Bioinformatics – Wikipedia, the free encyclopedia

Bioinformatics i// is an interdisciplinary scientific field that develops methods for storing, retrieving, organizing and analyzing biological data. A major activity in bioinformatics is to develop software tools to generate useful biological knowledge. Bioinformatics is a distinct science from biological computation, the latter being a computer science and computer engineering subfield using bioengineering and biology to build biological computers, whereas bioinformatics simply uses computers to better understand biology. Bioinformatics is similar to computational biology and has similar aims to it but differs on scale: whereas bioinformatics works with basic biological data (e.g. DNA bases), i.e. it works on the small scale paying attention to details, computational biology is a subfield of computer science which builds large-scale general theoretical models of biological systems seeking to expand our understanding of them from an abstract point of view, just as mathematical biology does with mathematical models.

Bioinformatics uses many areas of computer science, statistics, mathematics and engineering to process biological data. Complex machines are used to read in biological data at a much faster rate than before. Databases and information systems are used to store and organize biological data. Analyzing biological data may involve algorithms in artificial intelligence, soft computing, data mining, image processing, and simulation. The algorithms in turn depend on theoretical foundations such as discrete mathematics, control theory, system theory, information theory, and statistics. Commonly used software tools and technologies in the field include Java, C#, XML, Perl, C, C++, Python, R, SQL, CUDA, MATLAB, and spreadsheet applications.[1][2][3]

Paulien Hogeweg coined the term "Bioinformatics" in 1970 to refer to the study of information processes in biotic systems.[4][5][6] This definition placed bioinformatics as a field parallel to biophysics (the study of physical processes in biological systems) or biochemistry (the study of chemical processes in biological systems).[4]

Sequences. Computers became essential in molecular biology when protein sequences became available after Frederick Sanger determined the sequence of insulin in the early 1950s. Comparing multiple sequences manually turned out to be impractical. A pioneer in the field was Margaret Oakley Dayhoff, who has been hailed by David Lipman, director of the National Center for Biotechnology Information, as the "mother and father of bioinformatics."[7] Dayhoff compiled one of the first protein sequence databases, initially published as books[8] and pioneered methods of sequence alignment and molecular evolution.[9] Another early contributor to bioinformatics was Elvin A. Kabat, who pioneered biological sequence analysis in 1970 with his comprehensive volumes of antibody sequences released with Tai Te Wu between 1980 and 1991.[10]

Genomes. As whole genome sequences became available, again with the pioneering work of Frederick Sanger,[11] the term bioinformatics was re-discovered to refer to the creation of databases such as GenBank in 1982. With the public availability of data tools for their analysis were quickly developed and described in journals such as Nucleic Acids Research which published specialized issues on bioinformatics tools as early as 1982.

In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data. This includes nucleotide and amino acid sequences, protein domains, and protein structures.[12] The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:

The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques to achieve this goal. Examples include: pattern recognition, data mining, machine learning algorithms, and visualization. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and proteinprotein interactions, genome-wide association studies, and the modeling of evolution.

Bioinformatics now entails the creation and advancement of databases, algorithms, computational and statistical techniques, and theory to solve formal and practical problems arising from the management and analysis of biological data.

Over the past few decades rapid developments in genomic and other molecular research technologies and developments in information technologies have combined to produce a tremendous amount of information related to molecular biology. Bioinformatics is the name given to these mathematical and computing approaches used to glean understanding of biological processes.

Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning different DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures.

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Bioinformatics - Wikipedia, the free encyclopedia