 Connection
Galina Glazko to Computational Biology
This is a "connection" page, showing publications Galina Glazko has written about Computational Biology.
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Connection Strength |
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2.865 |
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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: 0.513
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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: 0.510
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Glazko GV, Zybailov BL, Rogozin IB. Computational prediction of polycomb-associated long non-coding RNAs. PLoS One. 2012; 7(9):e44878.
Score: 0.379
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Hu R, Qiu X, Glazko G. A new gene selection procedure based on the covariance distance. Bioinformatics. 2010 Feb 01; 26(3):348-54.
Score: 0.313
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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: 0.303
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Glazko GV, Mushegian AR. Detection of evolutionarily stable fragments of cellular pathways by hierarchical clustering of phyletic patterns. Genome Biol. 2004; 5(5):R32.
Score: 0.212
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Glazko GV, Koonin EV, Rogozin IB, Shabalina SA. A significant fraction of conserved noncoding DNA in human and mouse consists of predicted matrix attachment regions. Trends Genet. 2003 Mar; 19(3):119-24.
Score: 0.196
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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: 0.140
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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: 0.073
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Koonin EV, Rogozin IB, Glazko GV. p53 gain-of-function: tumor biology and bioinformatics come together. Cell Cycle. 2005 May; 4(5):686-8.
Score: 0.057
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Rogozin IB, Glazko GV, Glazkov MV. Computer prediction of sites associated with various elements of the nuclear matrix. Brief Bioinform. 2000 Feb; 1(1):33-44.
Score: 0.039
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Smolander J, Stupnikov A, Glazko G, Dehmer M, Emmert-Streib F. Comparing biological information contained in mRNA and non-coding RNAs for classification of lung cancer patients. BMC Cancer. 2019 Dec 03; 19(1):1176.
Score: 0.039
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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: 0.027
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Smolock EM, Korshunov VA, Glazko G, Qiu X, Gerloff J, Berk BC. Ribosomal protein L17, RpL17, is an inhibitor of vascular smooth muscle growth and carotid intima formation. Circulation. 2012 Nov 13; 126(20):2418-27.
Score: 0.024
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Emmert-Streib F, de Matos Simoes R, Tripathi S, Glazko GV, Dehmer M. A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data. Sci Rep. 2012; 2:513.
Score: 0.023
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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: 0.017
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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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