This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Analysis of gene expression data for cancer classification can provide valuable information for early diagnosis and treatment. The computational extraction of derived patterns from microarray gene expression is a non-trivial task that involves sophisticated algorithm design and analysis for specific domain discovery. Moreover, the extraction of biologically significant knowledge from the gene expression data is a growing computational challenge, as the large number of genes, which can correspond to different time sequences or tissue types, has a dimensionality that is several orders of magnitude more than the evaluated samples. During this reporting period, we have developed a formal approach for feature extraction of genes by first applying feature selection heuristics based on the statistical impurity measures and analyzing the associative dependencies between the genes and then computing weights to the genes based on their degree of participation in the rules. Consequently, we developed a weighted Jaccard and vector cosine similarity measure to compute the similarity between the discovered rules. To demonstrate the usability and efficiency of the concept of our technique, we applied it to three publicly available, multiclass cancer gene expression datasets and performed a biomedical literature search to support the effectiveness of our results.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Exploratory Grants (P20)
Project #
2P20RR016456-09
Application #
8168135
Study Section
Special Emphasis Panel (ZRR1-RI-7 (01))
Project Start
2010-07-15
Project End
2011-04-30
Budget Start
2010-07-15
Budget End
2011-04-30
Support Year
9
Fiscal Year
2010
Total Cost
$55,546
Indirect Cost
Name
Louisiana State University A&M Col Baton Rouge
Department
Pathology
Type
Schools of Veterinary Medicine
DUNS #
075050765
City
Baton Rouge
State
LA
Country
United States
Zip Code
70803
Hosain, Salman B; Khiste, Sachin K; Uddin, Mohammad B et al. (2016) Inhibition of glucosylceramide synthase eliminates the oncogenic function of p53 R273H mutant in the epithelial-mesenchymal transition and induced pluripotency of colon cancer cells. Oncotarget 7:60575-60592
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