PubServer: literature searches by homology

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Protein entries in databases like NCBI Entrez contain publication data, but the scope varies widely.
• Manual collection and analysis of publications for homologous proteins are time-consuming and labor-intensive.
• Automated tools are needed to efficiently manage and interpret literature associated with protein families.

Purpose of the Study:

• To introduce PubServer, a tool for automated collection, filtering, and analysis of publications related to homologous proteins.
• To facilitate functional annotation of novel and well-studied protein families by streamlining literature review.
• To provide researchers with an efficient method for identifying relevant scientific literature.

Main Methods:

• PubServer utilizes PSI-Blast to identify homologous proteins and retrieves associated literature references from databases.
• It filters publications based on user-adjustable criteria to remove irrelevant content.
• The tool generates vocabulary statistics from titles, abstracts, and MeSH terms to highlight common themes.

Main Results:

• PubServer automates the retrieval and filtering of publications for homologous protein groups.
• It provides vocabulary statistics to help identify key themes within the collected literature.
• The server presents results interactively, allowing for re-filtering and varied data presentation.

Conclusions:

• PubServer offers an automated solution for managing and analyzing scientific publications relevant to homologous proteins.
• The tool enhances the efficiency of functional protein annotation and literature review.
• It empowers researchers to quickly identify common themes and relevant information within large sets of scientific literature.