A data centric approach for constructing multiple sequence alignments
Grant Data
Project Title
A data centric approach for constructing multiple sequence alignments
Principal Investigator
Dr Ting, Hing Fung
(Principal Investigator (PI))
Duration
42
Start Date
2020-01-01
Completion Date
2023-06-30
Amount
518999
Conference Title
A data centric approach for constructing multiple sequence alignments
Keywords
convolutional neural networks, deep learning, multiple sequence alignment, protein families
Discipline
Computer Science FundamentalsBioinformatics
Panel
Engineering (E)
HKU Project Code
17208019
Grant Type
General Research Fund (GRF)
Funding Year
2019
Status
Completed
Objectives
1) Apply various machine learning methods to improve the performance of the MSA tool PnpProbs; 2) Apply various machine learning methods to improve the performance of other leading MSA tools, and then develop intelligent system for giving sound suggestion on the best MSA tool for an input; 3) Design and develop a truly data-driven MSA construction tool; 4) Integrate the results of this project and develop an online Web-based system that supports effective and user-friendly methods for constructing MSAs and analyzing them.