In silico analysis of genes implicated in Alopecia areata

Alopecia areata (AA) is a common genetically determined, complex autoimmune condition characterized by the rapid onset of hair loss in a sharply defined area. Though alopecia areata is not life threatening disease, the psychological impact of sudden and extensive hair loss can have significant quali...

Full description

Saved in:
Bibliographic Details
Published in:Pakistan journal of zoology 2011-06, Vol.43 (3), p.437-446
Main Authors: Anjum, I.F. (International Islamic Univ., Islamabad (Pakistan). Dept. of Bioinformatics and Biotechnology), Mir, A. (International Islamic Univ., Islamabad (Pakistan). Dept. of Bioinformatics and Biotechnology), Riaz, N. (International Islamic Univ., Islamabad (Pakistan). Dept. of Bioinformatics and Biotechnology)
Format: Article
Language:English
Subjects:
Alopecia
Autoimmune diseases
Baldness
Bioinformatics
Diagnosis
Gene mutations
GENES
Genetic aspects
GENETICS
Hair
Interleukin 1
MICA protein
Missense mutation
MUTATION
NUCLEOTIDE SEQUENCE
Observations
Protein-tyrosine-phosphatase
Quality of life
SKIN DISEASES
Tumor necrosis factor- alpha
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Alopecia areata (AA) is a common genetically determined, complex autoimmune condition characterized by the rapid onset of hair loss in a sharply defined area. Though alopecia areata is not life threatening disease, the psychological impact of sudden and extensive hair loss can have significant quality of life repercussions for affected patients and their families. For a better understanding and improved treatment of this complex disease, all of the genes involved in it should be analyzed and fully modeled. We have done in Silico protein analysis and complete modeling of the products of AIRS, PTPN22, AM], MY, TNF-a, ILIRN, ILIF5, MICA genes, which have been implicated in AA, and we have modeled the effects of some of the known missense mutations in these proteins at molecular level using bioinformatic tools.
ISSN:0030-9923