The Ontology for Parasite Lifecycle (OPL): towards a consistent vocabulary of lifecycle stages in parasitic organisms.

BACKGROUND: Genome sequencing of many eukaryotic pathogens and the volume of data available on public resources have created a clear requirement for a consistent vocabulary to describe the range of developmental forms of parasites. Consistent labeling of experimental data and external data, in databases and the literature, is essential for integration, cross database comparison, and knowledge discovery. The primary objective of this work was to develop a dynamic and controlled vocabulary that can be used for various parasites. The paper describes the Ontology for Parasite Lifecycle (OPL) and discusses its application in parasite research. RESULTS: The OPL is based on the Basic Formal Ontology (BFO) and follows the rules set by the OBO Foundry consortium. The first version of the OPL models complex life cycle stage details of a range of parasites, such as Trypanosoma sp., Leishmaniasp., Plasmodium sp., and Shicstosoma sp. In addition, the ontology also models necessary contextual details, such as host information, vector information, and anatomical locations. OPL is primarily designed to serve as a reference ontology for parasite life cycle stages that can be used for database annotation purposes and in the lab for data integration or information retrieval as exemplified in the application section below. CONCLUSION: OPL is freely available at http://purl.obolibrary.org/obo/opl.owl and has been submitted to the BioPortal site of NCBO and to the OBO Foundry. We believe that database and phenotype annotations using OPL will help run fundamental queries on databases to know more about gene functions and to find intervention targets for various parasites. The OPL is under continuous development and new parasites and/or terms are being added.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

A unified framework for managing provenance information in translational research

<p>Abstract</p> <p>Background</p> <p>A critical aspect of the NIH <it>Translational Research </it>roadmap, which seeks to accelerate the delivery of "bench-side" discoveries to patient's "bedside," is the management of the <it>provenance </it>metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researchers to verify the quality of data, reproduce scientific results published in peer-reviewed literature, validate scientific process, and associate trust value with data and results. Traditional approaches to provenance management have focused on only partial sections of the translational research life cycle and they do not incorporate "domain semantics", which is essential to support domain-specific querying and analysis by scientists.</p> <p>Results</p> <p>We identify a common set of challenges in managing provenance information across the <it>pre-publication </it>and <it>post-publication </it>phases of data in the translational research lifecycle. We define the semantic provenance framework (SPF), underpinned by the Provenir upper-level provenance ontology, to address these challenges in the four stages of provenance metadata:</p> <p>(a) Provenance <b>collection </b>- during data generation</p> <p>(b) Provenance <b>representation </b>- to support interoperability, reasoning, and incorporate domain semantics</p> <p>(c) Provenance <b>storage </b>and <b>propagation </b>- to allow efficient storage and seamless propagation of provenance as the data is transferred across applications</p> <p>(d) Provenance <b>query </b>- to support queries with increasing complexity over large data size and also support knowledge discovery applications</p> <p>We apply the SPF to two exemplar translational research projects, namely the Semantic Problem Solving Environment for <it>Trypanosoma cruzi </it>(<it>T.cruzi </it>SPSE) and the Biomedical Knowledge Repository (BKR) project, to demonstrate its effectiveness.</p> <p>Conclusions</p> <p>The SPF provides a unified framework to effectively manage provenance of translational research data during pre and post-publication phases. This framework is underpinned by an upper-level provenance ontology called Provenir that is extended to create domain-specific provenance ontologies to facilitate provenance interoperability, seamless propagation of provenance, automated querying, and analysis.</p

A Semantic Problem Solving Environment for Integrative Parasite Research: Identification of Intervention Targets for Trypanosoma cruzi

Effective research in parasite biology requires analyzing experimental lab data in the context of constantly expanding public data resources. Integrating lab data with public resources is particularly difficult for biologists who may not possess significant computational skills to acquire and process heterogeneous data stored at different locations. Therefore, we develop a semantic problem solving environment (SPSE) that allows parasitologists to query their lab data integrated with public resources using ontologies. An ontology specifies a common vocabulary and formal relationships among the terms that describe an organism, and experimental data and processes in this case. SPSE supports capturing and querying provenance information, which is metadata on the experimental processes and data recorded for reproducibility, and includes a visual query-processing tool to formulate complex queries without learning the query language syntax. We demonstrate the significance of SPSE in identifying gene knockout targets for T. cruzi. The overall goal of SPSE is to help researchers discover new or existing knowledge that is implicitly present in the data but not always easily detected. Results demonstrate improved usefulness of SPSE over existing lab systems and approaches, and support for complex query design that is otherwise difficult to achieve without the knowledge of query language syntax

Provenance Management in Parasite Research

The objective of this research is to create a semantic problem solving environment (PSE) for human parasite Trypanosoma cruzi. As a part of the PSE, we are trying to manage provenance of the experiment data as it is generated. It requires to capture the provenance which is often collected through web forms used by biologists to input the information about experiments they conduct. We have created Parasite Experiment Ontology (PEO) that represents provenance information used in the project. We have modified the back end which processes the data gathered from biologists, generates RDF triples and serializes them into the triple store. Moreover, it is necessary to assert that RDF triples conform to the PEO schema. This work allows us to capture provenance of experiments conducted at Tarleton Research Group as a part of this project

A Unified Framework fro Managing Provenance Information in Translational Research

Background A critical aspect of the NIH Translational Research roadmap, which seeks to accelerate the delivery of bench-side discoveries to patient\u27s bedside, is the management of the provenance metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researchers to verify the quality of data, reproduce scientific results published in peer-reviewed literature, validate scientific process, and associate trust value with data and results. Traditional approaches to provenance management have focused on only partial sections of the translational research life cycle and they do not incorporate domain semantics , which is essential to support domain-specific querying and analysis by scientists. Results We identify a common set of challenges in managing provenance information across the pre-publication and post-publication phases of data in the translational research lifecycle. We define the semantic provenance framework (SPF), underpinned by the Provenir upper-level provenance ontology, to address these challenges in the four stages of provenance metadata: (a) Provenance collection - during data generation (b) Provenance representation - to support interoperability, reasoning, and incorporate domain semantics (c) Provenance storage and propagation - to allow efficient storage and seamless propagation of provenance as the data is transferred across applications (d) Provenance query - to support queries with increasing complexity over large data size and also support knowledge discovery applications We apply the SPF to two exemplar translational research projects, namely the Semantic Problem Solving Environment for Trypanosoma cruzi (T.cruzi SPSE) and the Biomedical Knowledge Repository (BKR) project, to demonstrate its effectiveness. Conclusions The SPF provides a unified framework to effectively manage provenance of translational research data during pre and post-publication phases. This framework is underpinned by an upper-level provenance ontology called Provenir that is extended to create domain-specific provenance ontologies to facilitate provenance interoperability, seamless propagation of provenance, automated querying, and analysis

Association of System-Level Factors with Secondary Overtriage in Trauma Patients

Importance: Studies show that secondary overtriage (SO) contributes significantly to the economic burden of injured patients; thus, the association of SO with use of the trauma system has been examined. However, the association of the underlying trauma system design with such overtriage has yet to be evaluated. Objectives: To evaluate whether the distribution of trauma centers in a statewide trauma system is associated with SO and to identify clinical and demographic factors that may lead to SO. Design, Setting, and Participants: A retrospective cohort study was performed using 2008-2012 data from the Ohio Trauma and Emergency Medical Services registries. All patients taken to level III or nontrauma centers from the scene of the injury with an Injury Severity Score less than 15 and discharged alive were included. Among these patients, those with SO were identified as those who were subsequently transferred to a level I or II trauma center, had no surgical intervention, and were discharged alive within 48 hours of admission. The SO group was analyzed descriptively. Multiple logistic regression was used to identify system-level factors associated with SO. Statistical analysis was performed from August 1, 2017, to January 31, 2018. Main Outcomes and Measures: The primary outcome was the occurrence of SO. Results: Of 34494 trauma patients able to be matched in the 2 registries, 7881 (22.9%) met the inclusion criteria, of whom 965 (12.2%) had SO. The median age in the SO group was 40 years (interquartile range, 26-55 years), with 299 women and 666 men. After adjusting for age, sex, comorbidities, injury type, and insurance status, the study found that system-level factors (number of level I or II trauma centers in the region [\u3e1]) were significantly associated with SO (adjusted odds ratio, 1.98; 95% CI, 1.64-2.38; P \u3c.001; area under the curve, 0.89). The reasons for choice of destination by emergency medical services (specifically, choosing the closest facility: adjusted odds ratio, 1.65; 95% CI, 1.37-1.98; P \u3c.001) and use of a field trauma triage protocol (adjusted odds ratio, 2.21; 95% CI, 1.70-2.87; P \u3c.001), significantly increased the likelihood of SO. Conclusions and Relevance: This study\u27s findings suggest that the distribution of major trauma centers in the region is significantly associated with SO. Subsequent investigation to identify the optimal number and distribution of trauma centers may therefore be critical. Specific outreach and collaboration of level III trauma centers and nontrauma centers with level I and II trauma centers, along with the use of telemedicine, may provide further guidance to level III trauma centers and nontrauma centers on when to transfer injured patients

Association of System-Level Factors with Secondary Overtriage in Trauma Patients

Importance: Studies show that secondary overtriage (SO) contributes significantly to the economic burden of injured patients; thus, the association of SO with use of the trauma system has been examined. However, the association of the underlying trauma system design with such overtriage has yet to be evaluated. Objectives: To evaluate whether the distribution of trauma centers in a statewide trauma system is associated with SO and to identify clinical and demographic factors that may lead to SO. Design, Setting, and Participants: A retrospective cohort study was performed using 2008-2012 data from the Ohio Trauma and Emergency Medical Services registries. All patients taken to level III or nontrauma centers from the scene of the injury with an Injury Severity Score less than 15 and discharged alive were included. Among these patients, those with SO were identified as those who were subsequently transferred to a level I or II trauma center, had no surgical intervention, and were discharged alive within 48 hours of admission. The SO group was analyzed descriptively. Multiple logistic regression was used to identify system-level factors associated with SO. Statistical analysis was performed from August 1, 2017, to January 31, 2018. Main Outcomes and Measures: The primary outcome was the occurrence of SO. Results: Of 34494 trauma patients able to be matched in the 2 registries, 7881 (22.9%) met the inclusion criteria, of whom 965 (12.2%) had SO. The median age in the SO group was 40 years (interquartile range, 26-55 years), with 299 women and 666 men. After adjusting for age, sex, comorbidities, injury type, and insurance status, the study found that system-level factors (number of level I or II trauma centers in the region [\u3e1]) were significantly associated with SO (adjusted odds ratio, 1.98; 95% CI, 1.64-2.38; P \u3c.001; area under the curve, 0.89). The reasons for choice of destination by emergency medical services (specifically, choosing the closest facility: adjusted odds ratio, 1.65; 95% CI, 1.37-1.98; P \u3c.001) and use of a field trauma triage protocol (adjusted odds ratio, 2.21; 95% CI, 1.70-2.87; P \u3c.001), significantly increased the likelihood of SO. Conclusions and Relevance: This study\u27s findings suggest that the distribution of major trauma centers in the region is significantly associated with SO. Subsequent investigation to identify the optimal number and distribution of trauma centers may therefore be critical. Specific outreach and collaboration of level III trauma centers and nontrauma centers with level I and II trauma centers, along with the use of telemedicine, may provide further guidance to level III trauma centers and nontrauma centers on when to transfer injured patients

Kino: A Generic Document Management System for Biologists using SA-REST and Faceted Search

Document management has become an important consideration for the scientific community over the last decade. Human knowledge is central to many scientific domains, thus it is not possible to completely automate the document management process. Managing scientific documents require a semi-automatic approach to overcome issues of large volume, yet support the human participation in the process. In this paper we present Kino, a set of tools that streamline the document management process in life science domains. Kino is integrated with National Center for Biomedical Ontology (NCBO), providing scientists access to quality domain models. Annotated documents are indexed using a faceted indexing and search engine that provides fine grained search capabilities to the scientists. We present two use cases that highlight the pain points in managing scientific literature and also include an empirical evaluation

Kino: A Generic Document Management System for Biologists using SA-REST and Faceted Search

Document management has become an important consideration for the scientific community over the last decade. Human knowledge is central to many scientific domains, thus it is not possible to completely automate the document management process. Managing scientific documents require a semi-automatic approach to overcome issues of large volume, yet support the human participation in the process. In this paper we present Kino, a set of tools that streamline the document management process in life science domains. Kino is integrated with National Center for Biomedical Ontology (NCBO), providing scientists access to quality domain models. Annotated documents are indexed using a faceted indexing and search engine that provides fine grained search capabilities to the scientists. We present two use cases that highlight the pain points in managing scientific literature and also include an empirical evaluation

Provenance Management in Parasite Research

The objective of this research is to create a semantic problem solving environment (PSE) for human parasite Trypanosoma cruzi. As a part of the PSE, we are trying to manage provenance of the experiment data as it is generated. It requires to capture the provenance which is often collected through web forms used by biologists to input the information about experiments they conduct. We have created Parasite Experiment Ontology (PEO) that represents provenance information used in the project. We have modified the back end which processes the data gathered from biologists, generates RDF triples and serializes them into the triple store. Moreover, it is necessary to assert that RDF triples conform to the PEO schema. This work allows us to capture provenance of experiments conducted at Tarleton Research Group as a part of this project