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Functional Genomics, Proteomics, Metabolomics and Bioinformatics for Systems Biology

  • Chapter
Systems Biology

Abstract

This chapter introduces Systems Biology, its context, aims, concepts and strategies, then describes approaches used in genomics, epigenomics, transcriptomics, proteomics, metabolomics and lipidomics, and how recent technological advances in these fields have moved the bottleneck from data production to data analysis. Methods for clustering, feature selection, prediction analysis, text mining and pathway analysis used to analyse and integrate the data produced are then presented.

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Abbreviations

BASE:

BioArray Software Environment

BS:

BiSulphite

CATCH-IT:

Covalent Attachment of Tags to Capture Histones and Identify Turnover

CFS:

Correlation-based Feature Selection

CHARM:

Comprehensive High-throughput Array for Relative Methylation

ChIA-PET:

Chromatin Interaction Analysis by Paired-End Tag

ChIP:

Chromatin ImmunoPrecipitation

CLIP:

Crosslinking immunoprecipitation

DHS:

DNAse I hypersensitivity

DNA:

DeoxyriboNucleic Acid

EFS:

Ensemble Feature Selection

ELISA:

Enzyme-Linked ImmunoSorbent Assays

ENCODE:

ENCyclopedia Of DNA Elements

ESI:

ElectroSpray Ionisation

EWAS:

Epigenome-Wide Association Studies

FAB:

Fast Atom Bombardment

FAIRE:

Formaldehyde-assisted isolation of regulatory elements

FDR:

False Discovery Rate

FT-ICR:

Fourier Transform Ion Cyclotron Resonance

FUGE:

Functional Genomics Experiment data model

GAGE:

Generally Applicable Gene-set Enrichment

GC:

Gas Chromatography

GEO:

Gene Expression Omnibus

GO:

Gene Ontology

GSEA:

Gene Set Enrichment Analysis

GWAS:

Genome-Wide Association Studies

HITS-CLIP:

HIgh-Throughput Sequencing of RNAs isolated by CrossLinking ImmunoPrecipitation

HMM:

Hidden Markov Models

HPLC:

High Performance Liquid Chromatography

IMS:

Imaging Mass Spectrometry

IP:

ImmunoPrecipitation

iTRAQ:

Isobaric Tags for Relative and Absolute Quantitation

KEGG:

Kyoto Encyclopedia of Genes and Genomes

kNN:

k-Nearest Neighbor

LC:

Liquid Chromatography

MALDI:

Matrix Assisted Laser Desorption Ionisation

MBD:

Methyl-CpG Binding Domain

MCAM:

Multiple Clustering Analysis Methodology

MeDIP:

Methylated DNA Immunoprecipitation

MGDE:

Microarray Gene Expression Data

MIAME:

Minimum Information About a Microarray Experiment

MIAPE:

Minimum Information About a Proteomics Experiment

MINSEQE:

Minimum INformation about a high-throughput SeQuencing Experiment

MMASS:

Microarray-based Methylation Assessment of Single Samples

MN:

Microccocal Nuclease

MRM:

Multiple Reaction Monitoring

mRNA:

Messenger RiboNucleic Acid

MS:

Mass Spectrometry

NCBI:

National Center for Biotechnology Information

NER:

Named-Entity Recognition

NGS:

Next Generation Sequencing

NIH:

National Institutes of Health

NMR:

Nuclear Magnetic Resonance

PaGE:

Patterns from Gene Expression

PCR:

Polymerase Chain Reaction

PRIDE:

PRoteomics IDEntifications

PSM:

Peptide-Spectrum Match

QMS:

Quadrupole Mass Analyser

RNA:

RiboNucleic Acid

RRBS:

Reduced Representation Bisulphite Sequencing

RT-qPCR:

Reverse Transcription quantitative PCR

SAGE:

Serial Analysis of Gene Expression

SELDI:

Surface Enhanced Laser Desorption Ionization

SILAC:

Stable Isotope Labeling by Amino acids in Cell culture

SNP:

Single Nucleotide Polymorphism

SRM:

Selected Reaction Monitoring

SUMCOV:

SUM of COVariances

SVM:

Support Vector Machine

ToF:

Time-of-Flight

UCSC:

University of California, Santa Cruz

VOCs:

Volatile Organic Compounds

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Acknowledgments

This work was supported by the CNRS, the University of Luxembourg and the ISB, and in part by the EU grants to CA in the context of the MeDALL consortium (Mechanisms of the Development of Allergy, Grant Agreement FP7 N°264357) and the U-BIOPRED consortium (Unbiased Biomarkers for the PREDiction of respiratory disease outcomes, Grant Agreement IMI 115010).

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  1. European Institute for Systems Biology & Medicine, CNRS-UCBL—Université de Lyon, 50 Avenue Tony Garnier, 69007, Lyon, France

    Stéphane Ballereau, Amphun Chaiboonchoe, Hassan Ahmed, Johann Pellet & Charles Auffray

  2. Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7 Avenue des Hauts-Fourneaux, 4362, Esch-sur-Alzette, Luxembourg

    Enrico Glaab, Alexei Kolodkin, Maria Biryukov, Nikos Vlassis, Reinhard Schneider & Rudi Balling

  3. Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109–5234, USA

    Nitin Baliga & Leroy Hood

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Ballereau, S. et al. (2013). Functional Genomics, Proteomics, Metabolomics and Bioinformatics for Systems Biology. In: Prokop, A., Csukás, B. (eds) Systems Biology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6803-1_1

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