The articles.ELM resource: simplifying access to protein linear motif literature by annotation, text-mining and classification.

N Palopoli,J A Iserte,L B Chemes,G Parisi,T J Gibson,C Marino-Buslje,N E Davey

doi:10.1093/database/baaa040

Abstract

Modern biology produces data at a staggering rate. Yet, much of these biological data is still isolated in the text, figures, tables and supplementary materials of articles. As a result, biological information created at great expense is significantly underutilised. The protein motif biology field does not have sufficient resources to curate the corpus of motif-related literature and, to date, only a fraction of the available articles have been curated. In this study, we develop a set of tools and a web resource, ‘articles.ELM’, to rapidly identify the motif literature articles pertinent to a researcher’s interest. At the core of the resource is a manually curated set of about 8000 motif-related articles. These articles are automatically annotated with a range of relevant biological data allowing in-depth search functionality. Machine-learning article classification is used to group articles based on their similarity to manually curated motif classes in the Eukaryotic Linear Motif resource. Articles can also be manually classified within the resource. The ‘articles.ELM’ resource permits the rapid and accurate discovery of relevant motif articles thereby improving the visibility of motif literature and simplifying the recovery of valuable biological insights sequestered within scientific articles. Consequently, this web resource removes a critical bottleneck in scientific productivity for the motif biology field. Database URL: http://slim.icr.ac.uk/articles/

Highlights

The first definition of a short linear motif was coined in 1990 in an announcement for a Trends in Biochemical Sciences article series titled ‘Protein sequence motifs involved in recognition and targeting: a new series’ [5]
The ‘articles.Eukaryotic Linear Motif (ELM) literature dataset’ is a set of articles manually collected over the past decade for future curation in the ELM resource [7]
The articles.ELM classifier is a text-mining tool to classify putative motif articles based on their similarity to these manually classified groups of articles in the ELM resource [7]

Summary

Introduction

The first definition of a short linear motif ( known as a SLiM, MoRF or miniMotif) was coined in 1990 in an announcement for a Trends in Biochemical Sciences article series titled ‘Protein sequence motifs involved in recognition and targeting: a new series’ [5]. Only a handful of SLiM-related articles had been published and less than 10 motif classes had been characterized, including the nuclear localization signal (NLS), the integrinbinding RGD motif and the KDEL endoplasmic reticulum retrieval motif [6,9,10]. The definition included many of the key attributes of SLiMs such as their short length, physicochemical degeneracy and absence of tertiary structure [3]. Almost 30 years later, our understanding of SLiMs has exploded, revealing a central role in all aspects of cell regulation [7,14,17]. The motif literature provides an invaluable record of the complex decision-making taking place in the higher eukaryotic cell [15,16]

Methods

Results

Conclusion