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.
Author supplied keywords
- Bioinformatics
- Bottom-up
- Clustering
- Curse of dimensionality
- Data integration
- Emergence
- Epigenomics
- Feature selection
- Functional genomics
- High-dimensionality
- High-throughput
- Holistic
- Interactions
- Knowledge management
- Mass spectrometry
- Mathematical model
- Metabolomics
- Middle-out
- Network
- Next generation sequencing
- Ontology
- Pathway
- Prediction analysis
- Proteomics
- Text-mining
- Top-down
- Transcriptomics
Cite
CITATION STYLE
Ballereau, S., Glaab, E., Kolodkin, A., Chaiboonchoe, A., Biryukov, M., Vlassis, N., … Auffray, C. (2013). Functional genomics, proteomics, metabolomics and bioinformatics for systems biology. In Systems Biology: Integrative Biology and Simulation Tools (pp. 3–41). Springer Netherlands. https://doi.org/10.1007/978-94-007-6803-1_1
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