Data processing handbook for complex biological data sources

"[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

Includes 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

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

1.2.4 Data-dependent acquisition1.3 D…