 Connection
Galina Glazko to Gene Expression Profiling
This is a "connection" page, showing publications Galina Glazko has written about Gene Expression Profiling.
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Connection Strength |
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1.943 |
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Rahmatallah Y, Zybailov B, Emmert-Streib F, Glazko G. GSAR: Bioconductor package for Gene Set analysis in R. BMC Bioinformatics. 2017 Jan 24; 18(1):61.
Score: 0.401
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Rahmatallah Y, Emmert-Streib F, Glazko G. Comparative evaluation of gene set analysis approaches for RNA-Seq data. BMC Bioinformatics. 2014 Dec 05; 15:397.
Score: 0.346
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Rahmatallah Y, Emmert-Streib F, Glazko G. Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets. Bioinformatics. 2014 Feb 01; 30(3):360-8.
Score: 0.323
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Glazko GV, Emmert-Streib F. Unite and conquer: univariate and multivariate approaches for finding differentially expressed gene sets. Bioinformatics. 2009 Sep 15; 25(18):2348-54.
Score: 0.238
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Musa A, Ghoraie LS, Zhang SD, Glazko G, Yli-Harja O, Dehmer M, Haibe-Kains B, Emmert-Streib F. A review of connectivity map and computational approaches in pharmacogenomics. Brief Bioinform. 2018 05 01; 19(3):506-523.
Score: 0.110
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Glazko G, Rahmatallah Y, Zybailov B, Emmert-Streib F. Extracting the Strongest Signals from Omics Data: Differentially Expressed Pathways and Beyond. Methods Mol Biol. 2017; 1613:125-159.
Score: 0.100
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Rahmatallah Y, Emmert-Streib F, Glazko G. Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline. Brief Bioinform. 2016 05; 17(3):393-407.
Score: 0.091
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Stupnikov A, Glazko GV, Emmert-Streib F. Effects of subsampling on characteristics of RNA-seq data from triple-negative breast cancer patients. Chin J Cancer. 2015 Aug 08; 34(10):427-38.
Score: 0.091
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Tripathi S, Glazko GV, Emmert-Streib F. Ensuring the statistical soundness of competitive gene set approaches: gene filtering and genome-scale coverage are essential. Nucleic Acids Res. 2013 Apr; 41(7):e82.
Score: 0.076
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Hu R, Qiu X, Glazko G, Klebanov L, Yakovlev A. Detecting intergene correlation changes in microarray analysis: a new approach to gene selection. BMC Bioinformatics. 2009 Jan 15; 10:20.
Score: 0.058
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Manjang K, Tripathi S, Yli-Harja O, Dehmer M, Glazko G, Emmert-Streib F. Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning. Sci Rep. 2021 01 08; 11(1):156.
Score: 0.033
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Thomas J, Kim HR, Rahmatallah Y, Wiggins G, Yang Q, Singh R, Glazko G, Mukherjee A. RNA-seq reveals differentially expressed genes in rice (Oryza sativa) roots during interactions with plant-growth promoting bacteria, Azospirillum brasilense. PLoS One. 2019; 14(5):e0217309.
Score: 0.029
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Emmert-Streib F, de Matos Simoes R, Glazko G, McDade S, Haibe-Kains B, Holzinger A, Dehmer M, Campbell F. Functional and genetic analysis of the colon cancer network. BMC Bioinformatics. 2014; 15 Suppl 6:S6.
Score: 0.021
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Hanin L, Awadalla SS, Cox P, Glazko G, Yakovlev A. Chromosome-specific spatial periodicities in gene expression revealed by spectral analysis. J Theor Biol. 2009 Feb 07; 256(3):333-42.
Score: 0.014
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Klebanov L, Glazko G, Salzman P, Yakovlev A, Xiao Y. A multivariate extension of the gene set enrichment analysis. J Bioinform Comput Biol. 2007 Oct; 5(5):1139-53.
Score: 0.013
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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