Connection

Feng Luo to Gene Expression Profiling

This is a "connection" page, showing publications Feng Luo has written about Gene Expression Profiling.
Connection Strength

1.106
  1. Identifying differentially expressed genes in cancer patients using a non-parameter Ising model. Proteomics. 2011 Oct; 11(19):3845-52.
    View in: PubMed
    Score: 0.315
  2. Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory. BMC Bioinformatics. 2007 Aug 14; 8:299.
    View in: PubMed
    Score: 0.238
  3. Application of random matrix theory to microarray data for discovering functional gene modules. Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Mar; 73(3 Pt 1):031924.
    View in: PubMed
    Score: 0.217
  4. Predicting protein phosphorylation from gene expression: top methods from the IMPROVER Species Translation Challenge. Bioinformatics. 2015 Feb 15; 31(4):462-70.
    View in: PubMed
    Score: 0.096
  5. Massive-scale gene co-expression network construction and robustness testing using random matrix theory. PLoS One. 2013; 8(2):e55871.
    View in: PubMed
    Score: 0.087
  6. Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules. PLoS One. 2012; 7(9):e45041.
    View in: PubMed
    Score: 0.085
  7. Integrated Genome-Scale Analysis Identifies Novel Genes and Networks Underlying Senescence in Maize. Plant Cell. 2019 09; 31(9):1968-1989.
    View in: PubMed
    Score: 0.034
  8. A new reference genome for Sorghum bicolor reveals high levels of sequence similarity between sweet and grain genotypes: implications for the genetics of sugar metabolism. BMC Genomics. 2019 May 27; 20(1):420.
    View in: PubMed
    Score: 0.034
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.