Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/70444
Title: Computational Studies for the Identification and Analysis of Candidate Biomarkers for Human Diseases Implicated in DNA Repair System
Researcher: Sehgal, Manika
Guide(s): Singh, Tiratha Raj
Keywords: Colorectal Cancer
Database
DNA Repair
nsSNPs
Xeroderma Pigmentosum
University: Jaypee University of Information Technology, Solan
Completed Date: 09/02/2015
Abstract: In present era, the biomedical research has been revolutionized on the advent of human genome sequence and huge amount of genomic information is generated This huge amalgamation of genomic data is rising exponentially due to employment of high throughput techniques and application of modern biology However, less emphasis is remunerated on the obligatory genomic analysis, subsequently there is a need to apply extensive computational approaches that could deal abreast with the remarkable growth in generated biological data Since, the human system is very complex and the ultimate challenge is to decipher numerous multifaceted processes involved in the regulation of this system therefore systems biology has major relevance which assists in wideranging understanding of an entire system as a whole The human genome is susceptible to numerous endogenous and exogenous damages resulting in genomic instability These DNA lesions not only diversely impact genome but also enhance the predisposition to multi system defects including premature aging and ontogenesis On exposure to these damages, major cellular signaling processes are triggered which either result in cell cycle arrest, damage removal and activation of repair pathways There are a variety of DNA repair mechanisms which confiscates diverse form of lesions whether affecting single stranded or double stranded DNA Genetic abnormalities or mutations in DNA repair genes have implications in multiple hereditary disorders, aging and cancers which have always been a crucial subject for analysis among researchers Although some of the disease related mutations have been identified but there is a huge lack of knowledge underlying the associated mechanism newline newline newline
Pagination: 
URI: http://hdl.handle.net/10603/70444
Appears in Departments:Department of Bioinformatics

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01_title.pdfAttached File101.86 kBAdobe PDFView/Open
02_declaration.pdf332.17 kBAdobe PDFView/Open
03_certificate.pdf312.88 kBAdobe PDFView/Open
04_acknowledgement.pdf525.46 kBAdobe PDFView/Open
05_contents.pdf407.47 kBAdobe PDFView/Open
06_list of tables and figures.pdf375.42 kBAdobe PDFView/Open
07_chapter 1.pdf1.55 MBAdobe PDFView/Open
08_chapter 2.pdf1.5 MBAdobe PDFView/Open
09_chapter 3.pdf1.27 MBAdobe PDFView/Open
10_chapter 4.pdf1.41 MBAdobe PDFView/Open
11_chapter 5.pdf1.33 MBAdobe PDFView/Open
12_conclusion.pdf360.51 kBAdobe PDFView/Open
13_publications.pdf280.3 kBAdobe PDFView/Open


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