paraGSEA: a scalable approach for large-scale gene expression profiling

Author:

Peng Shaoliang12,Yang Shunyun2,Bo Xiaochen3,Li Fei3

Affiliation:

1. College of Computer Science and Electronic Engineering & National Supercomputer Centre in Changsha, Hunan University, Changsha 410082, China

2. School of Computer Science, National University of Defense Technology, Changsha 410073, China

3. Department of biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China

Publisher

Oxford University Press (OUP)

Subject

Genetics

Reference28 articles.

1. Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes;Lucas;Mol. Cancer Therapeut.,2014

2. jSplice: a high-performance method for accurate prediction of alternative splicing events and its application to large-scale renal cancer transcriptome data;Christinat;Bioinformatics,2016

3. Large-scale integration of small molecule-induced genome-wide transcriptional responses, kinome-wide binding affinities and cell-growth inhibition profiles reveal global trends characterizing systems-level drug action;Vidović;Front. Genet.,2014

4. NCBI GEO: archive for functional genomics data sets—update;Barrett;Nucleic Acids Res.,2011

5. ArrayExpress—a public database of microarray experiments and gene expression profiles;Parkinson;Nucleic Acids Res.,2007

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