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In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorithm, its efficiency majorly depends upon the underlying similarity/dissimilarity measure. During the analysis of such data often there is the need to further explore the similarity of genes not only with respect to their expression values but also with respect to their functional annotations, which can be obtained from Gene Ontology (GO) databases. In the existing literature several novel clustering and bi-clustering approaches were proposed to identify co-regulated genes from gene-expression datasets. Identifying co-regulated genes from gene expression data misses some important biological information about functionalities of genes, which is necessary to identify semantically related genes. In this paper, we have proposed sixteen different semantic gene-gene dissimilarity measures utilizing biological information of genes retrieved from a global biological database namely Gene Ontology (GO). Four different proximity measures, viz. Euclidean, Cosine, point symmetry and line symmetry are utilized along with four different representations of gene-GO-term annotation vectors to develop total sixteen gene-gene dissimilarity measures. In order to illustrate the profitability of developed dissimilarity measures, some multi-objective as well as single-objective clustering algorithms are applied utilizing proposed measures to identify functionally similar genes from Mouse genome and Yeast datasets. Furthermore, we have compared the performance of our proposed sixteen dissimilarity measures with three existing state-of-the-art semantic similarity and distance measures.
This article was published in the following journal.
The first step of any metagenome sequencing project is to get the inventory of OTU abundances (operational taxonomic units) and/or metagenomic gene abundances. The former is generated with 16S-rRNA-ta...
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With the development of pharmacogenomics and pharmacogenetics, personalized medicine based on genetic are increasingly required clinically. Incretin-based therapy is currently the most pop...
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RATIONALE: Inserting the p53 gene into a person's tumor may improve the body's ability to fight liver cancer. PURPOSE: Phase I trial to study the effectiveness of gene therapy with the p5...
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The number of copies of a given gene present in the cell of an organism. An increase in gene dosage (by GENE DUPLICATION for example) can result in higher levels of gene product formation. GENE DOSAGE COMPENSATION mechanisms result in adjustments to the level GENE EXPRESSION when there are changes or differences in gene dosage.
The use of techniques that produce a functional MUTATION or an effect on GENE EXPRESSION of a specific gene of interest in order to identify the role or activity of the gene product of that gene.
Techniques to alter a gene sequence that result in an inactivated gene, or one in which the expression can be inactivated at a chosen time during development to study the loss of function of a gene.
The GENETIC RECOMBINATION of the parts of two or more GENES resulting in a gene with different or additional regulatory regions, or a new chimeric gene product. ONCOGENE FUSION includes an ONCOGENE as at least one of the fusion partners and such gene fusions are often detected in neoplastic cells and are transcribed into ONCOGENE FUSION PROTEINS. ARTIFICIAL GENE FUSION is carried out in vitro by RECOMBINANT DNA technology.
Sets of structured vocabularies used for describing and categorizing genes, and gene products by their molecular function, involvement in biological processes, and cellular location. These vocabularies and their associations to genes and gene products (Gene Ontology annotations) are generated and curated by the Gene Ontology Consortium.
Bioinformatics is the application of computer software and hardware to the management of biological data to create useful information. Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied...
A DNA microarray or biochip is a collection of microscopic DNA spots attached to a solid surface used to measure the expression levels of large numbers of genes simultaneously or to genotype multiple regions of a genome.
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