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Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes
The twin epidemic of diabetes and obesity pose daunting challenges worldwide. The dramatic rise in obesity-associated diabetes resulted in an alarming increase in the incidence and prevalence of obesity an important complication of diabetes. Differences among individuals in their susceptibility to b...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Master Publishing Group
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614673/ https://www.ncbi.nlm.nih.gov/pubmed/23675069 |
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author | Rao, Allam Appa Tayaru, N. Manga Thota, Hanuman Changalasetty, Suresh Babu Thota, Lalitha Saroja Gedela, Srinubabu |
author_facet | Rao, Allam Appa Tayaru, N. Manga Thota, Hanuman Changalasetty, Suresh Babu Thota, Lalitha Saroja Gedela, Srinubabu |
author_sort | Rao, Allam Appa |
collection | PubMed |
description | The twin epidemic of diabetes and obesity pose daunting challenges worldwide. The dramatic rise in obesity-associated diabetes resulted in an alarming increase in the incidence and prevalence of obesity an important complication of diabetes. Differences among individuals in their susceptibility to both these conditions probably reflect their genetic constitutions. The dramatic improvements in genomic and bioinformatic resources are accelerating the pace of gene discovery. It is tempting to speculate the key susceptible genes/proteins that bridges diabetes mellitus and obesity. In this regard, we evaluated the role of several genes/proteins that are believed to be involved in the evolution of obesity associated diabetes by employing multiple sequence alignment using ClustalW tool and constructed a phylogram tree using functional protein sequences extracted from NCBI. Phylogram was constructed using Neighbor-Joining Algorithm a bioinformatic tool. Our bioinformatic analysis reports resistin gene as ominous link with obesity associated diabetes. This bioinformatic study will be useful for future studies towards therapeutic inventions of obesity associated type 2 diabetes. |
format | Online Article Text |
id | pubmed-3614673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Master Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-36146732013-05-01 Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes Rao, Allam Appa Tayaru, N. Manga Thota, Hanuman Changalasetty, Suresh Babu Thota, Lalitha Saroja Gedela, Srinubabu Int J Biomed Sci Article The twin epidemic of diabetes and obesity pose daunting challenges worldwide. The dramatic rise in obesity-associated diabetes resulted in an alarming increase in the incidence and prevalence of obesity an important complication of diabetes. Differences among individuals in their susceptibility to both these conditions probably reflect their genetic constitutions. The dramatic improvements in genomic and bioinformatic resources are accelerating the pace of gene discovery. It is tempting to speculate the key susceptible genes/proteins that bridges diabetes mellitus and obesity. In this regard, we evaluated the role of several genes/proteins that are believed to be involved in the evolution of obesity associated diabetes by employing multiple sequence alignment using ClustalW tool and constructed a phylogram tree using functional protein sequences extracted from NCBI. Phylogram was constructed using Neighbor-Joining Algorithm a bioinformatic tool. Our bioinformatic analysis reports resistin gene as ominous link with obesity associated diabetes. This bioinformatic study will be useful for future studies towards therapeutic inventions of obesity associated type 2 diabetes. Master Publishing Group 2008-03 /pmc/articles/PMC3614673/ /pubmed/23675069 Text en © Allam Appa Rao et al. Licensee Master Publishing Group http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Article Rao, Allam Appa Tayaru, N. Manga Thota, Hanuman Changalasetty, Suresh Babu Thota, Lalitha Saroja Gedela, Srinubabu Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes |
title | Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes |
title_full | Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes |
title_fullStr | Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes |
title_full_unstemmed | Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes |
title_short | Bioinformatic Analysis of Functional Proteins Involved in Obesity Associated with Diabetes |
title_sort | bioinformatic analysis of functional proteins involved in obesity associated with diabetes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614673/ https://www.ncbi.nlm.nih.gov/pubmed/23675069 |
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