Ian Harrow

BioCreative III interactive task: an overview

BackgroundThe BioCreative challenge evaluation is a community-wide effort for evaluating text mining and information extraction systems applied to the biological domain. The biocurator community, as an active user of biomedical literature, provides a diverse and engaged end user group for text mining tools. Earlier BioCreative challenges involved many text mining teams in developing basic capabilities relevant to biological curation, but they did not address the issues of system usage, insertion into the workflow and adoption by curators. Thus in BioCreative III (BC-III), the InterActive Task (IAT) was introduced to address the utility and usability of text mining tools for real-life biocuration tasks. To support the aims of the IAT in BC-III, involvement of both developers and end users was solicited, and the development of a user interface to address the tasks interactively was requested.ResultsA User Advisory Group (UAG) actively participated in the IAT design and assessment. The task focused on gene normalization (identifying gene mentions in the article and linking these genes to standard database identifiers), gene ranking based on the overall importance of each gene mentioned in the article, and gene-oriented document retrieval (identifying full text papers relevant to a selected gene). Six systems participated and all processed and displayed the same set of articles. The articles were selected based on content known to be problematic for curation, such as ambiguity of gene names, coverage of multiple genes and species, or introduction of a new gene name. Members of the UAG curated three articles for training and assessment purposes, and each member was assigned a system to review. A questionnaire related to the interface usability and task performance (as measured by precision and recall) was answered after systems were used to curate articles. Although the limited number of articles analyzed and users involved in the IAT experiment precluded rigorous quantitative analysis of the results, a qualitative analysis provided valuable insight into some of the problems encountered by users when using the systems. The overall assessment indicates that the system usability features appealed to most users, but the system performance was suboptimal (mainly due to low accuracy in gene normalization). Some of the issues included failure of species identification and gene name ambiguity in the gene normalization task leading to an extensive list of gene identifiers to review, which, in some cases, did not contain the relevant genes. The document retrieval suffered from the same shortfalls. The UAG favored achieving high performance (measured by precision and recall), but strongly recommended the addition of features that facilitate the identification of correct gene and its identifier, such as contextual information to assist in disambiguation.DiscussionThe IAT was an informative exercise that advanced the dialog between curators and developers and increased the appreciation of challenges faced by each group. A major conclusion was that the intended users should be actively involved in every phase of software development, and this will be strongly encouraged in future tasks. The IAT Task provides the first steps toward the definition of metrics and functional requirements that are necessary for designing a formal evaluation of interactive curation systems in the BioCreative IV challenge.

Metabolism of AF1 (KNEFIRF-NH2) in the nematode, Ascaris suum, by aminopeptidase, endopeptidase and deamidase enzymes.

We have studied the metabolism and inactivation of AF1 (KNEFIRF-NH2) by membranes prepared from the locomotory muscle of Ascaris suum. FIRF-NH2 and KNEFIRF were identified as three primary degradation products, resulting from the action of an endopeptidase, aminopeptidase and a deamidase, respectively. The endopeptidase resembled mammalian neprilysin (NEP, endopeptidase 24.11) in that the enzyme activity was inhibited by phosphoramidon and thiorphan and that it cleaved AF1 on the amino side of phenylalanine. The aminopeptidase activity was inhibited by amastatin and bestatin but not by puromycin. The deamidation of AF1 was inhibited by phenylmethylsulfonyl fluoride, p-chloromercuricphenylsulfonate and mercuric chloride, indicating that the deamidase enzyme is a serine protease with a requirement for a free thiol group for activity. AF1 (1 microM) induces an increase in tension and an increase in the frequency and amplitude of spontaneous contractions of an A. suum muscle strip. None of the aforementioned AF1 metabolites (2-20 microM) retained biological activity in this bioassay, indicating that the endopeptidase, aminopeptidase and deamidase have the potential to terminate the action of AF1 on locomotory muscle of A. suum.

Purification and properties of a membrane aminopeptidase from Ascaris suum muscle that degrades neuropeptides AF1 and AF2

We have identified on the membranes of the locomotory muscle of Ascaris suum an amastatin-sensitive aminopeptidase that hydrolyses the bioactive neuropeptides AF1 (KNEFIRF-NH2) and AF2 (KHEYLRF-NH2), by cleavage of the Lys1-Asn2 and Lys1-His2 peptide bonds, respectively. AF2 (1.2 nmol of HEYLRF-NH2 formed min[-1] (mg protein[-1])) was hydrolysed at a faster rate compared to AF1 (0.2 nmol of NEFIRF-NH2 formed min[-1] (mg protein[-1])). AF1 hydrolysis by the aminopeptidase was inhibited by the amastatin (IC50, 9.0 microM), leuhistin (IC50, 1.25 microM) but was insensitive to puromycin, indicating a similarity to mammalian aminopeptidase N. The enzyme was also inhibited by arphamenine B (IC50, 9.0 microM), (2S, 3R)-3-amino-2-hydroxy-4-(4-nitrophenyl)butanoyl-L-leucine (IC50, 8.0 microM), bestatin (IC50, 15.0 microM) and 1 mM 1-10 bis-phenanthroline. The detergent Triton X-100 solubilised enzyme had a pI of 5.0 and after 1000-fold purification by ion-exchange chromatography, appeared to have a Mr of around 240,000 by SDS-PAGE. The purified aminopeptidase had a Km of 534 microM for the hydrolysis of AF1 and cleaved Phe1 from FMRF-NH2, but was unable to hydrolyse DFMRF-NH2 or FDMRF-NH2. The aminopeptidase that we have described in this report might have a role in the extracellular metabolism and inactivation of neuropeptides acting on the locomotory muscle of A. suum.

Towards virtual knowledge broker services for semantic integration of life science literature and data sources.

Research in the life sciences requires ready access to primary data, derived information and relevant knowledge from a multitude of sources. Integration and interoperability of such resources are crucial for sharing content across research domains relevant to the life sciences. In this article we present a perspective review of data integration with emphasis on a semantics driven approach to data integration that pushes content into a shared infrastructure, reduces data redundancy and clarifies any inconsistencies. This enables much improved access to life science data from numerous primary sources. The Semantic Enrichment of the Scientific Literature (SESL) pilot project demonstrates feasibility for using already available open semantic web standards and technologies to integrate public and proprietary data resources, which span structured and unstructured content. This has been accomplished through a precompetitive consortium, which provides a cost effective approach for numerous stakeholders to work together to solve common problems.

Matching disease and phenotype ontologies in the ontology alignment evaluation initiative

BackgroundThe disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease.ResultsEleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results.ConclusionsFour systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype.