A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus
Grant Data
Project Title
A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus
Principal Investigator
Professor Wang, Junwen John
(Principal Investigator (PI))
Co-Investigator(s)
Professor Tsao George Sai Wah
(Co-Investigator)
Duration
24
Start Date
2011-01-01
Amount
982485
Conference Title
A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus
Presentation Title
Keywords
Algorithm, Epstein-Barr virus, Hidden Markov Model, Hidden Markov models, MicroRNA, MicroRNA target
Discipline
Others - Medicine, Dentistry and Health,Epidemiology
HKU Project Code
10091262
Grant Type
Research Fund for the Control of Infectious Diseases - Full Grants
Funding Year
2010
Status
Completed
All Publications
| Title | Author(s) | Issue Date | |
|---|---|---|---|
An SNP selection strategy identified IL-22 associating with susceptibility to tuberculosis in Chinese Journal:Scientific Reports | 2011 | ||
| 2011 | |||
GWASdb: A database for human genetic variants identified by genome-wide association studies Journal:Nucleic Acids Research | 2012 | ||
A functional single-nucleotide polymorphism in the promoter of the gene encoding interleukin 6 is associated with susceptibility to tuberculosis Journal:Journal of Infectious Diseases | 2012 | ||
| 2011 | |||
Correlated evolution of transcription factors and their binding sites Journal:Bioinformatics | 2011 |