MeSHer: identifying biological concepts in microarray assays based on PubMed references and MeSH terms
| Autor: | Eleanor A. Howe, Svetlana Karamycheva, Amira Djebbari, John Quackenbush |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Statistics and Probability
PubMed Microarray Information Storage and Retrieval Computational biology Biology computer.software_genre Biochemistry Set (abstract data type) Medical Subject Headings Artificial Intelligence Protein Interaction Mapping Molecular Biology Gene Natural Language Processing Oligonucleotide Array Sequence Analysis Models Statistical Models Genetic Mesh term Gene Expression Profiling Subject (documents) Angiotensin II Computer Science Applications Computational Mathematics Vocabulary Controlled Computational Theory and Mathematics Database Management Systems Data mining DNA microarray computer Software |
| Zdroj: | Bioinformatics. 21:3324-3326 |
| ISSN: | 1367-4811 1367-4803 |
| DOI: | 10.1093/bioinformatics/bti503 |
| Popis: | Summary: MeSHer uses a simple statistical approach to identify biological concepts in the form of Medical Subject Headings (MeSH terms) obtained from the PubMed database that are significantly overrepresented within the identified gene set relative to those associated with the overall collection of genes on the underlying DNA microarray platform. As a demonstration, we apply this approach to gene lists acquired from a published study of the effects of angiotensin II (Ang II) treatment on cardiac gene expression and demonstrate that this approach can aid in the interpretation of the resulting ‘significant’ gene set. Availability: The software is available at http://www.tm4.org Contact: johnq@jimmy.harvard.edu Supplementary information: Results from the analysis of significant genes from the published Ang II study. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|