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CMGSDB: integrating heterogeneous Caenorhabditis elegans data sources using compositional data mining.

Pati A, Jin Y, Klage K, Helm RF, Heath LS, Ramakrishnan N - Nucleic Acids Res. (2007)

Bottom Line: Besides gene, protein and functional annotations, CMGSDB currently unifies information about 531 RNAi phenotypes obtained from heterogeneous databases using a hierarchical scheme.A phenotype browser at the CMGSDB website serves this hierarchy and relates phenotypes to other biological entities.Chains can, for example, relate the knock down of a set of genes during an RNAi experiment to the disruption of a pathway or specific gene expression through another set of genes not directly related to the former set.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061, USA.

ABSTRACT
CMGSDB (Database for Computational Modeling of Gene Silencing) is an integration of heterogeneous data sources about Caenorhabditis elegans with capabilities for compositional data mining (CDM) across diverse domains. Besides gene, protein and functional annotations, CMGSDB currently unifies information about 531 RNAi phenotypes obtained from heterogeneous databases using a hierarchical scheme. A phenotype browser at the CMGSDB website serves this hierarchy and relates phenotypes to other biological entities. The application of CDM to CMGSDB produces 'chains' of relationships in the data by finding two-way connections between sets of biological entities. Chains can, for example, relate the knock down of a set of genes during an RNAi experiment to the disruption of a pathway or specific gene expression through another set of genes not directly related to the former set. The web interface for CMGSDB is available at https://bioinformatics.cs.vt.edu/cmgs/CMGSDB/, and serves individual biological entity information as well as details of all chains computed by CDM.

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Related in: MedlinePlus

Data integration and analysis in CMGSDB.
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Figure 2: Data integration and analysis in CMGSDB.

Mentions: The key components of CMGSDB are illustrated in Figure 2. Biots are contained in light green boxes, which are represented by one or more relations in CMGSDB. Blue arrows represent relationships in CMGSDB. Plain black arrows represent data flow.Figure 2.


CMGSDB: integrating heterogeneous Caenorhabditis elegans data sources using compositional data mining.

Pati A, Jin Y, Klage K, Helm RF, Heath LS, Ramakrishnan N - Nucleic Acids Res. (2007)

Data integration and analysis in CMGSDB.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2238953&req=5

Figure 2: Data integration and analysis in CMGSDB.
Mentions: The key components of CMGSDB are illustrated in Figure 2. Biots are contained in light green boxes, which are represented by one or more relations in CMGSDB. Blue arrows represent relationships in CMGSDB. Plain black arrows represent data flow.Figure 2.

Bottom Line: Besides gene, protein and functional annotations, CMGSDB currently unifies information about 531 RNAi phenotypes obtained from heterogeneous databases using a hierarchical scheme.A phenotype browser at the CMGSDB website serves this hierarchy and relates phenotypes to other biological entities.Chains can, for example, relate the knock down of a set of genes during an RNAi experiment to the disruption of a pathway or specific gene expression through another set of genes not directly related to the former set.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061, USA.

ABSTRACT
CMGSDB (Database for Computational Modeling of Gene Silencing) is an integration of heterogeneous data sources about Caenorhabditis elegans with capabilities for compositional data mining (CDM) across diverse domains. Besides gene, protein and functional annotations, CMGSDB currently unifies information about 531 RNAi phenotypes obtained from heterogeneous databases using a hierarchical scheme. A phenotype browser at the CMGSDB website serves this hierarchy and relates phenotypes to other biological entities. The application of CDM to CMGSDB produces 'chains' of relationships in the data by finding two-way connections between sets of biological entities. Chains can, for example, relate the knock down of a set of genes during an RNAi experiment to the disruption of a pathway or specific gene expression through another set of genes not directly related to the former set. The web interface for CMGSDB is available at https://bioinformatics.cs.vt.edu/cmgs/CMGSDB/, and serves individual biological entity information as well as details of all chains computed by CDM.

Show MeSH
Related in: MedlinePlus