Biotextgraph: Graphical Summarization of Functional Similarities from Textual Information

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2024 Jun 9

PMID 38851878

Authors

Noriaki Sato

Yao-Zhong Zhang

Zuguang Gu

Seiya Imoto

Affiliations

Soon will be listed here.

Abstract

Summary: Functional interpretation of biological entities such as differentially expressed genes is one of the fundamental analyses in bioinformatics. The task can be addressed by using biological pathway databases with enrichment analysis (EA). However, textual description of biological entities in public databases is less explored and integrated in existing tools and it has a potential to reveal new mechanisms. Here, we present a new R package biotextgraph for graphical summarization of omics' textual description data which enables assessment of functional similarities of the lists of biological entities. We illustrate application examples of annotating gene identifiers in addition to EA. The results suggest that the visualization based on words and inspection of biological entities with text can reveal a set of biologically meaningful terms that could not be obtained by using biological pathway databases alone. The results suggest the usefulness of the package in the routine analysis of omics-related data. The package also offers a web-based application for convenient querying.

Availability And Implementation: The package, documentation, and web server are available at: https://github.com/noriakis/biotextgraph.

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