ELM 2016--data update and new functionality of the eukaryotic linear motif resource

Area of Science:

• Bioinformatics
• Molecular Biology
• Proteomics

Background:

• Short linear motifs (SLiMs) are crucial for protein interactions and regulation.
• Databases like the Eukaryotic Linear Motif (ELM) resource are essential for cataloging these motifs.
• Manual curation ensures the accuracy and reliability of motif data.

Purpose of the Study:

• To present the latest updates and improvements to the Eukaryotic Linear Motif (ELM) resource.
• To highlight the expanded content and enhanced usability of the ELM database.
• To provide researchers with an updated, comprehensive resource for SLiMs.

Main Methods:

• Manual curation of scientific literature to identify and validate SLiMs.
• Inclusion of new motif classes and instances based on experimental evidence.
• Improvements to the web interface for better data accessibility and searchability.

Main Results:

• The ELM 2016 database includes over 240 motif classes and more than 2700 experimentally validated instances.
• Data has been curated from over 2400 scientific publications.
• Enhanced web interface offers individually searchable pages and downloadable data in various formats.

Conclusions:

• The updated ELM resource provides a significantly expanded and more accessible collection of SLiMs.
• This resource supports research in molecular biology, proteomics, and drug discovery.
• Continued manual curation ensures the high quality and relevance of the ELM database.