Strong expertise in developing bioinformatics applications and databases (C, Perl, PHP, MySQL). Developed Scansite, a program for predicting phosphorylation sites and short binding motifs in proteins.
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Experience in DNA and protein sequence analysis (finding transcription factor binding sites, analyzing multiple sequence alignments, graphing phylogenetic trees, using SNP databases, and designing oligo probes).
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Experience in proteomics data analysis (detecting peaks, comparing images, and calculating molecular weights and isolectric points) and structural biology (NMR and X-ray crystallography).
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Familiar with protein structure modeling and visualization (using MODELLER and PyMOL).
Perdeep K. Mehta, Ph.D., Research Scientist
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Extensive research, implementation and administration experience in sequence analysis software tools and databases, including Vector NTI, Lasergene, Muscle, EMBOSS, TRANSFAC Professional and other public databases.
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Experience in development of bio-computational algorithms, such as FPA (Family Profile Analysis) to detect distant protein homologs and SSPred for predicting protein secondary structure.
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Design and development experience for meta databases, including PAARsnp for polymorphisms in pharmacokinetic anticancer agents, HCNetDat for microarray data (cDNA and Affymetrix) annotations, and Brain Gene Expression Map (BGEM).
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Training and teaching experience for several bioinformatics software suites, including ClustalW, Lasergene, and Vector-NTI Advance.
Suraj Mukatira, Ph.D., Associate Research Scientist
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Trained and experienced in bioinformatics with strong molecular biology/genomics research background.
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Research experience in promoter identification/extraction and motif-finding in co-regulated genes from array experiments.
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Mapping genes from array experiments on to canonical pathways and networks using Ingenuity interaction database and pathway builders like Vector Pathblazer and GenMAPP.
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Gene structure: identification of intron/exon boundaries, alternate transcripts and SNPs.
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Protein identification: Database comparisons and queries for protein/motif identification and evolutionary relatedness.
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Software evaluation and teaching experience (Vector NTI advance and various bioinformatics tools/softwares).
David Finkelstein, Ph.D., Associate Research Scientist
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Extensive microarray expression analysis experience for both spotted and oliognucleotide arrays, including developement of normalization and transformation methods that enhance the application of statistical models.
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Molecular biology, biochemistry and physiology background including experience in analyzing toxicology with microarrays.
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Developed novel methods for data quality assessment and for visualizing data in a statistical context.
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Experience in classical experimental design, sample size estimation, time series analysis, and factorial designs.
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Computational statistical experience (STATA, SAS, and R); familiar with multivariate linear regression, regression diagnostics, and nonparametric analysis.
Jing Ma, Ph.D., Research Scientist Supporting Pathology & Hem/Onc Departments
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Experienced in genomic data analysis (microarray, SNP array, etc.) to identify differentially expressed genes, common transcription factor binding sites, and genetic lesions (chromosomal amplification/deletion/LOH). Experienced in biological pathway analysis by integrating analysis results from the high-throughput data with the information from genomic annotation databases such as Gene Ontology.
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Familiar with open source bioinformatics tools such as EMBOSS and Bioperl, and statistical software packages such as R, S-Plus, and SAS. Familiar with commercial data mining software applications such as Spotfire, GeneMaths, GeneSpring and open source R packages from Bioconductor for analyzing genomic data. Experienced in developing bioinformatics applications using Perl/CGI/Oracle.
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Strong research experience in genome-wide microarray analysis of the insulin signaling pathway and molecular genetic study of the proteasome gene family in Drosophila.
