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Updated: Sep 6, 2025
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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
Published on: March 5, 2022
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PHILM2Web: A high-throughput database of macromolecular host-pathogen interactions on the Web.
Tuan-Dung Le1, Phuong D Nguyen2, Dmitry Korkin3
1Department of Computer Science, Oklahoma State University, Stillwater, OK, USA.
Summary
This study introduces PHILM2Web, a novel platform for extracting pathogen-host interactions (HPIs) from biomedical literature. It provides a comprehensive database of HPIs, aiding infection research.
Area of Science:
- Bioinformatics
- Computational Biology
- Infectious Disease Research
Background:
- Host-pathogen interactions (HPIs) are crucial for understanding infection dynamics.
- Existing HPI databases are limited in scope or manually curated.
- Biomedical literature is a rich, yet underexplored, source of HPI data.
Purpose of the Study:
- To develop a high-throughput literature-mining platform for extracting HPI data.
- To create a comprehensive, automatically generated database of HPIs from PubMed abstracts.
- To provide researchers with a searchable portal and downloadable dataset of HPIs.
Main Methods:
- Utilized a high-precision HPI literature-mining algorithm (PHILM).
- Processed over 600,000 PubMed abstracts to identify HPIs.
- Integrated extracted HPI data into a web portal (PHILM2Web).
Main Results:
- Generated a database of 23,581 HPIs across 157 host and 403 pathogen organisms.
- Identified 257 HPIs relevant to COVID-19 from 25,796 abstracts.
- PHILM2Web offers searchable access and bulk download of the HPI dataset.
Conclusions:
- PHILM2Web provides the most comprehensive collection of HPIs from biomedical literature to date.
- The platform facilitates systematic study of HPIs, advancing infection research.
- Automated literature mining offers an efficient approach to HPI data curation.
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