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Jennifer Fostel

dblp:88/3348 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2006
0000-0001-5858-4393ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 80% Computational science and engineering · 20%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
data integration
0.112006
Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application · Bioinform. 2006
Computational science and engineering › scientific data management
data standards
0.112006
The MGED Ontology: a resource for semantics-based description of microarray experiments · Bioinform. 2006
Bioinformatics and computational biology › ontology
ontology development
0.112006
The MGED Ontology: a resource for semantics-based description of microarray experiments · Bioinform. 2006
Bioinformatics and computational biology
systems biology
0.112006
Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application · Bioinform. 2006

Methods — techniques the papers use, named apart from their topics

ontology engineering · 0.1object modeling · 0.1data standardization · 0.1
YearPublicationVenuePosition
2006 The MGED Ontology: a resource for semantics-based description of microarray experiments
abstract
MOTIVATION: The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. RESULTS: Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. AVAILABILITY: The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Patricia L. Whetzel, Helen E. Parkinson, Helen C. Causton, Liju Fan, Jennifer Fostel, Gilberto Fragoso, Laurence Game, Mervi Heiskanen, Norman Morrison, Philippe Rocca-Serra, Susanna-Assunta Sansone, Chris F. Taylor, Joseph White, Christian J. Stoeckert Jr.
Bioinform.5
2006 Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application
abstract
MOTIVATION: The CEBS data repository is being developed to promote a systems biology approach to understand the biological effects of environmental stressors. CEBS will house data from multiple gene expression platforms (transcriptomics), protein expression and protein-protein interaction (proteomics), and changes in low molecular weight metabolite levels (metabolomics) aligned by their detailed toxicological context. The system will accommodate extensive complex querying in a user-friendly manner. CEBS will store toxicological contexts including the study design details, treatment protocols, animal characteristics and conventional toxicological endpoints such as histopathology findings and clinical chemistry measures. All of these data types can be integrated in a seamless fashion to enable data query and analysis in a biologically meaningful manner. RESULTS: An object model, the SysBio-OM (Xirasagar et al., 2004) has been designed to facilitate the integration of microarray gene expression, proteomics and metabolomics data in the CEBS database system. We now report SysTox-OM as an open source systems toxicology model designed to integrate toxicological context into gene expression experiments. The SysTox-OM model is comprehensive and leverages other open source efforts, namely, the Standard for Exchange of Nonclinical Data (http://www.cdisc.org/models/send/v2/index.html) which is a data standard for capturing toxicological information for animal studies and Clinical Data Interchange Standards Consortium (http://www.cdisc.org/models/sdtm/index.html) that serves as a standard for the exchange of clinical data. Such standardization increases the accuracy of data mining, interpretation and exchange. The open source SysTox-OM model, which can be implemented on various software platforms, is presented here. AVAILABILITY: A universal modeling language (UML) depiction of the entire SysTox-OM is available at http://cebs.niehs.nih.gov and the Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. Currently, the public toxicological data in CEBS can be queried via a web application based on the SysTox-OM at http://cebs.niehs.nih.gov CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Sandhya Xirasagar, Scott F. Gustafson, Cheng-Cheng Huang, Qinyan Pan, Jennifer Fostel, Paul Boyer, B. Alex Merrick, Kenneth B. Tomer, Denny D. Chan, Kenneth J. Yost III, Danielle Choi, Nianqing Xiao, Stanley Stasiewicz, Pierre R. Bushel, Michael D. Waters
Bioinform.5