期刊
BIOINFORMATICS
卷 33, 期 3, 页码 450-452出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btw635
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资金
- State of South Dakota Research Innovation Center
- Agriculture Experiment Station of South Dakota State University
- National Science Foundation of United States [0604755, 1546869]
- National Natural Science Foundation of China [61402194]
- Direct For Biological Sciences
- Division Of Integrative Organismal Systems [0604755] Funding Source: National Science Foundation
- Division Of Integrative Organismal Systems
- Direct For Biological Sciences [1546869] Funding Source: National Science Foundation
- Office of Integrative Activities
- Office Of The Director [1355423] Funding Source: National Science Foundation
Motivation: Biclustering is widely used to identify co-expressed genes under subsets of all the conditions in a large-scale transcriptomic dataset. The program, QUBIC, is recognized as one of the most efficient and effective biclustering methods for biological data interpretation. However, its availability is limited to a C implementation and to a low-throughput web interface. Results: An R implementation of QUBIC is presented here with two unique features: (i) a 82% average improved efficiency by refactoring and optimizing the source C code of QUBIC; and (ii) a set of comprehensive functions to facilitate biclustering-based biological studies, including the qualitative representation (discretization) of expression data, query-based biclustering, bicluster expanding, biclusters comparison, heatmap visualization of any identified biclusters and co-expression networks elucidation.
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