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A New Approach for Sequence Analysis: Illustrating an Expanded Bioinformatics View through Exploring Properties of the Prestin Protein
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Author(s): Kathryn Dempsey (University of Nebraska at Omaha, USA & University of Nebraska Medical Center, USA), Benjamin Currall (Creighton University, USA), Richard Hallworth (Creighton University, USA)and Hesham Ali (University of Nebraska at Omaha, USA & University of Nebraska Medical Center, USA)
Copyright: 2013
Pages: 21
Source title:
Bioinformatics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-3604-0.ch079
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Abstract
Understanding the structure-function relationship of proteins offers the key to biological processes, and can offer knowledge for better investigation of matters with widespread impact, such as pathological disease and drug intervention. This relationship is dictated at the simplest level by the primary protein sequence. Since useful structures and functions are conserved within biology, a sequence with known structure-function relationship can be compared to related sequences to aid in novel structure-function prediction. Sequence analysis provides a means for suggesting evolutionary relationships, and inferring structural or functional similarity. It is crucial to consider these parameters while comparing sequences as they influence both the algorithms used and the implications of the results. For example, proteins that are closely related on an evolutionary time scale may have very similar structure, but entirely different functions. In contrast, proteins which have undergone convergent evolution may have dissimilar primary structure, but perform similar functions. This chapter details how the aspects of evolution, structure, and function can be taken into account when performing sequence analysis, and proposes an expansion on traditional approaches resulting in direct improvement of said analysis. This model is applied to a case study in the prestin protein and shows that the proposed approach provides a better understanding of input and output and can improve the performance of sequence analysis by means of motif detection software.
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