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Health Information Technology and Healthcare Information System

Health Information Technology and Healthcare Information System

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Related Experiment Video

Updated: Jun 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Database systems for knowledge-based discovery.

Sarma A R P Jagarlapudi¹, K V Radha Kishan

¹S-1, Phase-1, TIE, GVK Biosciences Pvt. Ltd., Balanagar, Hyderabad, India.

Methods in Molecular Biology (Clifton, N.J.)

|September 4, 2009

Summary

This summary is machine-generated.

Structured databases offer valuable information for researchers, aiding drug design and discovery. GVK BIO develops specialized databases from scientific literature for enhanced data analysis and knowledge derivation.

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Published on: November 22, 2019

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Last Updated: Jun 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Published on: June 13, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Area of Science:

Biomedical Informatics
Drug Discovery
Computational Chemistry

Background:

Database systems are crucial for organizing scientific information for diverse professionals.
Information technology advancements enable efficient access and analysis of large datasets.
Structured databases facilitate compilation, searching, archiving, analysis, and knowledge derivation.

Purpose of the Study:

To describe the development of specialized databases by GVK BIO.
To highlight the utility of these databases in research areas like medicinal chemistry and drug discovery.
To emphasize the potential of integrating databases with knowledge derivation tools.

Main Methods:

Development of databases from publicly available scientific literature.
Classification of databases as reference-centric or compound-centric.
Focus on specific research areas including medicinal chemistry, clinical research, and mechanism-based toxicity.

Main Results:

Creation of structured databases containing vast amounts of scientific data.
Databases are designed to be either reference-centric or compound-centric.
The developed databases are suitable for various research applications.

Conclusions:

Structured databases are essential for advancing drug design and discovery.
Integration with knowledge derivation tools significantly enhances the value of these databases.
GVK BIO's databases provide a valuable resource for the scientific community.