Microarray and Genome Informatics

National Institute Of Environmental Health Sciences

Investigators

Linked publications & trials

Abstract

Developed an application for generation of phenotypic prototypes using simulated annealing (SAModk-prototypes). The application uses k-mode and k-means style clustering of categorical histopathology observations and numeric gene expression and clinical chemistry data respectively via simulated annealing optimization to cluster biological samples into groups which share phenotypic responses to stimuli. The clustering of the samples using SAModk-prototypes and all the data together performs better than clustering of the data using any one of the data domains separately or pairwise combinations of the data.[unreadable] [unreadable] --------------------------------------------------------------------------------------------------[unreadable] [unreadable] Developed a software for biclustering of gene expression data using phenotypic measurements to constraint the clustering of the genes or by unsupervised clustering. The biclusters are phenotypically anchored to the gene expression. Constraining the clusters by Gene Onology biological processes was investigated. [unreadable] [unreadable] --------------------------------------------------------------------------------------------------[unreadable] [unreadable] Performed scanning of the rat genome to search for patterns of DNA sequence and motifs. The association of genome characteristics with differential expression of environmentally responsive genes was explored. [unreadable] [unreadable] --------------------------------------------------------------------------------------------------[unreadable] [unreadable] Developed the MicroArray Project System (MAPS) database for more customized management of experimental information and data from microarray studies. [unreadable] [unreadable] --------------------------------------------------------------------------------------------------[unreadable] [unreadable] Developed computational means to analyze the S. pombe (yeast) genome across multiple time series experiments and to find transcription factor-gene regulatory units. In addition, circle-circle regression modeling was performed on subsets of S. pombe cyclic genes to determine coherence between 10 time series experiments.