Warning: Undefined array key "mm" in /www/wwwroot/www.ai-bt.com/si.php on line 10 Deprecated: trim(): Passing null to parameter #1 ($string) of type string is deprecated in /www/wwwroot/www.ai-bt.com/si.php on line 10 A method for finding communities of related genes.

Literature DB >> 14757821

A method for finding communities of related genes.

Dennis M Wilkinson¹, Bernardo A Huberman.

Abstract

We present a method for creating a network of gene co-occurrences from the literature and partitioning it into communities of related genes. The way in which our method identifies communities makes it likely that the component genes of each community will be related by their function. The method processes a large database of article abstracts, synthesizing information from many sources to shed light on groups of genes that have been shown to interact. It is a tool to be used by researchers in the biomedical sciences to swiftly search for known interactions and to provide insight into unexplored connections. The partitioning procedure is designed to be particularly applicable to large networks in which individual nodes may play a role in more than one community. In this paper, we explain the details of the method, in particular the partitioning process. We also apply the method to produce communities of genes related to colon cancer and show that the results are useful.

Entities: Disease

Mesh：

Substances：
Proteins
RNA

Year: 2004 PMID： 14757821 PMCID： PMC387302 DOI： 10.1073/pnas.0307740100

Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN： 0027-8424 Impact factor: 11.205

16 in total

A method for finding communities of related genes.

1. Genome evolution. Global methylation in eutherian hybrids.

2. A literature network of human genes for high-throughput analysis of gene expression.

3. MedMiner: an Internet text-mining tool for biomedical information, with application to gene expression profiling.

4. Detecting Gene Symbols and Names in Biological Texts: A First Step toward Pertinent Information Extraction.

5. Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts.

6. Biobibliometrics: information retrieval and visualization from co-occurrences of gene names in Medline abstracts.

7. GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles.

8. Robust relational parsing over biomedical literature: extracting inhibit relations.

9. Using text analysis to identify functionally coherent gene groups.

10. A literature based method for identifying gene-disease connections.

1. From single genes to co-expression networks: extracting knowledge from barley functional genomics.

2. Complex network analysis of free-energy landscapes.

3. Clique-based data mining for related genes in a biomedical database.

Review 4. Cyclophilin nomenclature problems, or, 'a visit from the sequence police'.

5. Building a protein name dictionary from full text: a machine learning term extraction approach.

6. Improved network community structure improves function prediction.

7. The effect of edge definition of complex networks on protein structure identification.

8. Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.

9. Application of a new probabilistic model for mining implicit associated cancer genes from OMIM and medline.

10. The transfer and transformation of collective network information in gene-matched networks.