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Bioinformatics S Ranganathan, Macquarie University, Sydney, NSW, Australia Bioinformatics S Ranganathan, Macquarie University, Sydney, NSW, Australia r 2017 Elsevier Inc. All rights reserved. In 1991, Nobel laureate, Walter Gilbert said “The new paradigm, now emerging, is that all the ‘genes’ will be known (in the sense of being resident in databases available electronically), and that the starting point of a biological investigation will be theoretical. An individual scientist will begin with a theoretical conjecture, only then turning to experiment to follow or test that hypothesis.”1 In a nutshell, Gilbert is referring to the use of bioinformatics in all biological research endeavors. Bioinformatics, also known as computational biology, enables the scientific understanding of living systems through com- putation. It links molecular descriptors of organisms to biological processes, facilitating data mining and knowledge discovery. Emerging from an essential enabling technology in the Life Sciences, bioinformatics is now a fundamental research discipline. Bioinformatics is a key platform technology, underpinning biotechnology and genome research. The integration of compu- tational approaches with experimental life science and biomedical research generates theoretical analysis-based hypotheses, which will then steer experimental design. Some of the current challenges addressed by bioinformatics are: • Novel approaches to solving biological problems presented by genomics and proteomics. • Unraveling the genetic and environmental basis of health and disease. • Developing software to facilitate bioinformatics analyses. • Standardization of functional descriptors for different data types. • Improving knowledge management systems for intuitive use by life and biomedical scientists. Building on the applications of informatics (computer science) to biology, bioinformatics has established linkages with mathematics and statistics; physics and chemistry; medicine and pharmacology. Bioinformatics research thus entails inputs from diverse disciplines. The ultimate goal of bioinformatics is to provide a complete representation of living cells and organisms and understand the principles of how they function, so that, in the words of Nobel laureate Sydney Brenner, “computational biology becomes biological computation.” Systematic Organization of Sequences As molecular biologists uncover innumerable gene (DNA), transcript (RNA) and protein sequences, biological databases are essential for efficient data management and to facilitate sequence analysis. Structural bioinformatics on the other hand involves the analysis of three-dimensional structures of biological molecules. Needless to say, a working knowledge of biostatistics is crucial in this computational analysis. From Sequences to Organisms An important application of bioinformatics to molecular data is in phylogenetic analysis, for linking the genotype to the observed phenotype. Most analysis methods developed for sequences can be applied to organisms, leading to biodiversity informatics. An Integrated Approach to Biological Data Rather than looking at individual sequences, groups of genes or proteins, involved in a specific biological function is referred to as the study of biological pathways, analogous to biochemical and signaling pathways. Here, the terminology used to describe biological function has to be robust and has led to the development of gene ontology. With the immense accumulation of biological and biomedical literature, it is impractical today to collate information on specific biomolecules and their function, resulting in text mining. The study of interacting biological entities comprising a system constitutes biological networks. Ranging from gene and protein interaction networks, network biology extends to evolutionary and ecological networks. Bioinformatics applied to the immune system is labeled immunoinformatics. Sequence Data at the Organism Level With high-throughput technologies, the entire molecular data of an organism can be captured as its genome, transcriptome or proteome. Strategies involved in analyzing the raw data from instruments as well as the analysis of whole and proteome sequences Reference Module in Life Sciences doi:10.1016/B978-0-12-809633-8.12387-8 1 2 Bioinformatics has led to genome and proteome informatics. How genes, transcripts and proteins interact and communicate to carry out essential biological functions is studied as functional genomics. Bioinformatics in Health and Disease Genetic variations and gene–environment interactions in health and disease are important from a public health perspective as well as the health of farmed species. With the knowledge of the genomes of several infectious agents, disease informatics provides us biomarkers for diagnosis and monitoring disease progression. The molecular changes occurring in diseases such as cancer, autoimmune and neurological disorders are studied in translational bioinformatics, for facilitating personalized healthcare. Drug design is an area of bioinformatics that focuses on drug molecules and inhibitors that can ameliorate diseases and disorders in a targeted manner. The Bioinformatics section of the Reference Module on Life Sciences provides a great opportunity to keep readers updated with clear and authoritative descriptions of bioinformatics terms and areas. This section will be of interest of both life science researchers as well as students to learn about the most important and current features of bioinformatics. Reference 1. Gilbert, W., 1991. Towards a paradigm shift in biology. Nature 349, 99. Available at: http://www.nature.com/nature/journal/v349/n6305/pdf/349099a0.pdf.
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