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An Application In Bioinformatics : A Comparison Of Affymetrix And Compugen Human Genome Microarrays, Milind Misra
An Application In Bioinformatics : A Comparison Of Affymetrix And Compugen Human Genome Microarrays, Milind Misra
Theses
The human genome microarrays from Compugen® and Affymetrix® were compared in the context of the emerging field of computational biology. The two premier database servers for genomic sequence data, the National Center for Biotechnology Information and the European Bioinformatics Institute, were described in detail. The various databases and data mining tools available through these data servers were also discussed. Microarrays were examined from a historical perspective and their main current applications-expression analysis, mutation analysis, and comparative genomic hybridization-were discussed. The two main types of microarrays, cDNA spotted microarrays and high-density spotted microarrays were analyzed by exploring the human genome microarray …
A Method For Developing In-Silico Protein Homologs, Susan Mcclatchy
A Method For Developing In-Silico Protein Homologs, Susan Mcclatchy
Theses
Computational methods for identifying and screening the most promising drug receptor candidates in the human genome are of great interest to drug discovery researchers. Successful methods will accurately identify and narrow the field of potential drug receptor candidates. This study details one such method.
The method described here begins with the assumption that novel drug receptors have high sequence similarity to established drug receptors. The similarity search program FASTA3 aligns translated sequences of the human genome to known drug receptor sequences and ranks these alignments by measuring their statistical significance. Query results returned by FASTA3 are assembled into "in-silico proteins" …
Analysis Of Gene Expression Data Using Expressionist 3.1 And Genespring 4.2, Indu Shrivastava
Analysis Of Gene Expression Data Using Expressionist 3.1 And Genespring 4.2, Indu Shrivastava
Theses
The purpose of this study was to determine the differences in the gene expression analysis methods of two data mining tools, ExpressionisticTM 3.1 and GeneSpringTM 4.2 with focus on basic statistical analysis and clustering algorithms. The data for this analysis was derived from the hybridization of Rattus norvegicus RNA to the Affymetrix RG34A GeneChip. This analysis was derived from experiments designed to identify changes in gene expression patterns that were induced in vivo by an experimental treatment.
The tools were found to be comparable with respect to the list of statistically significant genes that were up-regulated by more …