Dissertation
A Software System for Assisting with Protein Annotation
Washington State University
Doctor of Philosophy (PhD), Washington State University
01/2021
DOI:
https://doi.org/10.7273/000001857
Handle:
https://hdl.handle.net/2376/120090
Abstract
Advances in genome sequencing have accelerated the growth of sequenced genomes but at a cost in the quality of genome annotation. At the same time, computational analysis is widely used for protein annotation, but a dearth of experimental verification has contributed to inaccurate annotation as well as to annotation error propagation. Thus, a tool to help life scientists with accurate protein annotation would be useful. In this work we describe a website we have developed, the Protein Annotation Surveillance Site (PASS), which provides such a tool. This website has three main components: a database of homologous clusters with more than nine million protein sequences deduced from the representative genomes of bacteria, archaea, eukarya, and viruses, together with sequence information; a machine-learning software tool which periodically queries the UniprotKB database to determine whether protein function has been experimentally verified; and a query-able webpage where the FASTA headers of sequences from the cluster best matching an input sequence are returned. The user can choose from these sequences to create a sequence similarity network to assist in annotation or else use their expert knowledge to choose an annotation from the cluster sequences. Illustrations demonstrating use of this website are given, and the Protein Annotation Surveillance Site (PASS) can be accessed at https://pass.eecs.wsu.edu/.
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Details
- Title
- A Software System for Assisting with Protein Annotation
- Creators
- Jin Tao
- Contributors
- Shira Broschat (Advisor)Kelly Brayton (Committee Member)Larry Holder (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Publisher
- Washington State University
- Number of pages
- 268
- Identifiers
- 99900606550201842
- Language
- English
- Resource Type
- Dissertation