Title
An intelligent data-centric approach toward identification of conserved motifs in protein sequences
Document Type
Conference Proceeding
Publication Date
2010
Abstract
The continued integration of the computational and biological sciences has revolutionized genomic and proteomic studies. However, efficient collaboration between these fields requires the creation of shared standards. A common problem arises when biological input does not properly fit the expectations of the algorithm, which can result in misinterpretation of the output. This potential confounding of input/output is a drawback especially when regarding motif finding software. Here we propose a method for improving output by selecting input based upon evolutionary distance, domain architecture, and known function. This method improved detection of both known and unknown motifs in two separate case studies. By standardizing input considerations, both biologists and bioinformaticians can better interpret and design the evolving sophistication of bioinformatic software.
Recommended Citation
Cooper, Kathryn Dempsey; Currall, Benjamin; Hallworth, Richard; and Ali, Hesham, "An intelligent data-centric approach toward identification of conserved motifs in protein sequences" (2010). Interdisciplinary Informatics Faculty Proceedings & Presentations. 14.
https://digitalcommons.unomaha.edu/interdiscipinformaticsfacproc/14
Included in
Bioinformatics Commons, Genetics and Genomics Commons, Numerical Analysis and Scientific Computing Commons
Comments
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
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