Open-Source

ForenSight is a set of open-source tools developed to assist genomics researchers forensic and genetic experts in performing comparative genetetics and DNA-matching.

Beyond its ability to accelerate comparative genetic analyses, ForenSight also addresses one of the major global challenges faced by forensic institutions — the secure storage of genetic data — through its encrypted vector database technology. With this proprietary methodology developed by our team, genetic information is encrypted to prevent potential biosecurity risks while preserving the unique value of DNA sequences. This allows forensic genetic comparisons to continue functioning seamlessly based on these encrypted representations.

In addition, the novel framework behind PharmaSight is designed to context-aware similarity computation and kernel-based vector database implementation is designed to detect and compute invisible contextual similarities, assisting researchers to perform their studies with a higher probability for exploration.

PharmaSight is an open-source technology designed to enable drug repositioning and repurposing with commodity hardware with seamless efficiency and precise accuracy. Compatible with broad range of proteomic and molecular file formats to be implementable for all types of workflows within drug development R&D infrastructure.

MoleSight is an open-source technology developed to be used drug development and pharmacophore studies optimize the molecular structure of drug candidates, docking simulations, binding affinity computations and chemistry simulations even with commodity hardware.

The architecture behind the MoleSight is optimized to effciently perform physics-based molecular simulations for target-ligand pairs. In addition, can be used to explore binding pockets with target-only setting and local molecular arrangement with ligand-only setting, enabling MoleSight to be compatible with broad range of use cases.

SequenSight is a novel statistical framework and open-source implementation, developed to perform analysis for Physical properties of biosequences and contribute multiple scientific fields of study, including gene analysis, variant detection, RNA and protein folding.

The novel, quantum-inspired methodology behind the SequenSight enables the multi-context analysis of the DNA, RNA and Amino Acid chains. Furthermore, it stands as a solid preprocessing framework for omics-driven machine learning applications.

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