type of data and general methods and tools for modern data processing. For instance, many labs follow the path of interdisciplinary studies and get their data validated by several methods. Researchers at those labs may not perform all the techniques themselves, but either in collaboration or through outsourcing, they make use of a range of them, because, in the absence of cross validation using different techniques, the chances for acceptance of an article for publication in high profile journals is weakened."--Website ebook

ISBN: 9780128172803 (electronic bk.)Subjects--Topical Terms:

487349
Bioinformatics
--Data processing.Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QH324.2

Dewey Class. No.: 570.285

Data processing handbook for complex biological data sources
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245 0 0 $a Data processing handbook for complex biological data sources $h [electronic resource] / $c edited by Gauri Misra.
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504 $a Includes bibliographical references and index.
505 0 $a Front Cover; Data Processing Handbook for Complex Biological Data Sources; Copyright Page; Dedication; Contents; List of contributors; Foreword by Jeremy C. Smith; Foreword by M.R.N. Murthy; Foreword by Aatto Laaksonen; Preface; Acknowledgments; 1 Mass spectroscopy; 1.1 Introduction; 1.1.1 Principle; 1.1.2 Instrumentation; 1.1.3 Types of ionization techniques; 1.1.3.1 Electron ionization; 1.1.3.2 Chemical ionization; 1.1.3.3 Fast atom bombardment; 1.1.3.4 Matrix assisted laser desorption ionization; 1.1.3.5 Electrospray ionization; 1.1.3.6 Fragmentation; 1.1.4 Analyzers
505 8 $a 1.1.4.1 Time of flight1.1.4.2 Quadrupole; 1.1.4.3 Ion trap analyzer; 1.1.4.4 Fourier transform-ion cyclotron resistance; 1.1.4.5 Orbitrap analyzer; 1.1.4.6 Tandem mass spectrometer; 1.1.5 Detectors; 1.1.5.1 Faraday cup; 1.1.5.2 Electron multipliers; 1.1.5.3 Photomultipliers; 1.1.5.4 Microchannel plate; 1.1.6 Mass interpretation; 1.1.6.1 Types of peaks; 1.1.6.2 Fragmentation rules; 1.1.6.3 Peptide mass fingerprinting; 1.1.6.4 Peptide fragmentation fingerprinting; 1.1.6.5 De novo peptide sequencing; 1.2 Raw data; 1.2.1 NanoLC principle; 1.2.2 Gradient; 1.2.3 Orbitrap technology
505 8 $a 1.2.4 Data-dependent acquisition1.3 Data processing; 1.3.1 Trans-proteomic pipeline; 1.3.2 Installation; 1.3.3 Raw file conversion; 1.3.4 Search engine support; 1.3.5 PeptideProphet for corroboration; 1.3.6 Pep3D to view chromatogram; 1.3.7 iProphet for peptide-level corroboration; 1.3.8 XPRESS/ASAP ratio for peptide quantitation; 1.3.9 Protein prophet for protein interpretation and corroboration; 1.4 Protein quantification and identification; 1.4.1 Label-free quantification; 1.4.2 Functional annotation and enrichment analysis; 1.5 Applications of mass spectrometry
505 8 $a 1.5.1 Application in proteomics1.5.2 Application in metabolomics; 1.5.3 Application in environment analysis; 1.5.4 Application in pharmacy; 1.5.5 Application in forensic science; 1.5.6 Applications in medical research; 1.6 Conclusion; References; Further Reading; 2 Circular dichroism; 2.1 Introduction; 2.2 Principle; 2.3 Raw data analyses; 2.3.1 Case study 1: to study acid-induced transitions in a protein; 2.3.2 Case study 2: to study pH-induced transitions in a protein; 2.3.3 Case study 3: to study structural transitions in nucleic acids
505 8 $a 2.3.4 Case study 4: determination of Tm and other thermodynamic parameters2.4 Miscellaneous examples; 2.5 Conclusion; Acknowledgments; References; 3 Fluorescence spectroscopy; 3.1 Introduction; 3.2 Principle; 3.2.1 Instrumentation; 3.3 Intrinsic fluorescence; 3.3.1 Protein stability studies; 3.3.2 Protein interaction studies; 3.4 Extrinsic fluorescence; 3.5 Fluorescence polarization; 3.6 Fluorescence resonance energy transfer; 3.7 Conclusion; Acknowledgment; References; 4 High-throughput sequencing; 4.1 Introduction; 4.2 High-throughput sequencing raw data
520 $a "[This book] provides relevant and to the point content for those who need to understand the different types of biological data and the techniques to process and interpret them. The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers. In order to succeed in data processing for biological data sources, it is necessary to master the type of data and general methods and tools for modern data processing. For instance, many labs follow the path of interdisciplinary studies and get their data validated by several methods. Researchers at those labs may not perform all the techniques themselves, but either in collaboration or through outsourcing, they make use of a range of them, because, in the absence of cross validation using different techniques, the chances for acceptance of an article for publication in high profile journals is weakened."--Website ebook
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