Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/6172
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dc.contributor.authorAsif, Muhammad-
dc.date.accessioned2018-11-15T09:37:16Z-
dc.date.available2018-11-15T09:37:16Z-
dc.date.issued2013-
dc.identifier.urihttp://hdl.handle.net/123456789/6172-
dc.description.abstractThe completion of human and other genome sequencing projects through high throughput sequencing approaches provides an opportunity to explore their byproduct, SNPs (single nucleotide polymorphism). Among the short variants that occurred in human genome, SNPs are more prominent than other variants. It is estimated that in human genome, there are more than four million SNPs, which act as molecular markers to comprehend the genome. SNPs are also used in agriculture for crop breeding and help in tracing the genetic disease and its susceptibility. Furthermore, SNPs are precise and effective source to understand evolutionary mechanisms. In this context, RFLP (Restriction Fragment Length Polymorphism), a commonly used technique to genotype the SNPs, is effectively used to study the genetic disorders, DNA finger printing and genome mapping. In this study, we developed a server VRSAP (Visual Representation of SNPs and Polymorphism), which facilitates in combining SNPs and RFLP based data in a single platform and largely helps in designing novel markers for genetic study. VRSAP mainly comprises three modules namely, SNP, RFLP and SNP-RFLP. All these modules work together for string and graphical visualization of SNPs and restriction sites. VRSAP generates a hypothetical gel image to investigate the unique pattern of markers. VRSAP functionality includes multiple species thereby aiding to understand the complexity among orthologs or paralogs. This pipeline is also applicable to human population to uncover the common SNPs with respect to their drug response. By using these features, a comparative study of disease causing genes can be performed to design a specific drug. Finally, VRSAP functionality was validated by the inclusion of transmembrane 106 protein gene family, which clearly indicated the effect of SNPs on restriction pattern change. Taken together, the comparative view generated by VRSAP is helpful in understanding the genome, gene family or even gene evolutionen_US
dc.language.isoenen_US
dc.publisherQuaid-i-Azam University Islamabaden_US
dc.subjectBioinformaticsen_US
dc.titleIn Silico RFLP Simulation, incorporated with SNPsen_US
dc.typeThesisen_US
Appears in Collections:M.Phil

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