In this article, we will explore the topic of Eukaryotic Linear Motif resource in depth, analyzing its impact on today's society and its relevance in different contexts. Since its appearance, Eukaryotic Linear Motif resource has generated a constant debate among experts and the general population, who seek to understand its importance in daily life. Over the years, Eukaryotic Linear Motif resource has evolved and taken on new meanings, leading to increased interest from researchers and scholars on the subject. In this sense, this article aims to provide a comprehensive view of Eukaryotic Linear Motif resource, addressing different approaches and providing valuable information for those interested in expanding their knowledge on this topic.
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Description | eukaryotic linear motifs. |
Contact | |
Authors | Holger Dinkel Toby Gibson |
Primary citation | Dinkel & al. (2012)[1] |
Release date | 2011 |
Access | |
Website | elm |
The Eukaryotic Linear Motif (ELM) resource is a computational biology resource (developed at the European Molecular Biology Laboratory (EMBL)) for investigating short linear motifs (SLiMs) in eukaryotic proteins.[2][3] It is currently the largest collection of linear motif classes with annotated and experimentally validated linear motif instances.
Linear motifs are specified as patterns using regular expression rules. These expressions are used in the ELM prediction pipeline which detects putative motif instances in protein sequences. To improve the predictive power, context-based rules and logical filters are being developed and applied to reduce the amount of false positives matches.
As of 2010 ELM contained 146 different motifs that annotate more than 1300 experimentally determined instances within proteins.[3] The current version of the ELM server provides filtering by cell compartment, phylogeny, globular domain clash (using the SMART/Pfam databases) and structure.[4] In addition, both the known ELM instances and any positionally conserved matches in sequences similar to ELM instance sequences are identified and displayed.