Literature DB >> 18999231

Using an integrated ontology and information model for querying and reasoning about phenotypes: The case of autism.

Samson W Tu1, Samson Tu, Lakshika Tennakoon, Martin O'Connor, Martin Connor, Ravi Shankar, Amar Das.   

Abstract

The Open Biomedical Ontologies (OBO) Foundry is a coordinated community-wide effort to develop ontologies that support the annotation and integration of scientific data. In work supported by the National Database of Autism Research (NDAR), we are developing an ontology of autism that extends the ontologies available in the OBO Foundry. We undertook a systematic literature review to identify domain terms and relationships relevant to autism phenotypes. To enable user queries and inferences about such phenotypes using data in the NDAR repository, we augmented the domain ontology with an information model. In this paper, we show how our approach, using a combination of description logic and rule-based reasoning, enables high-level phenotypic abstractions to be inferred from subject-specific data. Our integrated domain ontologyinformation model approach allows scientific data repositories to be augmented with rule-based abstractions that facilitate the ability of researchers to undertake data analysis.

Entities:  

Mesh:

Year:  2008        PMID: 18999231      PMCID: PMC2655950     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  7 in total

1.  Biodynamic ontology: applying BFO in the biomedical domain.

Authors:  Pierre Grenon; Barry Smith; Louis Goldberg
Journal:  Stud Health Technol Inform       Date:  2004

Review 2.  Data integration and genomic medicine.

Authors:  Brenton Louie; Peter Mork; Fernando Martin-Sanchez; Alon Halevy; Peter Tarczy-Hornoch
Journal:  J Biomed Inform       Date:  2006-03-09       Impact factor: 6.317

3.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration.

Authors:  Barry Smith; Michael Ashburner; Cornelius Rosse; Jonathan Bard; William Bug; Werner Ceusters; Louis J Goldberg; Karen Eilbeck; Amelia Ireland; Christopher J Mungall; Neocles Leontis; Philippe Rocca-Serra; Alan Ruttenberg; Susanna-Assunta Sansone; Richard H Scheuermann; Nigam Shah; Patricia L Whetzel; Suzanna Lewis
Journal:  Nat Biotechnol       Date:  2007-11       Impact factor: 54.908

4.  Using the autism diagnostic interview--revised to increase phenotypic homogeneity in genetic studies of autism.

Authors:  Vanessa Hus; Andrew Pickles; Edwin H Cook; Susan Risi; Catherine Lord
Journal:  Biol Psychiatry       Date:  2007-02-15       Impact factor: 13.382

5.  The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism.

Authors:  C Lord; S Risi; L Lambrecht; E H Cook; B L Leventhal; P C DiLavore; A Pickles; M Rutter
Journal:  J Autism Dev Disord       Date:  2000-06

6.  A public health collaboration for the surveillance of autism spectrum disorders.

Authors:  Catherine E Rice; Jon Baio; Kim Van Naarden Braun; Nancy Doernberg; F John Meaney; Russell S Kirby
Journal:  Paediatr Perinat Epidemiol       Date:  2007-03       Impact factor: 3.980

7.  Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders.

Authors:  C Lord; M Rutter; A Le Couteur
Journal:  J Autism Dev Disord       Date:  1994-10
  7 in total
  9 in total

1.  Evaluation of semantic-based information retrieval methods in the autism phenotype domain.

Authors:  Saeed Hassanpour; Martin J O'Connor; Amar K Das
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  NeuroLOG: sharing neuroimaging data using an ontology-based federated approach.

Authors:  Bernard Gibaud; Gilles Kassel; Michel Dojat; Bénédicte Batrancourt; Franck Michel; Alban Gaignard; Johan Montagnat
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

3.  Building an ontology for pressure ulcer risk assessment to allow data sharing and comparisons across hospitals.

Authors:  Hyeoneui Kim; Jeeyae Choi; Lelanie Secalag; Laura Dibsie; Aziz Boxwala; Lucila Ohno-Machado
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

4.  An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data.

Authors:  Omri Mugzach; Mor Peleg; Steven C Bagley; Stephen J Guter; Edwin H Cook; Russ B Altman
Journal:  J Biomed Inform       Date:  2015-07-04       Impact factor: 6.317

Review 5.  Text mining applications in psychiatry: a systematic literature review.

Authors:  Adeline Abbe; Cyril Grouin; Pierre Zweigenbaum; Bruno Falissard
Journal:  Int J Methods Psychiatr Res       Date:  2015-07-17       Impact factor: 4.035

6.  Modeling the autism spectrum disorder phenotype.

Authors:  Alexa T McCray; Philip Trevvett; H Robert Frost
Journal:  Neuroinformatics       Date:  2014-04

Review 7.  Data-Driven Diagnostics and the Potential of Mobile Artificial Intelligence for Digital Therapeutic Phenotyping in Computational Psychiatry.

Authors:  Peter Washington; Natalie Park; Parishkrita Srivastava; Catalin Voss; Aaron Kline; Maya Varma; Qandeel Tariq; Haik Kalantarian; Jessey Schwartz; Ritik Patnaik; Brianna Chrisman; Nathaniel Stockham; Kelley Paskov; Nick Haber; Dennis P Wall
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2019-12-13

8.  Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of Cerebrotendinous xanthomatosis.

Authors:  María Taboada; Diego Martínez; Belén Pilo; Adriano Jiménez-Escrig; Peter N Robinson; María J Sobrido
Journal:  BMC Med Inform Decis Mak       Date:  2012-07-31       Impact factor: 2.796

9.  A semantic-based method for extracting concept definitions from scientific publications: evaluation in the autism phenotype domain.

Authors:  Saeed Hassanpour; Martin J O'Connor; Amar K Das
Journal:  J Biomed Semantics       Date:  2013-08-12
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.