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.
| Original language | English |
|---|---|
| Title of host publication | 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 |
| Pages | 398-401 |
| Number of pages | 4 |
| DOIs | |
| State | Published - 2010 |
| Event | 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 - Niagara Falls, NY, United States Duration: Aug 2 2010 → Aug 4 2010 |
Other
| Other | 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 |
|---|---|
| Country | United States |
| City | Niagara Falls, NY |
| Period | 8/2/10 → 8/4/10 |
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All Science Journal Classification (ASJC) codes
- Biomedical Engineering
- Health Information Management
Cite this
An intelligent data-centric approach toward identification of conserved motifs in protein sequences. / Dempsey, Kathryn; Currall, Benjamin; Hallworth, Richard J.; Ali, Hesham.
2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010. 2010. p. 398-401.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An intelligent data-centric approach toward identification of conserved motifs in protein sequences
AU - Dempsey, Kathryn
AU - Currall, Benjamin
AU - Hallworth, Richard J.
AU - Ali, Hesham
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77958030578&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77958030578&partnerID=8YFLogxK
U2 - 10.1145/1854776.1854839
DO - 10.1145/1854776.1854839
M3 - Conference contribution
SN - 9781450304382
SP - 398
EP - 401
BT - 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
ER -