Abstract
dc:description.abstractFunctional annotations of novel or unknown proteins is one of the central problems in post-genomics bioinformatics research. With the vast expansion of genomic and proteomic data and technologies over the last decade, development of automated function prediction (AFP) methods for large-scale identification of protein function has be-come imperative in many aspects. In this research, we address two important divergences from the “one protein – one function” concept on which all existing AFP methods are developed:
Degree
thesis:*- Name thesis:degree_name
- Doctor of Philosophy (PhD)
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Year
- 2016
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Khan, Ishita Kamal
- Contributors dc:contributor
-
- DAISUKE KIHARA
- ALEX POTHEN
- JENNIFER NEVILLE
- KIHONG PARK
- ROBERT D. SKEEL
Subjects
dc:subject × 4Identifiers
dc:identifier.*- Repository record dc:identifier
- https://docs.lib.purdue.edu/open_access_dissertations/1220
- OAI identifier oai:identifier
- oai:docs.lib.purdue.edu:open_access_dissertations-2436