L J Lancashire

Summary

Affiliation: University of Manchester
Country: UK

Publications

  1. doi request reprint A validated gene expression profile for detecting clinical outcome in breast cancer using artificial neural networks
    L J Lancashire
    Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester, M20 4BX, UK
    Breast Cancer Res Treat 120:83-93. 2010
  2. doi request reprint Identification of gene transcript signatures predictive for estrogen receptor and lymph node status using a stepwise forward selection artificial neural network modelling approach
    Lee J Lancashire
    Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester M20 4BX, United Kingdom
    Artif Intell Med 43:99-111. 2008
  3. doi request reprint An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies
    Lee J Lancashire
    Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester M20 4BX, UK
    Brief Bioinform 10:315-29. 2009

Detail Information

Publications3

  1. doi request reprint A validated gene expression profile for detecting clinical outcome in breast cancer using artificial neural networks
    L J Lancashire
    Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester, M20 4BX, UK
    Breast Cancer Res Treat 120:83-93. 2010
    ..Importantly our principal prognosticator, CA9, showed that it is capable of selecting an aggressive subgroup of patients who are known to have poor prognosis...
  2. doi request reprint Identification of gene transcript signatures predictive for estrogen receptor and lymph node status using a stepwise forward selection artificial neural network modelling approach
    Lee J Lancashire
    Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester M20 4BX, United Kingdom
    Artif Intell Med 43:99-111. 2008
    ..These high throughput technologies have resulted in an unprecedented rate of data generation, often of high complexity, highlighting the need for novel data analysis methodologies that will cope with data of this nature...
  3. doi request reprint An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies
    Lee J Lancashire
    Clinical and Experimental Pharmacology, Paterson Institute for Cancer Research, University of Manchester, Manchester M20 4BX, UK
    Brief Bioinform 10:315-29. 2009
    ....