Abstract
Bioinformatics has emerged as new discipline at the interface of molecular bioscience with mathematics, computer science and information technology. Bioinformatics is driven by data arising from high-throughput technologies in molecular bioscience. To enable biological discovery, bioinformatics draws on and extends technologies for data capture, management, integration and mining, computing, and communication technology. The rise of genomics has been a key driver for bioinformatics. Genomics, however, was never an end unto itself, but rather was intended to enable the understanding of complex biological systems. Bioinformatics continues to evolve in support of its constituent domains and, increasingly, their integration into genome-scale molecular systems biology. This article presents bioinformatics first from the perspective of computer science and information technology, then from the perspective of bioscience. In practice these perspectives often merge, making bioinformatics a rich, vibrant area of multidisciplinary research and application.
TopOne way of exploring the interface between molecular bioscience and IT is to track experimental data from their generation, capture and retrieval, through their aggregation and dissemination via international data services, to their subsequent analysis. Here I deconstruct data analysis into data models, algorithms, analytical methods and software, workflows and visualisation. This trajectory is common to scientific data, although bioinformatics is notable for its culture of open data, well-established data formats and standards, and data reuse facilitated by large international repositories with associated data services.
Key Terms in this Chapter
Epigenetics: The study of heritable changes in gene expression or phenotype that do not arise from changes in the nucleotide sequence of the genome.
Genomics: The study of the totality of genetic information in a cell or organism.
Systems Biology: The study of networks of interactions among the components of a biological system, emphasising a synthetic, non-reductionist approach and emergent properties.
Metagenomics: The study of the genetic information in a sample of a mixed community, for example from soil, water, or the intestinal tract of an animal, without prior separation of the constituent organisms.
Omics (or ‘Omics): Genomics, transcriptomics, and other fields of biology characterised by the study of the totality of a class of molecule ( e.g. proteomics), process ( e.g. metabolomics) or traits ( e.g. phenomics) in a cell or organism.
Synthetic Biology: The engineering design and construction of new or modified functions in biological systems.
Phylogenetics: The study of genetic relationships among molecules, organisms or taxa over time.
Gene Expression: The process in which information in a gene is transduced to yield one or more gene products (proteins and/or non-protein-coding RNAs).
Transcriptomics: The study of the totality of the RNA molecules arising from the expression of genes under specified conditions.