3 results match your criteria: "Psychiatry Department and Molecular and Behavioral Neuroscience Institute.[Affiliation]"

Cross-domain neurobiology data integration and exploration.

BMC Genomics

December 2010

Psychiatry Department and Molecular and Behavioral Neuroscience Institute, University of Michigan, USA.

Background: Understanding the biomedical implications of data from high throughput experiments requires solutions for effective cross-scale and cross-domain data exploration. However, existing solutions do not provide sufficient support for linking molecular level data to neuroanatomical structures, which is critical for understanding high level neurobiological functions.

Results: Our work integrates molecular level data with high level biological functions and we present results using anatomical structure as a scaffold.

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Open Biomedical Ontology-based Medline exploration.

BMC Bioinformatics

May 2009

Psychiatry Department and Molecular and Behavioral Neuroscience Institute, University of Michigan, USA.

Background: Effective Medline database exploration is critical for the understanding of high throughput experimental results and the development of novel hypotheses about the mechanisms underlying the targeted biological processes. While existing solutions enhance Medline exploration through different approaches such as document clustering, network presentations of underlying conceptual relationships and the mapping of search results to MeSH and Gene Ontology trees, we believe the use of multiple ontologies from the Open Biomedical Ontology can greatly help researchers to explore literature from different perspectives as well as to quickly locate the most relevant Medline records for further investigation.

Results: We developed an ontology-based interactive Medline exploration solution called PubOnto to enable the interactive exploration and filtering of search results through the use of multiple ontologies from the OBO foundry.

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Understanding the molecular mechanisms underlying complex disorders requires the integration of data and knowledge from different sources including free text literature and various biomedical databases. To facilitate this process, we created the Biomedical Concept Diagram Editor (BCDE) to help researchers distill knowledge from data and literature and aid the process of hypothesis development. A key feature of BCDE is the ability to capture information with a simple drag-and-drop.

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