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      by 
      Nguyen, Phan, author. (orcid)0000-0001-8002-2979
      Format: 
      Excerpt: 
      Methods for Inferring Gene Regulatory Networks from Time Series Expression Data / Nguyen, Phan
      by 
      Chiang, Colby, author. (orcid)0000-0002-4113-6065
      Format: 
      Excerpt: 
      The Impact of Structural Variation on Human Gene Expression / Chiang, Colby, author. (orcid)0000
      by 
      Mohaimani, Aurash, author. (orcid)0000-0002-9286-8071
      Format: 
      Excerpt: 
      GEORAC: An RNA-Seq Atlas Constructor for the Gene Expression Omnibus / Mohaimani, Aurash, author
      by 
      Tien, Matthew, author. (orcid)0000-0002-0006-9644
      Format: 
      Excerpt: 
      Gene regulation underlies all functional outputs of a cell. Measuring changes in gene expression
      by 
      Varn, Frederick S., author.
      Format: 
      Excerpt: 
      methodology for inferring immune infiltration levels of distinct cellular subsets from patient gene expression
      by 
      Murphy, Julianne, author.
      Format: 
      Excerpt: 
      direct associations between miRNA CNV, miRNA gene expression, target gene expression, and phenotype.
      by 
      Hughitt, Vincent Keith, author. (orcid)0000-0003-0787-9559
      Format: 
      Excerpt: 
      -pathogen interactions. While popular techniques such as differential expression and gene set enrichment analysis can
      by 
      Shu, Le, author.
      Format: 
      Excerpt: 
      -wide datasets of total cholesterol and fasting glucose. I then applied Mergeomics to identify the shared gene
      by 
      Deeter, Anthony, author.
      Format: 
      Excerpt: 
      , processes, and discretizes RNA-Seq gene expression data. This module was used and tested to process lung
      by 
      Hixson, Kim Kathleen, author. (orcid)0000-0003-3915-7040
      Format: 
      Excerpt: 
      ADT knock-outs (KOs) and over-expression (OE) lines. By using both KO and OE lines we could provide
      by 
      Lin, Nan, author.
      Format: 
      Excerpt: 
      following two types of data effectively: 1. the time-course data such as the time-course gene expression
      by 
      Zhang, Ruoyu, author. (orcid)0000-0001-5672-5527
      Format: 
      Excerpt: 
      observed heteroplasmy dynamics could significantly affect certain gene expression levels.
      by 
      Hsiao, Yun-Hua, author.
      Format: 
      Excerpt: 
      relatively well studied, but their impact on co- and post-transcriptional control of gene expression is less
      by 
      Mbewe-Campbell, Nzali Violet, author.
      Format: 
      Excerpt: 
      calculating q-values for pairwise differential gene expression; chi-square tests to determine independence
      by 
      Liu, Wanlu, author.
      Format: 
      Excerpt: 
      gene expression. In order to develop site-specific and efficient tools for DNA methylation targeting