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Connection

Lance Miller to Algorithms

This is a "connection" page, showing publications Lance Miller has written about Algorithms.
Connection Strength

0.396
  1. Song Q, Wang H, Bao J, Pullikuth AK, Li KC, Miller LD, Zhou X. Systems biology approach to studying proliferation-dependent prognostic subnetworks in breast cancer. Sci Rep. 2015 Aug 10; 5:12981.
    View in: PubMed
    Score: 0.101
  2. Lee WH, Wong CW, Leong WY, Miller LD, Sung WK. LOMA: a fast method to generate efficient tagged-random primers despite amplification bias of random PCR on pathogens. BMC Bioinformatics. 2008 Sep 10; 9:368.
    View in: PubMed
    Score: 0.063
  3. Miller LD, Liu ET. Expression genomics in breast cancer research: microarrays at the crossroads of biology and medicine. Breast Cancer Res. 2007; 9(2):206.
    View in: PubMed
    Score: 0.056
  4. Wong CW, Heng CL, Wan Yee L, Soh SW, Kartasasmita CB, Simoes EA, Hibberd ML, Sung WK, Miller LD. Optimization and clinical validation of a pathogen detection microarray. Genome Biol. 2007; 8(5):R93.
    View in: PubMed
    Score: 0.056
  5. Ivshina AV, George J, Senko O, Mow B, Putti TC, Smeds J, Lindahl T, Pawitan Y, Hall P, Nordgren H, Wong JE, Liu ET, Bergh J, Kuznetsov VA, Miller LD. Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res. 2006 Nov 01; 66(21):10292-301.
    View in: PubMed
    Score: 0.055
  6. Miller LD, Long PM, Wong L, Mukherjee S, McShane LM, Liu ET. Optimal gene expression analysis by microarrays. Cancer Cell. 2002 Nov; 2(5):353-61.
    View in: PubMed
    Score: 0.042
  7. Ploner A, Miller LD, Hall P, Bergh J, Pawitan Y. Correlation test to assess low-level processing of high-density oligonucleotide microarray data. BMC Bioinformatics. 2005 Mar 31; 6:80.
    View in: PubMed
    Score: 0.012
  8. Peng X, Karuturi RK, Miller LD, Lin K, Jia Y, Kondu P, Wang L, Wong LS, Liu ET, Balasubramanian MK, Liu J. Identification of cell cycle-regulated genes in fission yeast. Mol Biol Cell. 2005 Mar; 16(3):1026-42.
    View in: PubMed
    Score: 0.012
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.