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Sophic Chemo Genomics

Sophic Chemo-Genomics Module included in Sophic’s Drug Safety system is also a standalone module. Chemo-Genomics is integrates the Broad Institute’s CMap, MSig DB and GSEA analysis packages into the BioXM Knowledge Management Suite. This integration allows investigators to submit individual or batch experiments that are processed through both CMap and MSig to produce a list of chemical compounds with similar gene expression signatures. This rapid identification and analysis of potential drugs that may impact gene expression signatures is important for understanding and curing cancers and other complex diseases. SCS experimental results can be easily and automatically integrated with the BioXM repositories to identify other potentially valuable networks and information found in public and internal data sets.

The Broad Institute Connectivity Map (also known as CMap) is a collection of genome-wide transcriptional expression data from cultured human cells treated with bioactive small molecules and simple pattern-matching algorithms that together enable the discovery of functional connections between drugs, genes and diseases through the transitory feature of common gene expression changes. The MSig Database is used as a reference for finding related signal transduction pathways.
The Sophic Chemo-Genomics System (SCS) is designed to integrate CMap, MSig DB and GSEA analysis packages within the BioXM Knowledge Management System. This integration allows investigators to submit individual or batch experiments that are processed through both CMap and MSig to produce a list of chemical compounds with similar gene expression signatures. This rapid identification and analysis of potential drugs that may impact gene expression signatures is important for understanding and curing cancers and other complex diseases. SCS experimental results can be easily and automatically integrated with the BioXM repositories to identify other potentially valuable networks and information found in public and internal data sets.
Integration between SCS and BioXM produces valuable results and is easy to use:

  • Input a list of genes of interest from laboratory experiments to SCS. This list will form a unique expression profile or signature.
  • Ask SCS whether the drug or treatment used in the expression study has a similar gene profile or signature to the gene list in (1.) above. SCS uses the Sophic-improved Broad Institute statistical analysis tool (or other statistical analysis tool) for profiling to compare the gene expression pattern between the gene set in CMap and those in the experiment(s).
  • SCS output is a list of drugs/compounds found in CMap that are automatically integrated into BioXM for further enrichment derived from multiple reference databases. SCS and BioXM provide extensive information on the known compounds related to the gene expression profiles and help explain the mode of action for the experimental compounds or treatments based on the known drug mechanisms.

SCS will help scientists more efficiently research cancer and other complex diseases, manage data integration, organize and control complex research projects and identify potential biomarkers, targets, and drugs.

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