Technologies for the measurement of mRNA quantities within cells are key components of a biomedical researcher

Public Health Relevance

The proposed research aims to develop computational methods for the support of a technology that measures the quantities of RNA inside of a cell. With this technology and the developed computational methods, researchers will be able to better diagnose and understand the molecular basis of human disease.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG005232-03
Application #
8293382
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Pazin, Michael J
Project Start
2010-07-01
Project End
2014-04-30
Budget Start
2012-05-01
Budget End
2014-04-30
Support Year
3
Fiscal Year
2012
Total Cost
$271,772
Indirect Cost
$73,772
Name
University of Wisconsin Madison
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Li, Shijun; Guo, Wei; Dewey, Colin N et al. (2013) Rbm20 regulates titin alternative splicing as a splicing repressor. Nucleic Acids Res 41:2659-72
Zhang, Yan; Cooke, Amy; Park, Sookhee et al. (2013) Bicaudal-C spatially controls translation of vertebrate maternal mRNAs. RNA 19:1575-82
LeGault, Laura H; Dewey, Colin N (2013) Inference of alternative splicing from RNA-Seq data with probabilistic splice graphs. Bioinformatics 29:2300-10
Haas, Brian J; Papanicolaou, Alexie; Yassour, Moran et al. (2013) De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 8:1494-512
Chung, Dongjun; Kuan, Pei Fen; Li, Bo et al. (2011) Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-Seq data. PLoS Comput Biol 7:e1002111
Li, Bo; Dewey, Colin N (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323