The Gene Ontology Consortium (GOC) is a community-based bioinformatics project that classifies gene product function through the use of structured controlled vocabularies. A fundamental application of the Gene Ontology (GO) is in the creation of gene product annotations, evidence-based associations between GO definitions and experimental or sequence-based analysis. Currently, the GOC disseminates 126 million annotations covering >374 000 species including all the kingdoms of life. This number includes two classes of GO annotations: those created manually by experienced biocurators reviewing the literature or by examination of biological data (1.1 million annotations covering 2226 species) and those generated computationally via automated methods. As manual annotations are often used to propagate functional predictions between related proteins within and between genomes, it is critical to provide accurate consistent manual annotations. Toward this goal, we present here the conventions defined by the GOC for the creation of manual annotation. This guide represents the best practices for manual annotation as established by the GOC project over the past 12 years. We hope this guide will encourage research communities to annotate gene products of their interest to enhance the corpus of GO annotations available to all.

/pdf/a-guide-to-best-practices-for-gene-ontology-go-manual-heen3gvhst.pdf

A guide to best practices for Gene Ontology (GO) manual annotation

Scientific publications are documentary representations of defeasible arguments, supported by data and repeatable methods. They are the essential mediating artifacts in the ecosystem of scientific communications. The institutional “goal” of science is publishing results. The linear document publication format, dating from 1665, has survived transition to the Web. Intractable publication volumes; the difficulty of verifying evidence; and observed problems in evidence and citation chains suggest a need for a web-friendly and machine-tractable model of scientific publications. This model should support: digital summarization, evidence examination, challenge, verification and remix, and incremental adoption. Such a model must be capable of expressing a broad spectrum of representational complexity, ranging from minimal to maximal forms. The micropublications semantic model of scientific argument and evidence provides these features. Micropublications support natural language statements; data; methods and materials specifications; discussion and commentary; challenge and disagreement; as well as allowing many kinds of statement formalization. The minimal form of a micropublication is a statement with its attribution. The maximal form is a statement with its complete supporting argument, consisting of all relevant evidence, interpretations, discussion and challenges brought forward in support of or opposition to it. Micropublications may be formalized and serialized in multiple ways, including in RDF. They may be added to publications as stand-off metadata. An OWL 2 vocabulary for micropublications is available at http://purl.org/mp
 . A discussion of this vocabulary along with RDF examples from the case studies, appears as OWL Vocabulary and RDF Examples in Additional file1. Micropublications, because they model evidence and allow qualified, nuanced assertions, can play essential roles in the scientific communications ecosystem in places where simpler, formalized and purely statement-based models, such as the nanopublications model, will not be sufficient. At the same time they will add significant value to, and are intentionally compatible with, statement-based formalizations. We suggest that micropublications, generated by useful software tools supporting such activities as writing, editing, reviewing, and discussion, will be of great value in improving the quality and tractability of biomedical communications.

/pdf/micropublications-a-semantic-model-for-claims-evidence-16bnwlzdmn.pdf

Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications

To support more effective biomedical information management, Semantic MEDLINE integrates document retrieval, advanced natural language processing, automatic summarization and visualization into a single Web portal. The application is intended to help manage the results of PubMed searches by condensing core semantic content in the citations retrieved. Output is presented as a connected graph of semantic relations, with links to the original MEDLINE citations. The ability to connect salient information across documents helps users keep up with the research literature and discover connections which might otherwise go unnoticed. Semantic MEDLINE can make an impact on biomedicine by supporting scientific discovery and the timely translation of insights from basic research into advances in clinical practice and patient care. Semantic MEDLINE is illustrated here with recent research on the clock genes.

https://skr3.nlm.nih.gov/SemMedDB/jsp/Rindflesch2011.pdf

Semantic MEDLINE: An advanced information management application for biomedicine

Fully automated text mining (TM) systems promote efficient literature searching, retrieval, and review but are not sufficient to produce ready-to-consume curated documents. These systems are not meant to replace biocurators, but instead to assist them in one or more literature curation steps. To do so, the user interface is an important aspect that needs to be considered for tool adoption. The BioCreative Interactive task (IAT) is a track designed for exploring user-system interactions, promoting development of useful TM tools, and providing a communication channel between the biocuration and the TM communities. In BioCreative V, the IAT track followed a format similar to previous interactive tracks, where the utility and usability of TM tools, as well as the generation of use cases, have been the focal points. The proposed curation tasks are user-centric and formally evaluated by biocurators. In BioCreative V IAT, seven TM systems and 43 biocurators participated. Two levels of user participation were offered to broaden curator involvement and obtain more feedback on usability aspects. The full level participation involved training on the system, curation of a set of documents with and without TM assistance, tracking of time-on-task, and completion of a user survey. The partial level participation was designed to focus on usability aspects of the interface and not the performance per se. In this case, biocurators navigated the system by performing pre-designed tasks and then were asked whether they were able to achieve the task and the level of difficulty in completing the task. In this manuscript, we describe the development of the interactive task, from planning to execution and discuss major findings for the systems tested.

/pdf/overview-of-the-interactive-task-in-biocreative-v-1qk0t2htb9.pdf

Overview of the interactive task in BioCreative V

Manual curation of data from the biomedical literature is a rate-limiting factor for many expert curated databases. Despite the continuing advances in biomedical text mining and the pressing needs of biocurators for better tools, few existing text-mining tools have been successfully integrated into production literature curation systems such as those used by the expert curated databases. To close this gap and better understand all aspects of literature curation, we invited submissions of written descriptions of curation workflows from expert curated databases for the BioCreative 2012 Workshop Track II. We received seven qualified contributions, primarily from model organism databases. Based on these descriptions, we identified commonalities and differences across the workflows, the common ontologies and controlled vocabularies used and the current and desired uses of text mining for biocuration. Compared to a survey done in 2009, our 2012 results show that many more databases are now using text mining in parts of their curation workflows. In addition, the workshop participants identified text-mining aids for finding gene names and symbols (gene indexing), prioritization of documents for curation (document triage) and ontology concept assignment as those most desired by the biocurators.

Database URL: http://www.biocreative.org/tasks/bc-workshop-2012/workflow/

Biocuration workflows and text mining: overview of the BioCreative 2012 Workshop Track II

BioCreative: Critical Assessment of Information Extraction in Biology is an international community-wide effort for evaluating text mining and information extraction systems applied to the biological domain (http://www.biocreative.org/). The Challenge Evaluations and the accompanying BioCreative Workshops bring together the text mining and biology communities to drive the development of text mining systems that can be integrated into the biocuration workflow and the knowledge discovery process. To address the current barriers in using text mining in biology, BioCreative has further been conducting user requirement analysis, user-based evaluations and fostering standard development for text mining tool re-use and integration. This DATABASE virtual issue captures the major results from the BioCreative-2012 Workshop on Interactive Text Mining in the Biocuration Workflow and is the fifth special issue devoted to BioCreative.

BioCreative-2012 virtual issue.

This volume contains the full papers accepted for presentation at the BioLINK 2005 meeting. This workshop represents the first joint Association for Computational Linguistics (ACL)/Intelligent Systems for Molecular Biology (ISMB) meeting. Each organization has held a workshop in this area for the past three to four years; this is the first meeting sponsored jointly by the two parent organizations. In bringing these two groups together, we have also melded two different traditions of distribution. The ISMB tradition has been focussed on invited talks and "short papers" describing works in progress. The ACL tradition has focussed on rigorously peer-reviewed full papers describing compeleted work. This workshop features works in the three categories of "full paper," "short paper," and poster submissions. Submissions in all three categories underwent an ACL-style peer review process.

Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics

This session is focused on text mining applications that link information from the biomedical literature to the growing array of struc ured resources available to researchers, such as protein databases (e.g., UniPr ot, PDB, PIR), model organism databases (e.g., FlyBase, MGI, SGD), ontologies (th e Gene Ontology, as well as the growing number of ontologies in OBO – Open Biologic al Ontologies), and nomenclatures (HUGO, HUPO). To achieve this focus, there was an explicit requirement that submissions include both a text mi ning component and a mapping between at least two publicly available data source s. There were twenty papers submitted to this session, with nine papers accepte d (7 for oral presentation).

/pdf/linking-biomedical-information-through-text-mining-session-1vv3qyqqli.pdf

Linking biomedical information through text mining: session introduction

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BioCreative-2012 virtual issue.

Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics

Linking biomedical information through text mining: session introduction