Showing 1-25 of 7,333 resultsfor "Index Terms":Secondary Structure
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A two-stage neural network based technique for protein secondary structure prediction
2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2008 | Conference Paper |
Cited by: Papers (1)
Protein secondary structure prediction is one of the most important research areas in bioinformatics. In this paper, we propose a two-stage protein secondary structure prediction technique, implemented using neural network models. The first neural network stage of the proposed technique associates the input protein sequence to a bin containing its corresponding homologues. The second stage predict...Show More
Multiple alignment through protein secondary-structure information
It is well known that protein secondary-structure information can help the process of performing multiple alignment, in particular when the amount of similarity among the involved sequences moves toward the "twilight zone" (less than 30% of pairwise similarity). In this paper, a multiple alignment algorithm is presented, explicitly designed for exploiting any available secondary-structure informat...Show More
Secondary Structure and Contact Guided Differential Evolution for Protein Structure Prediction
Ab initio protein tertiary structure prediction is one of the long-standing problems in structural bioinformatics. With the help of residue-residue contact and secondary structure prediction information, the accuracy of ab initio structure prediction can be enhanced. In this study, an improved differential evolution with secondary structure and residue-residue contact information referred to as SC...Show More
Solving the Secondary Structure Matching Problem in Cryo-EM De Novo Modeling Using a Constrained $K$-Shortest Path Graph Algorithm
Electron cryomicroscopy is becoming a major experimental technique in solving the structures of large molecular assemblies. More and more three-dimensional images have been obtained at the medium resolutions between 5 and $10 \AA$. At this resolution range, major $\alpha$-helices can be detected as cylindrical sticks and β-sheets can be detected as plain-like regions. A critical question in de nov...Show More
Toward Better Understanding of Protein Secondary Structure: Extracting Prediction Rules
Although numerous computational techniques have been applied to predict protein secondary structure (PSS), only limited studies have dealt with discovery of logic rules underlying the prediction itself. Such rules offer interesting links between the prediction model and the underlying biology. In addition, they enhance interpretability of PSS prediction by providing a degree of transparency to the...Show More
Prediction of protein secondary structure using multilayer feed-forward neural networks
2013 25th Chinese Control and Decision Conference (CCDC)
Year: 2013 | Conference Paper |
Cited by: Papers (2)
Important progress has been achieved in predicting secondary structure of protein sequences using artificial neural network recently. However, most of the models they used were BP networks with single hidden layer. In this paper, we try to use feedforward neural network involving more hidden layers to train and test the data set. While it has better generation ability and higher accuracy rate than...Show More
An Aggregation Method to Identify the RNA Meta-Stable Secondary Structure and its Functionally Interpretable Structure Ensemble
RNA can provide vital cellular functions through its secondary or tertiary structure. Due to the low-throughput nature of experimental approaches, studies on RNA structures mainly resort to computational methods. However, current existing tools fail to consider RNA structure ensembles and do not provide ways to decipher functional hypotheses for the new predictions. In this research, a novel metho...Show More
SARNA-Predict: Accuracy Improvement of RNA Secondary Structure Prediction Using Permutation-Based Simulated Annealing
Ribonucleic acid (RNA), a single-stranded linear molecule, is essential to all biological systems. Different regions of the same RNA strand will fold together via base pair interactions to make intricate secondary and tertiary structures that guide crucial homeostatic processes in living organisms. Since the structure of RNA molecules is the key to their function, algorithms for the prediction of ...Show More
Folding type specific secondary structure propensities of synonymous codons
We have proposed new amino acid secondary structure propensities in proteins with different folding types based on synonymous codons. They have been derived from 200 all alpha, all beta, alpha/beta, and alpha + beta proteins of known structures and their coding genes. The secondary structure propensities of the same codon in gene coding for different folding type proteins are not the same. For ins...Show More
Peptides secondary structure prediction with neural networks: a criterion for building appropriate learning sets
Artificial neural networks have been recently applied with success for protein secondary structure prediction. So far, one of the two main aspects on which neural net performance depends, the topology of the net, has been considered. The present work addresses the other main aspect, the building up of the learning set. The author presents a criterion to build up suitable learning sets based on the...Show More
A voting scheme to improve the secondary structure prediction
ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010
Year: 2010 | Conference Paper |
Cited by: Papers (2)
This paper presents a novel approach, namely SSVS, to improve the secondary structure prediction of proteins. In this work, a Radial Basis Function Neural Network is trained to combine different answers found by different secondary structure prediction techniques to produce superior answers. SSVS is tested with three of the well-known benchmarks in this field. The results demonstrate the superiori...Show More
Exploring Dominating Features from Apis Mellifera Pre-miRNA
2008 International Conference on Advanced Computer Theory and Engineering
Year: 2008 | Conference Paper |
Cited by: Papers (1)
In this paper, we report systematic in depth analysis of 54 known pre-miRNA from Apis mellifera (honey bee) with a set of 14 attributes. We have derived this set of attributes from secondary structure data that are generated from pre-miRNA sequences from Apis meillfera database using RNAfold. Principal component analysis method has been applied for dimension reduction. It reduces dimension of this...Show More
Characteristics of Secondary Electron Emission from Textured Structure Surface
2023 24th International Vacuum Electronics Conference (IVEC)
Year: 2023 | Conference Paper |
The secondary electron emission (SEE) of microwave device materials is an important physical process affecting the micro-discharge effect of components. The surface structure design applied to reduce SEE has increased year by year, but there are few reports on the surface simulation of textured structures. In this paper, the Monte Carlo (MC) model of SEE on metal surface is used to realize the Mon...Show More
A Review on RNA Secondary Structure Prediction Algorithms
2018 International Congress on Big Data, Deep Learning and Fighting Cyber Terrorism (IBIGDELFT)
Year: 2018 | Conference Paper |
Cited by: Papers (3)
Undoubtedly, RNA has vital functions on organisms. As a single stranded nucleic acid, it tends to bend and twirl and it forms a stable structure of itself. This is what comes to be known as the RNA secondary structure. RNA secondary structure is of use in determining the functionalities of RNA sequences as well as in pharmaceutical developments. Furthermore, predicting the secondary structure of a...Show More
An improved prediction of protein secondary structures based on a multi-mold integrated neural network
2012 8th International Conference on Natural Computation
Year: 2012 | Conference Paper |
Cited by: Papers (2)
The purpose of this proposes an improved prediction of protein secondary structures based on a multi-mold integrated neural network. A structure of modified artificial neural network based on built a 5-child network integrated multi-mold neural networks in which a child for each network using neural network classification is divided into two-level network is presented. Prediction comprehensive res...Show More
Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction
In this paper, we develop a segmental semi-Markov model (SSMM) for protein secondary structure prediction which incorporates multiple sequence alignment profiles with the purpose of improving the predictive performance. The segmental model is a generalization of the hidden Markov model where a hidden state generates segments of various length and secondary structure type. A novel parameterized mod...Show More
Amino Acid Encoding Methods for Protein Sequences: A Comprehensive Review and Assessment
As the first step of machine-learning based protein structure and function prediction, the amino acid encoding play a fundamental role in the final success of those methods. Different from the protein sequence encoding, the amino acid encoding can be used in both residue-level and sequence-level prediction of protein properties by combining them with different algorithms. However, it has not attra...Show More
A Comparative Study on Filtering Protein Secondary Structure Prediction
Petros Kountouris;Michalis Agathocleous;Vasilis J. Promponas;Georgia Christodoulou;Simos Hadjicostas;Vassilis Vassiliades;Chris Christodoulou
Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine learning techniques and empirical rules and we found that combinations of the two lead to the highest improvement.Show More
A Fast Algorithm for Low-Resolution Protein Structure Prediction
2006 International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2006 | Conference Paper |
Cited by: Papers (4)
We propose a new approach for the protein tertiary structure prediction based on the concept of mini-threading. The method identifies useful fragments in Protein Data Bank (PDB) with variable lengths and retrieves spatial restraints. The multidimensional scaling method and least-squares minimization are used to build coarse-grain structural models. Our method uses the information in the PDB effici...Show More
PSS-SQL: Protein Secondary Structure - Structured Query Language
Dariusz Mrozek;Dominika Wieczorek;Bozena Malysiak-Mrozek;Stanislaw Kozielski
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
Year: 2010 | Conference Paper |
Cited by: Papers (11)
Secondary structure representation of proteins provides important information regarding protein general construction and shape. This representation is often used in protein similarity searching. Since existing commercial database management systems do not offer integrated exploration methods for biological data e.g. at the level of the SQL language, the structural similarity searching is usually p...Show More
New Trend of Protein Secondary Structure Prediction
2009 International Symposium on Intelligent Ubiquitous Computing and Education
Year: 2009 | Conference Paper |
Cited by: Papers (1)
At first, this paper reviews the development history of the protein secondary structure prediction. Some concerned secondary structure prediction methods are introduced. Then a novel method is proposed, which substantially improves the prediction accuracy of CB513 with 80.49% and RS126 with 82.79% respectively. In the end, this paper points out several possible trends in the protein secondary stru...Show More
Prediction of protein secondary structure using large margin nearest neighbor classification
2011 3rd International Conference on Advanced Computer Control
Year: 2011 | Conference Paper |
Cited by: Papers (1)
Prediction of protein secondary structure from a primary sequence plays a critical role in structural biology. In this paper, we introduce a novel method for protein secondary structure prediction by using PSSM profiles and large margin nearest neighbor classification. Although the PSSM profiles and traditional nearest neighbor (NN) method can be directly used to predict secondary structure, since...Show More
Improved protein secondary structure prediction using support vector machine with a new encoding scheme and an advanced tertiary classifier
Prediction of protein secondary structures is an important problem in bioinformatics and has many applications. The recent trend of secondary structure prediction studies is mostly based on the neural network or the support vector machine (SVM). The SVM method is a comparatively new learning system which has mostly been used in pattern recognition problems. In this study, SVM is used as a machine ...Show More
StemP: A Fast and Deterministic Stem-Graph Approach for RNA Secondary Structure Prediction
We propose a new deterministic methodology to predict the secondary structure of RNA sequences. What information of stem is important for structure prediction, and is it enough ? The proposed simple deterministic algorithm uses minimum stem length, Stem-Loop score, and co-existence of stems, to give good structure predictions for short RNA and tRNA sequences. The main idea is to consider all possi...Show More
Structural classification of protein sequences based on signal processing and support vector machines
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2016 | Conference Paper |
Cited by: Papers (6)
The function of any protein depends directly on its secondary and tertiary structure. Proteins can fold into a three-dimensional shape, which is primarily depended on the arrangement of amino acids in the primary structure. In recent years, with the explosive sequencing of proteins, it is unfeasible to perform detailed experimental studies, as these methodologies are very expensive and time consum...Show More
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