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Lung Cancer is a disease of uncontrolled cell growth and replication in lung tissues.These rapidly growing cells begin to invade adjacent tissues and thus lung cancer acts to be Metastatic in nature. This work aims to obtain a comparative and statistical collaboration of conserved mutated and unmutated patterns in lung cancer patients while highlighting RAS and EGFR Protein Families which are actively involved in the pathogenesis of Lung Cancer.A variety of bioinformatics tools and search engines were used to arrive at the sequence, structure and function of the proteins of these families.…mehr

Produktbeschreibung
Lung Cancer is a disease of uncontrolled cell growth and replication in lung tissues.These rapidly growing cells begin to invade adjacent tissues and thus lung cancer acts to be Metastatic in nature. This work aims to obtain a comparative and statistical collaboration of conserved mutated and unmutated patterns in lung cancer patients while highlighting RAS and EGFR Protein Families which are actively involved in the pathogenesis of Lung Cancer.A variety of bioinformatics tools and search engines were used to arrive at the sequence, structure and function of the proteins of these families. Inter protein analysis, Intra Protein analysis, conserved pattern identification, Mutation study, Protein-Protein interaction and Primer Designing were performed. On the basis of various parameters protein binding site was identified.Simulation was performed to get the optimized energy.The drug discovery program includes finding all chemical compounds having potential to inactive the protein.Virtual screening and docking studies were performed.The present study contributes to the possibility that genetic components are more important as compared to environmental and smoking(carcinogens) factors.
Autorenporträt
Msc Bioinformatics,BIT,Mesra,India.Currently holds the position of Bioinformatics Research Associate in BioAxis DNA Research Centre,India.Several International publications in Bioinformatics field.Major research interest includes in-silico drug design,molecular modelling,simulation studies,toxicity prediction.