List Of Protein Secondary Structure Prediction Programs
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List Of Protein Secondary Structure Prediction Programs
List of notable protein secondary structure prediction programs See also * List of protein structure prediction software * Protein structure prediction Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is differen ... {{DEFAULTSORT:Protein Structure Prediction Structural bioinformatics software Protein structure Protein methods ...
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RaptorX / Software For Protein Modeling And Analysis
RaptorX is a software and web server for protein structure and function prediction that is free for non-commercial use. RaptorX is among the most popular methods for protein structure prediction. Like other remote homology recognition/protein threading techniques, RaptorX is able to regularly generate reliable protein models when the widely used PSI-BLAST cannot. However, RaptorX is also significantly different from those profile-based methods (e.g., HHPred and Phyre2) in that RaptorX excels at modeling of protein sequences without a large number of sequence homologs by exploiting structure information. RaptorX Server has been designed to ensure a user-friendly interface for users inexpert in protein structure prediction methods. Description The RaptorX project was started in 2008 and RaptorX Server was released to the public in 2011. Standard usage After pasting a protein sequence into the RaptorX submission form, a user will typically wait a couple of hours (depending ...
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PSI-BLAST
In bioinformatics, BLAST (basic local alignment search tool) is an algorithm and program for comparing primary biological sequence information, such as the amino-acid sequences of proteins or the nucleotides of DNA and/or RNA sequences. A BLAST search enables a researcher to compare a subject protein or nucleotide sequence (called a query) with a library or database of sequences, and identify database sequences that resemble alphabet above a certain threshold. For example, following the discovery of a previously unknown gene in the mouse, a scientist will typically perform a BLAST search of the human genome to see if humans carry a similar gene; BLAST will identify sequences in the pig genome that resemble the mouse gene based on similarity of sequence. Background BLAST, which ''The New York Times'' called ''the Google of biological research'', is one of the most widely used bioinformatics programs for sequence searching. It addresses a fundamental problem in bioinformatics ...
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GOR Method
The GOR method (short for Garnier–Osguthorpe–Robson) is an information theory-based method for the prediction of secondary structures in proteins. It was developed in the late 1970s shortly after the simpler Chou–Fasman method. Like Chou–Fasman, the GOR method is based on probability parameters derived from empirical studies of known protein tertiary structures solved by X-ray crystallography. However, unlike Chou–Fasman, the GOR method takes into account not only the propensities of individual amino acids to form particular secondary structures, but also the conditional probability of the amino acid to form a secondary structure given that its immediate neighbors have already formed that structure. The method is therefore essentially Bayesian in its analysis. Method The GOR method analyzes sequences to predict alpha helix, beta sheet, turn, or random coil In polymer chemistry, a random coil is a conformation of polymers where the monomer subunits are oriented randomly ...
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Bayesian Inference
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the Sequential analysis, dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". Introduction to Bayes' rule Formal explanation Bayesian inference derives the posterior probability as a consequence relation, consequence of two Antecedent (logic), antecedents: a prior probability and a "likelihood function" derived from a statistical model for the observed data. Bayesian inference computes ...
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Jpred
Jpred v.4 is the latest version of the JPred Protein Secondary Structure Prediction Server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction, that has existed since 1998 in different versions. In addition to protein secondary structure, JPred also makes predictions of solvent accessibility and coiled-coil regions. The JPred service runs up to 134 000 jobs per month and has carried out over 2 million predictions in total for users in 179 countries. JPred 2 The static HTML pages of JPred 2 are still available for reference. JPred 3 The JPred v3 followed on from previous versions of JPred developed and maintained by James Cuff and Jonathan Barber (see JPred References). This release added new functionality and fixed many bugs. The highlights are: * New, friendlier user interface * Retrained and optimised version of Jnet (v2) - mean secondary structure prediction accuracy of >81% * Batch submission of jobs * Better er ...
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Neural Network
A neural network is a network or neural circuit, circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning re ...
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HMMER
HMMER is a free and commonly used software package for sequence analysis written by Sean Eddy. Its general usage is to identify homologous protein or nucleotide sequences, and to perform sequence alignments. It detects homology by comparing a ''profile-HMM'' (a Hidden Markov model constructed explicitly for a particular search) to either a single sequence or a database of sequences. Sequences that score significantly better to the profile-HMM compared to a null model are considered to be homologous to the sequences that were used to construct the profile-HMM. Profile-HMMs are constructed from a multiple sequence alignment in the HMMER package using the ''hmmbuild'' program. The profile-HMM implementation used in the HMMER software was based on the work of Krogh and colleagues. HMMER is a console utility ported to every major operating system, including different versions of Linux, Windows, and Mac OS. HMMER is the core utility that protein family databases such as Pfam and ...
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Predictprotein
PredictProtein (PP) is an automatic service that searches up-to-date public sequence databases, creates alignments, and predicts aspects of protein structure and function. Users send a protein sequence and receive a single file with results from database comparisons and prediction methods. PP went online in 1992 at the European Molecular Biology Laboratory; since 1999 it has operated from Columbia University and in 2009 it moved to the Technische Universität München. Although many servers have implemented particular aspects, PP remains the most widely used public server for structure prediction: over 1.5 million requests from users in 104 countries have been handled; over 13000 users submitted 10 or more different queries. PP web pages are mirrored in 17 countries on 4 continents. The system is optimized to meet the demands of experimentalists not experienced in bioinformatics. This implied that we focused on incorporating only high-quality methods, and tried to collate results o ...
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Neural Networks
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from ...
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List Of Protein Structure Prediction Software
This list of protein structure prediction software summarizes notable used software tools in protein structure prediction, including homology modeling, protein threading Protein threading, also known as fold recognition, is a method of protein modeling which is used to model those proteins which have the same fold as proteins of known structures, but do not have homologous proteins with known structure. It differs ..., ''ab initio'' methods, secondary structure prediction, and transmembrane helix and signal peptide prediction. Software list Below is a list which separates programs according to the method used for structure prediction. Homology modeling Threading/fold recognition ''Ab initio'' structure prediction Secondary structure prediction Detailed list of programs can be found at List of protein secondary structure prediction programs See also * List of protein secondary structure prediction programs * Comparison of nucleic acid simulation software * Li ...
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Protein Structure Prediction
Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; and it is important in medicine (for example, in drug design) and biotechnology (for example, in the design of novel enzymes). Starting in 1994, the performance of current methods is assessed biannually in the CASP experiment (Critical Assessment of Techniques for Protein Structure Prediction). A continuous evaluation of protein structure prediction web servers is performed by the community project CAMEO3D. Protein structure and terminology Proteins are chains of amino acids joined together by peptide bonds. Many conformations of this chain are possible due to the rotation of the main chain ...
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