DocumentCode :
3292365
Title :
Evolving Models of Biological Sequence Similarity
Author :
Miranker, Daniel P.
Author_Institution :
Univ. of Texas at Austin, Austin
fYear :
2008
fDate :
11-12 April 2008
Firstpage :
3
Lastpage :
9
Abstract :
For computer scientists the problem of biological data retrieval has become synonymous with homology-based retrieval of primary gene sequence data and their associated protein products. This perspective is accessible to computer scientists, as primary sequence data is modeled as strings and fundamental algorithmic tools can be applied. However, by sticking with this formative foundation, we computer scientists are failing to recognize new challenges and opportunities arising in this rapidly changing arena. Most notably, sequence data represents a polymer; a complex molecule is itself composed of a linear sequence of smaller molecules (monomers). The monomers interact with each other, both with their local neighbors and at long range, forming secondary and tertiary structure. As more sophisticated similarity models incorporate elements of these three-dimensional chemical environments, they have the potential to supplant the use of primary structure homology as the foremost method of data retrieval.
Keywords :
biology; information retrieval; biological data retrieval; biological sequence similarity; gene sequence; homology-based retrieval; Amino acids; Bioinformatics; Biological system modeling; Biology computing; Cells (biology); Genomics; Information retrieval; Proteins; RNA; Sequences; bioinformatics; metric space; similarity search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Similarity Search and Applications, 2008. SISAP 2008. First International Workshop on
Conference_Location :
Belfast
Print_ISBN :
0-7695-3101-6
Type :
conf
DOI :
10.1109/SISAP.2008.23
Filename :
4492920
Link To Document :
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