Reach Us +441414719275
A Comparative Study Of Gene Similarity Measures | 9336
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
Open Access

Like us on:

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

International Conference on Integrative Biology Summit

Anurag Nagar
ScientificTracks Abstracts: J Comput Sci Syst Biol
DOI: 10.4172/0974-7230.S1.002
Genes are essential functional, regulatory and hereditary units present in all living organisms. They are identified by contiguous stretches of DNA present in chromosomes and carry the codes for a polypeptide or RNA chain that has a particular purpose. Genes also code for protein synthesis, which is one of the most important functions of the cells. Genes have been studied from various perspectives-such as identifying their DNA sequence and location on chromosomes, identifying their purpose and functions, studying evolution over time, and finding their similarity across multiple species. One of the most important repositories of gene related information is the Gene Ontology (GO) project. This project was started with the aim of providing a standard way of storing gene related information for multiple species and products. Gene Ontology contains three types of gene ontologies that describe biological terms and processes-Biological Processes (BP), Molecular Function (MF) and Cellular Components. These terms are organized in the form a directed acyclic graph with the terms getting more specific as we travel down the graph. Various genome projects such as the yeast genome project and the human genome project annotate species-specific genes with the terms of the GO. One of the important applications of GO is to compute similarities between genes -either from the same species or different ones. Various semantic similarity measures have been proposed so far. Some of them use the Information Content of the terms, such as that proposed by Resnik et al while others use the distances between edges of the terms, such as that proposed by Nagar et al. Researchers have tried to improve upon them continuously, for example the IntelliGO measure proposed by Benabderrahmane et al. The above similarity measures use different approaches so their results are different for the same pair of genes. With the development of next generation sequencing technologies, it has become possible to identify the exact location and sequence of the genes. It is thus possible to compute the sequence similarity between two genes and see how this correlates to their semantic similarity computed by using GO. Some amount of work in this direction has been done by P.W. Lord et al in their paper ? Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation ?. However, this was in 2002 and they used only one GO-based similarity measure. Since then many new methods have been proposed and it is interesting to re-visit this problem and compare their similarities. This talk will present a background of GO, review the existing semantic similarity measures and compare them with the sequence similarity measures obtained by using sequence comparison methods such as Clustal. The results show that there is still a need for better semantic similarity measures that utilize the structure of GO terms and the information content in them.
image PDF   |   image HTML

Relevant Topics

Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Business & Management Journals


[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version