Molecular Connections’ knowledgebase of biomolecular interactions facilitates the pharmaceutical companies to build customized disease specific pathways. We employ deep curation and Natural Language Processing (NLP) based text mining methods to identify novel gene/gene-mutation and disease associations from scientific literature to create state-of-the-art disease pathways.
In a biological system the signal is transmitted through series of molecular interactions. Network analysis is one of the primary mode of data integration and analysis methods for the study of complex biological systems. Network building can also be case specific for example in case of disease specific molecular mechanisms.
At Molecular Connections, we systemically break down the scientific literature into its parts and build relationships between the molecular entities by combining manual curation and text mining approaches depending on the specific needs of the project. Our domain experts have put together a knowledgebase of protein-protein and protein-small molecule interaction. The knowledgebase is regularly updated and the contents can be used to model biological pathways systemically, to study cross talk between pathways and also to construct disease specific pathways.

Select Case Studies

  • For a top pharmaceutical company we constructed an interactome of molecular components involved in the epigenetic regulation, in order for the client to identify signaling pathways and molecular targets involved in the amelioration of specific disease case.
  • Probable interaction networks involved in pathology of Alzheimer’s disease: predicting targets and therapeutic agents-NetProTM based study.
    Objective: To highlight the application of NetProTMin predicting interaction networks, potential targets and therapeutic agents for specific pathological conditions using high throughput data

Case Studies