Results 41 to 50 of about 257,655 (321)
Protein secondary structure prediction using neural networks and deep learning: A review [PDF]
Wafaa Wardah+3 more
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A Kernel for Protein Secondary Structure Prediction [PDF]
Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is ...
Guermeur, Yann+2 more
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Protein secondary structure is the basis of studying the tertiary structure of proteins, drug design and development, and the 8-state protein secondary structure can provide more adequate protein information than the 3-state structure.
Shun Li, Lu Yuan, Yuming Ma , Yihui Liu
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Protein secondary structure: entropy, correlations and prediction [PDF]
Abstract Motivation: Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone or by non-local tertiary interactions? To answer this question, we measure the entropy densities of primary and secondary structure sequences, and the local inter-sequence mutual ...
Gavin E. Crooks, Steven E. Brenner
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Sample Reduction Strategies for Protein Secondary Structure Prediction
Predicting the secondary structure from protein sequence plays a crucial role in estimating the 3D structure, which has applications in drug design and in understanding the function of proteins. As new genes and proteins are discovered, the large size of
Sema Atasever+3 more
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Recently a new method called the self-optimized prediction method (SOPM) has been described to improve the success rate in the prediction of the secondary structure of proteins.
C. Geourjon, G. Deléage
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Combining classifiers for protein secondary structure prediction [PDF]
Protein secondary structure prediction is an important step in estimating the three dimensional structure of proteins. Among the many methods developed for predicting structural properties of proteins, hybrid classifiers and ensembles that combine predictions from several models are shown to improve the accuracy rates. In this paper, we train, optimize
Aydin, Zafer, Uzut, Ommu Gulsum
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PCI-SS: MISO dynamic nonlinear protein secondary structure prediction
Background Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology.
Aboul-Magd Mohammed O+2 more
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Using Deep Learning (CNN, RNN, LSTM, GRU) methods for the prediction of Protein Secondary Structure
Proteins play a crucial function in the biological processes of living organisms. Knowing the function of the protein offers significant insight into future biological and medical research. Since a protein’s shape determines its function, it is important
Ezgi Çakmak, İhsan Hakan Selvi
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MASSP3: A System for Predicting Protein Secondary Structure [PDF]
A system that resorts to multiple experts for dealing with the problem of predicting secondary structures is described, whose performances are comparable to those obtained by other state-of-the-art predictors. The system performs an overall processing based on two main steps: first, a "sequence-to-structure" prediction is performed, by resorting to a ...
ARMANO, GIULIANO, ORRO A, VARGIU, ELOISA
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