Triage by ranking to support the curation of protein interactions

Abstract

Today, molecular biology databases are the cornerstone of knowledge sharing for life and health sciences. The curation and maintenance of these resources are labour intensive. Although text mining is gaining impetus among curators, its integration in curation workflow has not yet been widely adopted. The Swiss Institute of Bioinformatics Text Mining and CALIPHO groups joined forces to design a new curation support system named nextA5. In this report, we explore the integration of novel triage services to support the curation of two types of biological data: protein–protein interactions (PPIs) and post-translational modifications (PTMs). The recognition of PPIs and PTMs poses a special challenge, as it not only requires the identification of biological entities (proteins or residues), but also that of particular relationships (e.g. binding or position). These relationships cannot be described with onto-terminological descriptors such as the Gene Ontology for molecular functions, which makes the triage task more challenging. Prioritizing papers for these tasks thus requires the development of different approaches. In this report, we propose a new method to prioritize articles containing information specific to PPIs and PTMs. The new resources (RESTful APIs, semantically annotated MEDLINE library) enrich the neXtA5 platform. We tuned the article prioritization model on a set of 100 proteins previously annotated by the CALIPHO group. The effectiveness of the triage service was tested with a dataset of 200 annotated proteins. We defined two sets of descriptors to support automatic triage: the first set to enrich for papers with PPI data, and the second for PTMs. All occurrences of these descriptors were marked-up in MEDLINE and indexed, thus constituting a semantically annotated version of MEDLINE. These annotations were then used to estimate the relevance of a particular article with respect to the chosen annotation type. This relevance score was combined with a local vector-space search engine to generate a ranked list of PMIDs. We also evaluated a query refinement strategy, which adds specific keywords (such as ‘binds’ or ‘interacts’) to the original query. Compared to PubMed, the search effectiveness of the nextA5 triage service is improved by 190% for the prioritization of papers with PPIs information and by 260% for papers with PTMs information. Combining advanced retrieval and query refinement strategies with automatically enriched MEDLINE contents is effective to improve triage in complex curation tasks such as the curation of protein PPIs and PTMs. Database URL: http://candy.hesge.ch/nextA5

ECO, the Evidence & Conclusion Ontology: community standard for evidence information

“…For manual curation of protein function and phenotypes, neXtProt has adopted ECO as one of its standardization resources. Recently, neXtA 5 , a semi-automatic annotation application developed through a collaboration between the Swiss Institute of Bioinformatics Text Mining and CALIPHO groups, predicts ECO classes as part of the data extraction step (17,18). We have added nearly 130 new evidence classes to support their curation needs.…”

Overview of the BioCreative VI text-mining services for Kinome Curation Track

“…The neXtProt database ( 2–3 ) aims at representing the current state of knowledge on the human proteome. Human curators play a key role in defining the content and ensuring the quality of these reference databases ( 4–5 ). Their mission consists of continuously collecting, verifying and annotating the literature.…”

“…Most curation methods are based on manual approaches, which produce the most accurate knowledge but are also time-consuming ( 6 ). At the very first stage of the process, one study ( 7 ) estimates that ∼7% of the curation time is assigned to the rejection of papers, while another study ( 4 ) assumes that 15% of curators’ time is spent on selecting relevant articles. Triage systems that retrieve, filter and/or prioritize the literature can hence help curators focus on articles appropriate for curation.…”

Accelerating annotation of articles via automated approaches: evaluation of the neXtA5 curation-support tool by neXtProt

“…We have developed an automatic article-processing tool that addresses our specific curation needs, neXtA 5 (22, 23). neXtA 5 provides a search engine coupled with an annotation system, directly integrated into the workflow of curators.…”

“…In previous work, we have optimized the ranking algorithm of neXtA 5 for the triage task. The tool exhibits significant improvements of 191–261% compared to PubMed (22, 23). The present article describes the testing and evaluation of neXtA 5 by expert curators.…”