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  • Influence
Quantile normalization for combining gene-expression datasets
TLDR
In this study, quantile normalization (QN) was utilized to remove the unwanted dataset variations, after which the adjusted datasets were used for classification. Expand
  • 6
  • 1
A high-dimension two-sample test for the mean using cluster subspaces
  • J. Zhang, M. Pan
  • Mathematics, Computer Science
  • Comput. Stat. Data Anal.
  • 1 May 2016
TLDR
A common problem in modern genetic research is that of comparing the mean vectors of two populations-typically in settings in which the data dimension is larger than the sample size-where Hotelling's test cannot be applied. Expand
  • 12
  • 1
Correlation-based linear discriminant classification for gene expression data.
  • M. Pan, J. Zhang
  • Computer Science, Medicine
  • Genetics and molecular research : GMR
  • 23 January 2017
TLDR
In this study, a recently developed correlation-based classifier, the ensemble of random subspace (RS) Fisher linear discriminants (FLDs), was utilized. Expand
  • 2
  • PDF
Genetic or non-genetic prognostic factors in colon cancer
  • J. Zhang, M. Pan
  • Biology, Computer Science
  • 12th International Conference on Fuzzy Systems…
  • 1 August 2015
TLDR
This study was trying to identify whether a prognostic factor was genetic or not by using GEPs. Expand
  • 1
Genetic or non-genetic prognostic factors for colon cancer classification
Many researches have addressed patient classification using prognostic factors or gene expression profiles (GEPs). This study tried to identify whether a prognostic factor was genetic by using GEPs.Expand
A Knowledge Recommendation Algorithm Based on Time Migration
TLDR
We propose a knowledge recommendation algorithm based on time migration (KRBTM) based on short-term and long-term behavior of users. Expand
Selecting and combining biomarkers by gene expression profiles for colon cancer classification
  • M. Pan, J. Zhang
  • Biology, Computer Science
  • 8th International Conference on Biomedical…
  • 1 October 2015
TLDR
In order to improve colorectal cancer (CRC) stratification, researches made before were using biomarkers, biomarker combinations or gene expression profile clustering individually for patient classification. Expand
Genetic or non-genetic prognostic factors for colon cancer classification