Data Processing Handbook for Complex Biological Data Sources

Cover
Data Processing Handbook for Complex Biological Data Sources
Copyright
Dedication
List of contributors
Foreword
Foreword
Foreword
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 flight
			1.1.4.2 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 acquisition
	1.3 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
		1.5.1 Application in proteomics
		1.5.2 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
		2.3.4 Case study 4: determination of Tm and other thermodynamic parameters
	2.4 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
	4.3 Databases for storing next generation sequencing raw data
	4.4 Data processing
		4.4.1 Read quality control
		4.4.2 DNA-seq: the next generation sequencing genomics application
			4.4.2.1 Short variant discovery
			4.4.2.2 Structural variant discovery
			4.4.2.3 Genome assembly
		4.4.3 RNA-seq: the next generation sequencing transcriptomics application
			4.4.3.1 Differential gene expression analysis
			4.4.3.2 Transcriptome reconstruction
		4.4.4 Next generation sequencing epigenetic application
	4.5 High-throughput sequencing data analysis in an open source platform—galaxy
	4.6 Conclusion
	Acknowledgment
	Reference
5 Nuclear magnetic resonance
	5.1 Introduction
	5.2 Theoretical and practical aspects
		5.2.1 Fundamental concepts
		5.2.2 Nuclear magnetic resonance relaxation mechanisms
	5.3 Raw data
	5.4 Data processing
		5.4.1 Integrating data approaches including web-based sources
	5.5 Essential analysis and processing software
		5.5.1 Acquisition and initial processing
		5.5.2 Computer-aided resonance assignment: spectra assignment
		5.5.3 Spin works (Manitoba University): spectra processing and analysis
		5.5.4 NMRFAM-SPARKY: assignment of integrated spectra
		5.5.5 Collaborative computing project for nuclear magnetic resonance: spectral processing and analysis
		5.5.6 Nuclear magnetic resonance pipe processing and analysis
	5.6 Structure determination softwares
	5.7 Molecular model visualization softwares
	5.8 Examples
		5.8.1 Isolated proteins
		5.8.2 Protein interactions
		5.8.3 Nucleic acids (DNA and RNA)
		5.8.4 General overview
	5.9 Conclusion
	References
6 Fourier transform infrared spectroscopy: Data interpretation and applications in structure elucidation and analysis of sm...
	6.1 Introduction
	6.2 Interpretation of biorelevant small molecules
	6.3 Ligand-binding interactions
	6.4 Drug–cell interactions
	6.5 Biomolecules metal/metal complexes
		6.5.1 Biomolecules: Fe-oxides
			6.5.1.1 Small organic molecules as stabilizing agents
			6.5.1.2 Nucleic bases—β-FeOOH nanoparticles
			6.5.1.3 5′-Guanosine monophosphate-β-FeOOH
			6.5.1.4 DNA- Fe (II) and Fe (III) nanoparticles
			6.5.1.5 Peptide mediated biomineralization of Iron (III) oxyhydroxide nanoparticles
		6.5.2 Guanosine monophosphate-cadmium sulfide nanostructures
	6.6 Graphene-based nanomaterials
	6.7 Conclusion
	6.8 List of abbreviations
	Acknowledgments
	References
7 Microscopy
	7.1 Introduction
	7.2 Transmission electron microscopy
		7.2.1 Sample preparation
			7.2.1.1 Sample preparation: biological specimen
			7.2.1.2 Sample preparation: nanomaterial samples
		7.2.2 Three-dimensional tomography
	7.3 Scanning electron microscopy
		7.3.1 Sample preparation
			7.3.1.1 Sample preparation: biological specimen
				7.3.1.1.1 Coating the specimen surface
			7.3.1.2 Sample preparation: nanomaterial specimen
		7.3.2 Environmental scanning electron microscope
		7.3.3 Three-dimensional scanning electron microscope
	7.4 Atomic force microscopy
		7.4.1 Sample preparation
			7.4.1.1 Sample preparation for biological
			7.4.1.2 Sample preparation for nanomaterial
	7.5 Confocal microscopy
	7.6 Data analysis: transmission electron microscopy, scanning electron microscope, atomic force microscope, and confocal mi...
	7.7 Conclusions
	Acknowledgment
	References
8 Principles and applications of flow cytometry
	8.1 Introduction
		8.1.1 Light scattering and fluorescence
		8.1.2 Cell labeling and compensation
	8.2 Integrating data approaches and analytical tools
		8.2.1 Phenotyping cell populations
		8.2.2 Cell proliferation
		8.2.3 Cell cycle
		8.2.4 Apoptosis
	8.3 Conclusion
	References
9 Isothermal titration calorimetry
	9.1 Introduction
	9.2 Raw data
	9.3 Data processing
		9.3.1 Web-based sources
	9.4 Examples
		9.4.1 Protein–metal interactions
		9.4.2 Thermodynamic basis of calcium binding to EhCRD from Entamoeba histolytica
		9.4.3 Protein carbohydrate interactions
	9.5 Conclusion
	References
10 Metagenome analysis and interpretation
	10.1 Introduction
	10.2 Metagenomics
		10.2.1 Metagenomic applications
			10.2.1.1 Enzymes and metagenomics
			10.2.1.2 Metagenomics and bioactive molecules
			10.2.1.3 Novel biosynthetic pathways
		10.2.2 Metagenome analysis
			10.2.2.1 In silico analysis of the functional metagenomics datasets
			10.2.2.2 In silico analysis of sequenced metagenome datasets
				10.2.2.2.1 Quality filtration
					10.2.2.2.1.1 FastQC
					10.2.2.2.1.2 Fastqp
					10.2.2.2.1.3 MetaQC chain
			10.2.2.3 In silico analysis of 16S rRNA gene (SSU rRNA gene) datasets
				10.2.2.3.1 QIIME
				10.2.2.3.2 MEGAN
				10.2.2.3.3 MOTHUR
				10.2.2.3.4 JAGUC
				10.2.2.3.5 UniFrac
				10.2.2.3.6 PICRUSt
				10.2.2.3.7 Galaxy (https://huttenhower.sph.harvard.edu/galaxy/)
			10.2.2.4 In silico analysis of whole metagenome datasets
				10.2.2.4.1 MG RAST [12]
				10.2.2.4.2 SEED
				10.2.2.4.3 MetaPath
	10.3 Experimental and data analysis framework of metagenomic projects
		10.3.1 Project I: Human gut microbiome structure
		10.3.2 Project II Microbiome structure comparison of garden soil and hospital soil to define anthropogenic influence on soi...
		10.3.3 Project III Metagenomic analysis of soil microbiome [45]
	10.4 Conclusion
	References
Index
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