Gracob: a novel graph-based constant-column biclustering method for mining growth phenotype data

Majed A. Alzahrani; Hiroyuki Kuwahara; Wei Wang; Xin Gao

doi:10.1093/bioinformatics/btx199

Gracob: a novel graph-based constant-column biclustering method for mining growth phenotype data

Majed A. Alzahrani, Hiroyuki Kuwahara, Wei Wang, Xin Gao

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Growth phenotype profiling of genome-wide genedeletion strains over stress conditions can offer a clear picture that the essentiality of genes depends on environmental conditions. Systematically identifying groups of genes from such high-throughput data that share similar patterns of conditional essentiality and dispensability under various environmental conditions can elucidate how genetic interactions of the growth phenotype are regulated in response to the environment.We first demonstrate that detecting such\co-fit

Original language	English (US)
Pages (from-to)	2523-2531
Number of pages	9
Journal	Bioinformatics
Volume	33
Issue number	16
DOIs	https://doi.org/10.1093/bioinformatics/btx199
State	Published - Apr 4 2017
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): URF/1/1976-04, NIH U01HG008488, NIH R01GM115833, NIH U54GM114833, NSF DBI-1565137, NSF IIS-1313606
Acknowledgements: The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/1976-04. NIH U01HG008488, NIH R01GM115833, NIH U54GM114833, NSF DBI-1565137, and NSF IIS-1313606.

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10.1093/bioinformatics/btx199

https://repository.kaust.edu.sa/bitstream/10754/623634/1/btx199.pdf

Cite this

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title = "Gracob: a novel graph-based constant-column biclustering method for mining growth phenotype data",

abstract = "Growth phenotype profiling of genome-wide genedeletion strains over stress conditions can offer a clear picture that the essentiality of genes depends on environmental conditions. Systematically identifying groups of genes from such high-throughput data that share similar patterns of conditional essentiality and dispensability under various environmental conditions can elucidate how genetic interactions of the growth phenotype are regulated in response to the environment.We first demonstrate that detecting such\co-fit",

author = "Alzahrani, {Majed A.} and Hiroyuki Kuwahara and Wei Wang and Xin Gao",

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doi = "10.1093/bioinformatics/btx199",

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AU - Kuwahara, Hiroyuki

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AU - Gao, Xin

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Gracob: a novel graph-based constant-column biclustering method for mining growth phenotype data

Abstract

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