Regular Expression Based Pattern Matching for Gene Expression Data to Identify the Abnormality Gnome

2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM) ◽

10.1109/icrtccm.2017.71 ◽

2017 ◽

Author(s):

L. Sharmila ◽

U. Sakthi ◽

A. Geethanjali ◽

Suresh Sagadevan

Keyword(s):

Gene Expression ◽

Pattern Matching ◽

Gene Expression Data ◽

Regular Expression ◽

Expression Data

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A pattern matching approach for clustering gene expression data

International Journal of Data Mining Modelling and Management ◽

10.1504/ijdmmm.2011.041492 ◽

2011 ◽

Vol 3 (2) ◽

pp. 130 ◽

Author(s):

Rosy Das ◽

Jugal Kalita ◽

Dhruba K. Bhattacharyya

Keyword(s):

Gene Expression ◽

Pattern Matching ◽

Gene Expression Data ◽

Expression Data

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A Hierarchical Approach for Clustering and Pattern Matching of Gene Expression Data

2012 Sixth International Conference on Genetic and Evolutionary Computing ◽

10.1109/icgec.2012.16 ◽

2012 ◽

Author(s):

Soriful Hoque ◽

Salim Istyaq ◽

Md. Mushir Riaz

Keyword(s):

Gene Expression ◽

Pattern Matching ◽

Gene Expression Data ◽

Expression Data ◽

Hierarchical Approach

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Regular expression based pattern extraction from a cell - Specific gene expression data

Informatics in Medicine Unlocked ◽

10.1016/j.imu.2019.100269 ◽

2019 ◽

Vol 17 ◽

pp. 100269

Author(s):

Suja Subramanian ◽

Tessamma Thomas

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Regular Expression ◽

Specific Gene ◽

Expression Data ◽

Pattern Extraction ◽

Specific Gene Expression ◽

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Cancer Classification from Gene Expression data using Fuzzy-Rough techniques An Empirical Study

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i6.415420 ◽

2018 ◽

Vol 6 (6) ◽

pp. 415-420

Author(s):

Ansuman Kumar ◽

Anindya Halder

Keyword(s):

Gene Expression ◽

Empirical Study ◽

Gene Expression Data ◽

Cancer Classification ◽

Expression Data

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Statistical methods for analysis of time course gene expression data

Frontiers in Bioscience ◽

10.2741/a743 ◽

2002 ◽

Vol 7 (1) ◽

pp. a90-98 ◽

Author(s):

Hongzhe Li

Keyword(s):

Gene Expression ◽

Statistical Methods ◽

Gene Expression Data ◽

Time Course ◽

Expression Data

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Faculty Opinions recommendation of A new type of stochastic dependence revealed in gene expression data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1032265.370760 ◽

2006 ◽

Author(s):

Arcady Mushegian

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Expression Data ◽

Stochastic Dependence ◽

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Faculty Opinions recommendation of A systematic comparison and evaluation of biclustering methods for gene expression data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1087930.540878 ◽

2007 ◽

Author(s):

Daniel Chamovitz

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Expression Data ◽

Systematic Comparison

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Faculty Opinions recommendation of CAERUS: predicting CAncER oUtcomeS using relationship between protein structural information, protein networks, gene expression data, and mutation data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.11029956.11977055 ◽

2011 ◽

Author(s):

Yuanpeng Janet Huang

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Structural Information ◽

Protein Networks ◽

Expression Data ◽

Cancer Outcomes ◽

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Faculty Opinions recommendation of Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1116793.572870 ◽

2008 ◽

Author(s):

Laura Haneline

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

In Silico ◽

Leukemia Stem Cells ◽

Expression Data

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Faculty Opinions recommendation of Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1116793.1165055 ◽

2010 ◽

Author(s):

Anthony D Ho ◽

Eike C Buss ◽

Patrick Wuchter

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

In Silico ◽

Leukemia Stem Cells ◽

Expression Data

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