Microarray-based genomic surveys and other high-throughput approaches are becoming increasingly important in biology. As a result, methods are necessary to analyze and compare the abundant information embedded within the massive data sets they produce. Through a number of collaborations, we have produced several computer computer-based tools to analyse DNA sequence data and microarray expression output data.

Mar-Wiz, developed though a collaboration with Dr. Gautham Singh at Futuresoft, is an algorithm that analyzes DNA sequence data for motifs that bind the nuclear matrix. This web-based program plots a nuclear matrix binding potential along the length of queried sequence. Potentials higher than 0.75 are good candidates for regions of matrix association. go to Nuclear Matrix/Chromatin Structure

To go to Mar-Wiz, follow the link below.

TAQ, developed through a colaboration with the Computer Science department, uses a log-linear regression strategy to estimate the initial template quantity in a real-time PCR assay. go to Nuclear Matrix/Chromatin Structure

To access TAQ, follow the link below.

Onto-Express, developed though a collaboration with the computer sciences department at Wayne State University, correlates array expression profiles with the cytogenetic gene locations, the biochemical and molecular functions, the biological processes, cellular components and cellular roles of the translated proteins. The profiles created by Onto-Express fundamentally increase the value of gene expression analyses by facilitating the translation of quantitative value sets to records that contain biological implications. Onto-Express was used to evaluate some RNA in sperm data that was recently published in the Lancet (Ostermeier et al. 2002, 360: 772-777). go to RNA in sperm

To access Onto-Express, follow the link below.

go to Onto-Express go to MAR-Wiz go to TAQ


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Draghici, S., Martins, R.P., Leach, R.E. and Krawetz, S.A. (2001) Expressed Sequenced Tag Data Mining: The Reality of Virtual Gene Expression. Atlantic Symposium on Computational Biology, and Genome Information Systems & Technology 39 - 41. 

Martins, R.P., Leach, R.E. and Krawetz, S.A. (2001) Whole body gene expression by data mining. Genomics 72:34-42. [PubMed]

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Khatri, P., Draghici, S., Ostermeier, G.C. and Krawetz, S.A. (2002) Profiling gene expression utilizing onto-express. Genomics 79:266-270. [PubMed]

Ostermeier,G.C., Dix, D. J. and Krawetz, S.A. (2002) A bioinformatic strategy to rapidly characterize cDNA libraries. Bioinformatics 18:949-952.  [PubMed]

Draghici, S., Khatri, P., Martins, R.P., Ostermeier, G.C., and Krawetz, S.A. (2002) Global functional profiling of gene expression. Genomics. In press.

Ostermeier,G.C., Liu, Z., Martins, R.P., Draghici, S.. and Krawetz, S.A. (2002) Amplicon enrichment estimated with Target Analysis Quantification (TAQ) software. In review



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