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Connection

Mary Yang to Oligonucleotide Array Sequence Analysis

This is a "connection" page, showing publications Mary Yang has written about Oligonucleotide Array Sequence Analysis.

 
Connection Strength
 
 
 
0.681
 
  1. Zeng XQ, Li GZ, Wu GF, Yang JY, Yang MQ. Irrelevant gene elimination for partial least squares based dimension reduction by using feature probes. Int J Data Min Bioinform. 2009; 3(1):85-103.
    View in: PubMed
    Score: 0.293
  2. Pirooznia M, Gong P, Yang JY, Yang MQ, Perkins EJ, Deng Y. ILOOP--a web application for two-channel microarray interwoven loop design. BMC Genomics. 2008 Sep 16; 9 Suppl 2:S11.
    View in: PubMed
    Score: 0.072
  3. Li GZ, Bu HL, Yang MQ, Zeng XQ, Yang JY. Selecting subsets of newly extracted features from PCA and PLS in microarray data analysis. BMC Genomics. 2008 Sep 16; 9 Suppl 2:S24.
    View in: PubMed
    Score: 0.072
  4. Zeng XQ, Li GZ, Yang JY, Yang MQ, Wu GF. Dimension reduction with redundant gene elimination for tumor classification. BMC Bioinformatics. 2008 May 28; 9 Suppl 6:S8.
    View in: PubMed
    Score: 0.070
  5. Pirooznia M, Yang JY, Yang MQ, Deng Y. A comparative study of different machine learning methods on microarray gene expression data. BMC Genomics. 2008; 9 Suppl 1:S13.
    View in: PubMed
    Score: 0.068
  6. Yang JY, Li GZ, Meng HH, Yang MQ, Deng Y. Improving prediction accuracy of tumor classification by reusing genes discarded during gene selection. BMC Genomics. 2008; 9 Suppl 1:S3.
    View in: PubMed
    Score: 0.068
  7. Liu Q, Sung AH, Qiao M, Chen Z, Yang JY, Yang MQ, Huang X, Deng Y. Comparison of feature selection and classification for MALDI-MS data. BMC Genomics. 2009 Jul 07; 10 Suppl 1:S3.
    View in: PubMed
    Score: 0.019
  8. Yang JY, Yang MQ, Arabnia HR, Deng Y. Genomics, molecular imaging, bioinformatics, and bio-nano-info integration are synergistic components of translational medicine and personalized healthcare research. BMC Genomics. 2008 Sep 16; 9 Suppl 2:I1.
    View in: PubMed
    Score: 0.018
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.