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Updated: Jun 23, 2026

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

An on demand data integration model for biological databases.

Mathew Palakal¹, Pavithra Naidu

¹School of Informatics, Indiana University Purdue University Indianapolis, 535 West Michigan St., IT 475, Indianapolis, Indiana, USA. mpalakal@iupui.edu

International Journal of Data Mining and Bioinformatics

|May 13, 2009

Summary

This summary is machine-generated.

BioXBase is a novel biological query system that integrates data from diverse sources. It enhances information retrieval by 30%, providing a unified, real-time view for improved biological knowledge acquisition.

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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

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A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

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Published on: May 27, 2021

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Area of Science:

Bioinformatics
Computational Biology
Data Science

Background:

Biological data is increasingly distributed across heterogeneous sources.
Integrating this data for knowledge acquisition presents significant challenges.
Existing systems often lack comprehensive, real-time data integration capabilities.

Purpose of the Study:

To develop a user-centric biological query system (BioXBase) for seamless information integration.
To enable real-time knowledge acquisition from distributed, semantically heterogeneous biological data sources.
To present integrated biological information in a homogeneous, unified view.

Main Methods:

Development of the BioXBase system for real-time, on-the-fly information extraction.
Querying multiple distributed biological data sources over the internet.
Organizing retrieved information into a unified data view.
Comparative analysis against systems with only local databases.

Main Results:

BioXBase improved retrieval results by 30% compared to systems using only local databases.
Combining BioXBase results with a local database further enhanced results by 20%.
The system provides a homogeneous, unified view of biological information in real time.

Conclusions:

BioXBase effectively addresses the challenge of integrating distributed biological data.
The system significantly enhances the accuracy and significance of biological information retrieval.
BioXBase facilitates efficient knowledge acquisition for biological research.