An Insilico Approach For Protein Secondary Structure Modeling: Prediction of helical transmembrane region using Artificial Neur,Used

An Insilico Approach For Protein Secondary Structure Modeling: Prediction of helical transmembrane region using Artificial Neur,Used

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SKU: DADAX3846582689
Brand: LAP Lambert Academic Publishing
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The structural knowledge of transmembrane proteins is difficult to attain experimentally, as the wetlab experimental methods are time consuming, expensive, require good infrastructure and contain high false positive results. Hence, the need of insilico methods for protein secondary structure prediction is being driven by above listed limitations. Over a number of years, various transmembrane region predictors has been developed using computational approach. In this book, a connectionist (ANNArtificial Neural Network) model has been developed for prediction of alpha helical transmembrane region using amino acid properties rather than using the traditional hydrophobicity approach. The best connectionist model developed in this book, achieved an accuracy of 73.31%, which seems to be relatively better than the methods developed earlier by different researchers. This book will be equally helpful to bioinformatician, molecular biologist as well as computational biologist in solving various complex biological problems that could not be solved with the traditional approach.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

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