Abstract
Biological researchers have proposed the existence of protein domains specific to individual taxonomic kingdoms of organism that do not participate directly in catalytic activity and yet are essential to genetic complementation of loss-of-function mutations [1]. Under the scope of this project, we design and implement a computational algorithm for unsupervised identification of new kingdom-specific sequence motifs to distinguish protein domains warranting empirical investigation. We execute this algorithm on sequences for a protein with empirically documented kingdom-specific domain, and validate the results with respect to biological realism by mapping to a 3-D protein structure and comparing against existing protein annotations.
Original language | English |
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Title of host publication | Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 |
Editors | Harald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang |
Pages | 2221-2228 |
Number of pages | 8 |
ISBN (Electronic) | 9781538654880 |
DOIs | |
State | Published - Jan 21 2019 |
Event | 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain Duration: Dec 3 2018 → Dec 6 2018 |
Publication series
Name | Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 |
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Conference
Conference | 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 |
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Country/Territory | Spain |
City | Madrid |
Period | 12/3/18 → 12/6/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- classification
- feature identification
- information theory
- protein alignment
- sequence alignment
ASJC Scopus subject areas
- Biomedical Engineering
- Health Informatics