Protein Secondary Structure Prediction With a Reductive Deep Learning Method
نویسندگان
چکیده
منابع مشابه
Protein Secondary Structure Prediction: a Literature Review with Focus on Machine Learning Approaches
DNA sequence, containing all genetic traits is not a functional entity. Instead, it transfers to protein sequences by transcription and translation processes. This protein sequence takes on a 3D structure later, which is a functional unit and can manage biological interactions using the information encoded in DNA. Every life process one can figure is undertaken by proteins with specific functio...
متن کاملprotein secondary structure prediction: a literature review with focus on machine learning approaches
dna sequence, containing all genetic traits is not a functional entity. instead, it transfers to protein sequences by transcription and translation processes. this protein sequence takes on a 3d structure later, which is a functional unit and can manage biological interactions using the information encoded in dna. every life process one can figure is undertaken by proteins with specific functio...
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Protein structure prediction is an important and fundamental problem for which machine learning techniques have been widely used in bioinformatics and computational biology. Recently, deep learning has emerged as a new active area of research in machine learning, showing great success in diverse areas of signal and information processing studies. In this article, we provide a brief review on re...
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We present a new method for protein secondary structure prediction, based on the recognition of well-defined pentapeptides, in a large databank. Using a databank of 635 protein chains, we obtained a success rate of 68.6%. We show that progress is achieved when the databank is enlarged, when the 20 amino acids are adequately grouped in 10 sets and when more pentapeptides are attributed one of th...
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Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning exte...
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ژورنال
عنوان ژورنال: Frontiers in Bioengineering and Biotechnology
سال: 2021
ISSN: 2296-4185
DOI: 10.3389/fbioe.2021.687426