Abstract
dc:description.abstractgeneralIn my research, I developed protein model quality estimation methods aimed at evaluating the reliability of computationally predicted protein models in the absence of experimentally solved ground truth structures. These methods specifically focus on estimating errors within the protein models to quantify their structural accuracy. Recognizing that even the most advanced protein structure prediction techniques may produce models with errors, I also developed a complementary protein model refinement method. This refinement method iteratively optimizes the weakly modeled regions, guided by the error estimation module of my quality estimation approach. The development of these model quality estimation methods, therefore, not only offers valuable insights into the structural reliability of protein models but also contributes to optimizing the overall reliability of protein models generated by state-of-the-art computational methods.
Degree
thesis:*- Name thesis:degree_name
- Doctor of Philosophy
- Level thesis:degree_level
- doctoral
- Discipline thesis:degree_discipline
- Computer Science and Applications
- Department dc:contributor.department
- Computer Science and Applications
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2023
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Shuvo, Md Hossain
- Chair dc:contributor.committeechair
-
- Bhattacharya, Debswapna
- Committee members dc:contributor.committeemember
-
- Zhang, Liqing
- Heath, Lenwood S.
- Onufriev, Alexey
- Emrich, Scott
Subjects
dc:subject × 4Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Dc Identifier Other
- vt_gsexam:39314
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/117278