GeNLP: a web tool for NLP-based exploration and prediction of microbial gene function

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Understanding microbial gene function is crucial for various biological applications.
• Predicting the function of uncharacterized genes remains a significant challenge in genomics.

Purpose of the Study:

• To introduce GeNLP, a web application for exploring microbial gene semantics.
• To enable predictions of uncharacterized gene families using genomic context.
• To provide an interactive platform for accessing and utilizing gene relationship data.

Main Methods:

• Utilizes a pre-trained language model for analyzing genomic data.
• Employs natural language processing (NLP) techniques to uncover gene relationships.
• Provides a web-based interactive interface for user exploration and prediction.

Main Results:

• GeNLP facilitates the exploration of microbial gene "semantics".
• The application enables predictions of gene families based on genomic context.
• Users can interact with the data to uncover gene relationships.

Conclusions:

• GeNLP offers a novel approach to understanding microbial gene function.
• The web application democratizes access to advanced genomic analysis tools.
• GeNLP empowers researchers to make data-driven predictions about uncharacterized genes.