Bioinformatics

Researchers require analytic solutions to map experimental data in the context of biological systems for

• Effective interpretation of high-throughput data
• Gaining insights into multidimensional data
• Correlating experimental data with annotation, clinical and administrative data

Integration of disparate sources of biological data to leverage publicly-curated biological content combined with proprietary content sources for

• Efficient searching, querying and reporting for research
• Enabling translational research
• Ensuring data consistency, security and compliance

Persistent Advantage

• Team of domain experts including a number of experienced molecular biologist, bioinformaticians  with PhDs in bioinformatics, computer science, statistics, and biology
• Hands-on knowledge of tools including Genespring, Rosetta Resolver, Spotfire, tools for Sanger as well as NGS data analysis
• Computational Experts having extensive experience with R, Bioconductor, Matlab, SAS, SPSS, Clementine, Intelligent Miner, Octave, Weka, Scilab, Orange
• Deep understanding of various life sciences and experiment data sources such as Entrez Gene, Unigene, Gene Ontology, Homologene, dbSNP, GEO, ArrayExpress, BIND

Persistent Offerings

• Sanger and Next Generation Sequencing, Genotyping, Mutation Profiling
  • Data Warehousing for high-throughput sequencing  data
  • Development of new algorithms for secondary and tertiary sequence data analysis
  • Performance improvement of prototype algorithms/tools
  • Development of new tools  for  sequence data visualization, experiment specific pipeline
  • Enhancement and support for exciting software and tools
  • Customize widely used open source sequence analysis tools to support for Next Gen Sequencing (NGS) plate form specific analysis
  • Algorithm/Functional Testing
• Gene Expression Analysis
  • Gene Expression Analysis Platform with comprehensive statistical analysis and visualization tools
  • Algorithms for correlating annotation data with expression data
  • Visualization: Bar graph, scatter plot and heat-map (all web-based)
• Proteomics
  • Workflow management
  • Multi-role system
• Metabolomics
  • Looking for signatures in spectroscopic data
  • Detection of anomalies like spikes, artifacts etc.
• Data mart design based on
  • Life sciences semantics
  • Reporting requirements for scientific explorations
  • Reusable parsing framework and components for
  • Biological data formats
  • Entrez Gene, Gene Ontology, Homologene, UniGene, dbSNP
  • Domain specific transformation strategies
  • Mapping of multimodality data
  • Annotations: experimental, clinical, chemical, biological
     

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