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Grant:
A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus
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Project Title
A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus
Principal Investigator
Wang, John Junwen (Principal investigator)
Co-Investigator(s)
Tsao, George Sai Wah (Co-Investigator)
Project Code
10091262
Funding Year
2010/2011
Amount
982485
Panel
Medicine
Start Date
01-01-2011
Expected Completion
31-12-2012
Status
On-going
Keywords
Hidden Markov Model, MicroRNA, Hidden Markov models, Algorithm, Epstein-Barr virus, MicroRNA target
Discipline
Others - Medicine, Dentistry and Health, Epidemiology
Grant Type/Funding Scheme
Research Fund for the Control of Infectious Diseases - Full Grants
Duration
24
Publication
An SNP selection strategy identified IL-22 associating with susceptibility to tuberculosis in Chinese
Publication
Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions
Publication
Correlated evolution of transcription factors and their binding sites
Publication
EpiRegNet: Constructing epigenetic regulatory network from high throughput gene expression data for humans
Publication
A functional single-nucleotide polymorphism in the promoter of the gene encoding interleukin 6 is associated with susceptibility to tuberculosis
Publication
GWASdb: A database for human genetic variants identified by genome-wide association studies
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