Bioinformatics and computational biology involve the use of techniques from applied mathematics, informatics, statistics, and computer science to solve biological problems. Research in computational biology often overlaps with systems biology. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution.

The terms bioinformatics and computational biology are often used interchangeably, although the former typically focuses on algorithm development and specific computational methods, while the latter focuses more on hypothesis testing and discovery in the biological domain. Although this distinction is used by National Institutes of Health in their working definitions of Bioinformatics and Computational Biology, it is clear that there is a tight coupling of developments and knowledge between the more hypothesis-driven research in computational biology and technique-driven research in bioinformatics. Computational biology also includes lesser known but equally important subdisciplines such as computational biochemistry and computational biophysics.

A common thread in projects in bioinformatics and computational biology is the use of mathematical tools to extract useful information from noisy data produced by high-throughput biological techniques such as genomics (The field of data mining overlaps with computational biology in this regard). A representative problem in bioinformatics is the assembly of high-quality DNA sequences from fragmentary "shotgun" DNA sequencing, while in computational biology, a representative problem might be statistical testing of a hypothesis of common gene regulation using data from mRNA microarrays or mass spectrometry.

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Predicting giant transmembrane {beta}-barrel architecture
Reboul, C. F., Mahmood, K., Whisstock, J. C., Dunstone, M. A. Wed, 09 May 2012 03:19:33 -0700
Motivation: The β-barrel is a ubiquitous fold that is deployed to accomplish a wide variety of biological functions including membrane-embedded pores. Key influences of β-barrel lumen diameter include the number of β-strands (n) and the degree of shear (S), the latter value measuring the extent to which the β-sheet is tilted within the β-barrel. Notably, it has previously been reported that the shear value for small antiparallel β-barrels (n≤24) typically ranges between n and 2n. Conversely, it has been suggested that the β-strands in giant antiparallel β-barrels, such as those formed by pore forming cholesterol-dependent cytolysins (CDC), are parallel relative to the axis of the β-barrel, i.e. S=0. The S=0 arrangement, however, has never been observed in crystal structures of small β-barrels. Therefore, the structural basis for how CDCs form a β-barrel and span a membrane remains to be understood. Results: Through comparison of molecular models with experimental data, we are able to identify how giant CDC β-barrels utilize a ‘near parallel’ arrangement of β-strands where S=n/2. Furthermore, we show how side-chain packing within the β-barrel lumen is an important limiting factor with respect to the possible shear values for small β-barrels (n≤24  β-strands). In contrast, our models reveal no such limitation restricts the shear value of giant β-barrels (n>24 β-strands). Giant β-barrels can thus access a different architecture compared with smaller β-barrels. Contact: michelle.dunstone@monash.edu Supplementary information: Supplementary data are available at Bioinformatics online.

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