Identifying association of a STIM1 genes related to prognosis of solid tumor: a bioinformatics analysis of gene expression data

Proceedings for Annual Meeting of The Japanese Pharmacological Society ◽

10.1254/jpssuppl.wcp2018.0_po4-10-29 ◽

2018 ◽

Vol WCP2018 (0) ◽

pp. PO4-10-29

Author(s):

Md Misbah ◽

Wei Chiao Chang

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Solid Tumor ◽

Bioinformatics Analysis ◽

Expression Data

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P.0606 Identification of key genes involved in antipsychotic-induced metabolic dysregulation based on integrative bioinformatics analysis of multi-tissue gene expression data

European Neuropsychopharmacology ◽

10.1016/j.euroneuro.2021.10.571 ◽

2021 ◽

Vol 53 ◽

pp. S445

Author(s):

P. Gassó ◽

A. Martínez-Pinteño ◽

L. Prohens ◽

À.G. Segura ◽

M. Parellada ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Bioinformatics Analysis ◽

Expression Data ◽

Metabolic Dysregulation ◽

Key Genes ◽

Tissue Gene Expression

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Bioinformatics analysis of gene expression data for the identification of critical genes in breast invasive carcinoma

Molecular Medicine Reports ◽

10.3892/mmr.2017.7717 ◽

2017 ◽

Vol 16 (6) ◽

pp. 8657-8664 ◽

Author(s):

Yi Li ◽

Yongsheng Wang

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Invasive Carcinoma ◽

Bioinformatics Analysis ◽

Expression Data

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Comprehensive bioinformatics analysis of trabecular meshwork gene expression data to unravel the molecular pathogenesis of primary open‐angle glaucoma

Acta Ophthalmologica ◽

10.1111/aos.14154 ◽

2019 ◽

Vol 98 (1) ◽

pp. 48-57 ◽

Author(s):

Ilona Liesenborghs ◽

Lars M. T. Eijssen ◽

Martina Kutmon ◽

Theo G. M. F. Gorgels ◽

Chris T. Evelo ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Trabecular Meshwork ◽

Bioinformatics Analysis ◽

Primary Open Angle Glaucoma ◽

Open Angle Glaucoma ◽

Molecular Pathogenesis ◽

Expression Data ◽

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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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