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Structured-prediction

Returning now to the issue of the accuracy of various electronic structure predictions, it is natural to ask why... [Pg.2159]

Unfortunately, the approach of determining empirical potentials from equilibrium data is intrinsically limited, even if we assume complete knowledge of all equilibrium geometries and their energies. It is obvious that statistical potentials cannot define an energy scale, since multiplication of a potential by a positive, constant factor does not alter its global minimizers. But for the purpose of tertiary structure prediction by global optimization, this does not not matter. [Pg.215]

J.D. Bryngelson, When is a potential accurate enough for structure prediction Theory and application to a random heteropolymer model of protein folding, J. Ghem. Phys. 100 (1994), 6038-6045. [Pg.222]

S. Sun, Reduced representation model of protein structure prediction statistical potential and genetic algorithms. Protein Sci. 2 (1993), 762-785. [Pg.223]

S. Sun, Reduced representation approach to protein tertiary structure prediction statistical potential and simulated annealing, J. Theor. Biol. 172 (1995), 13-32. [Pg.223]

P. Ulrich, W. Scott, W.F. van Gunsteren and A. Torda, Protein structure prediction force 6elds parametrization with quasi Newtonian dynamics. Proteins 27 (1997), 367-384. [Pg.224]

Chatfield C and A J CoHns 1980. Introduction to Multivariate Analysis. London, Chapman Hall. Desiraju G R 1997. Crystal Gazing Structure Prediction and Polymorphism. Sdence 278 404-405. Everitt B.S. 1993 Cluster Analysis. Chichester, John Wiley Sons. [Pg.521]

Gavezzotti A 1994. Are Crystal Structures Predictable Accounts of Chemical Research 27 309-314. [Pg.523]

Protein Structure Prediction, Sequence Analysis and Protein Folding... [Pg.525]

Rule-based Approaches Using Secondary Structure Prediction... [Pg.536]

Ihe rule-based approach to protein structure prediction is obviously very reliant on th quality of the initial secondary structure prediction, which may not be particularly accurate The method tends to work best if it is known to which structural class the protein belongs this can sometimes be deduced from experimental techniques such as circular dichroism... [Pg.537]

A Comparison of Protein Structure Prediction Pilethocls CASP-... [Pg.563]

CASP stands for Critical Assessment of techniques for protein Structure Prediction. [Pg.563]

Barton G J1996. Protein Sequence Alignment and Database Scanning. In Sternberg M E (Editor) Prote Structure Prediction - A Practical Approach. Oxford, IRL Press, pp. 31-63. [Pg.573]

Cuff IA and G J Barton 1999. Evaluation and Improvement of Multiple Sequence Methods for P Secondary Structure Prediction. Proteins Structure, Function and Genetics 34 508-519. [Pg.575]

Moult J, T Hubbard, K Fldelis and J T Pedersen 1999. Critical Assessment of Methods of Protein Structure Prediction (CASP) Round III. Proteins Structure, Function and Genetics Suppl. 3 2-6. [Pg.576]

GJ Barton. Protein sequence alignment and database scanning. In MJE Sternberg, ed. Protein Structure Prediction A Practical Approach. Oxford, UK IRE Press at Oxford Univ Press, 1998. [Pg.302]

I Wojcik, I-P Mornon, I Chomilier. New efficient statistical sequence-dependent structure prediction of short to medium-sized protein loops based on an exhaustive loop classification. I Mol Biol 289 1469-1490, 1999. [Pg.306]

WA Lim, A Hodel, RT Sauer, FM Richards. The crystal structure of a mutant protein with altered but improved hydrophobic core packing. Proc Natl Acad Sci USA 91 423-427, 1994. PB Harbury, B Tidor, PS Kim. Repacking proteins cores with backbone freedom Structure prediction for coiled coils. Pi oc Natl Acad Sci USA 92 8408-8412, 1995. [Pg.307]

MJE Sternberg, PA Bates, LA Kelley, RM MacCallum. Progress m protein structure prediction Assessment of CASP3. Curr Opm Struct Biol 9 368-373, 1999. [Pg.308]

DM Standley, JR Gunn, RA Friesner, AE McDermott. Tertiary structure prediction of mixed alpha/beta proteins via energy minimization. Proteins 33 240-252, 1998. [Pg.309]

J Moult, T Flubbard, SFI Bryant, K Fidelis, JT Pedersen. Critical assessment of methods of protein structure prediction (CASP) Round II. Proteins Suppl 1 2-6, 1997. [Pg.310]

RL Dunbrack Jr, DL Gerloff, M Bower, X Chen, O Lichtarge, FE Cohen. Meeting review The second meeting on the critical assessment of techniques for protein structure prediction (CASP2), Asilomar, CA, Dec 13-16, 1996. Folding Des 2 R27-R42, 1997. [Pg.310]

J Novotny, R Bruccoleri, M Karplus. An analysis of incorrectly folded protein models Implications for structural predictions. J Mol Biol 177 787-818, 1984. [Pg.310]

For example, Stolorz et al. [88] derived a Bayesian formalism for secondary structure prediction, although their method does not use Bayesian statistics. They attempt to find an expression for / ( j. seq) = / (seq j.)/7( j.)//7(seq), where J. is the secondary structure at the middle position of seq, a sequence window of prescribed length. As described earlier in Section II, this is a use of Bayes rule but is not Bayesian statistics, which depends on the equation p(Q y) = p(y Q)p(Q)lp(y), where y is data that connect the parameters in some way to observables. The data are not sequences alone but the combination of sequence and secondary structure that can be culled from the PDB. The parameters we are after are the probabilities of each secondary structure type as a function of the sequence in the sequence window, based on PDB data. The sequence can be thought of as an explanatory variable. That is, we are looking for... [Pg.338]

Thompson and Goldstein [89] improve on the calculations of Stolorz et al. by including the secondary structure of the entire window rather than just a central position and then sum over all secondary strucmre segment types with a particular secondary structure at the central position to achieve a prediction for this position. They also use information from multiple sequence alignments of proteins to improve secondary structure prediction. They use Bayes rule to fonnulate expressions for the probability of secondary structures, given a multiple alignment. Their work describes what is essentially a sophisticated prior distribution for 6 i(X), where X is a matrix of residue counts in a multiple alignment in a window about a central position. The PDB data are used to form this prior, which is used as the predictive distribution. No posterior is calculated with posterior = prior X likelihood. [Pg.339]

TJ Hubbard, J Park. Eold recognition and ab initio structure predictions using hidden Markov models and (I-strand pair potentials. Proteins Struct Eunct Genet 23 398-402, 1995. [Pg.347]

JE Gibrat, J Garnier, B Robson. Eurther developments of protein secondary structure prediction using information theory. New parameters and consideration of residue pairs. J Mol Biol 198 425-443, 1987. [Pg.347]

LH Holley, M Karplus. Protein secondary structure prediction with a neural network. Proc Natl Acad Sci USA 86 152-156, 1989. [Pg.348]


See other pages where Structured-prediction is mentioned: [Pg.11]    [Pg.105]    [Pg.518]    [Pg.524]    [Pg.528]    [Pg.536]    [Pg.537]    [Pg.561]    [Pg.578]    [Pg.578]    [Pg.247]    [Pg.214]    [Pg.275]    [Pg.280]    [Pg.294]    [Pg.306]    [Pg.336]   
See also in sourсe #XX -- [ Pg.4 , Pg.44 , Pg.48 , Pg.49 , Pg.53 , Pg.54 , Pg.57 ]




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3D structure prediction

A Classic Optimisation Problem Predicting Crystal Structures

A Comparison of Protein Structure Prediction Methods CASP

Ab initio prediction of protein structure

Accuracy of structure predictions

Advances in Crystal Structure Prediction and Applications to Pharmaceutical Materials

All-atom protein structure prediction

Amino acid sequences structure prediction from

Applications - Protein Structure Prediction

Applications of Crystal Structure Prediction

Are crystal structures predictable

Blind Tests of Crystal Structure Prediction

Boroxol Rings in Crystalline Structures Predictions of New B2O3 Polymorphs from First-Principles

Cambridge Crystallographic Data Centre crystal structure prediction blind tests

Carbamazepine structure prediction

Computational modeling structure prediction

Computational studies structure prediction

Conformational analysis crystal structures predicted

Conformations structure prediction models

Critical Assessment Structure Prediction

Critical Assessment of Structure Prediction

Critical Assessment of Techniques for Protein Structure Prediction

Critical Assessment of Techniques for Protein Structure Prediction (CASP

Crystal Structure Prediction Methodologies

Crystal structure prediction

Crystal structure prediction CCDC blind tests

Crystal structure prediction Monte Carlo methods

Crystal structure prediction Subject

Crystal structure prediction analysis

Crystal structure prediction applications

Crystal structure prediction assumption

Crystal structure prediction blind tests

Crystal structure prediction by computer

Crystal structure prediction clustering

Crystal structure prediction conformational analysis

Crystal structure prediction conformer selection

Crystal structure prediction defined

Crystal structure prediction intermolecular potential

Crystal structure prediction lattice energy calculation

Crystal structure prediction lattice energy minimization

Crystal structure prediction lattice vibrations

Crystal structure prediction molecular dynamics

Crystal structure prediction molecular flexibility

Crystal structure prediction molecular mechanics

Crystal structure prediction polymorphism

Crystal structure prediction search method

Crystal structure prediction solvates

Crystal structure prediction space groups

Crystal structure prediction stability ranking

Crystal structure prediction stoichiometry

Crystal structure prediction techniques used

Crystal structure prediction thermodynamics

Crystal structure prediction/control

Crystal structure, predicting

Crystal structures, predicted

Crystal symmetries structure predictions

Disulfides structure prediction

Electronic structure enthalpy predictions

Electronic structure geometric predictions

Electronic structure spectra predictions

Energy Calculations and Crystal Structure Predictions

Energy Calculations and Structure Predictions

Enthalpy predictions electronic structure calculations

Enzymes structure prediction

Expert system chemical structure prediction

First-principles Methods for Predicting Protein Structure

Free energy minimization, secondary structure prediction

Free energy predictions electronic structure calculations

Further Assessments of Crystal Structure Prediction

Gene structure prediction

Geometrical representation structure prediction

Hartree-Fock calculations and structure predictions

Homology modeling sequence-structure-function prediction

Homology modeling structure prediction

Knowledge-based prediction tertiary structure

Knowledge-based structural prediction

Learning for Protein Structure and Function Prediction

Ligand identification sequence-structure-function prediction

Macromolecular structures prediction

Methods for Structure Prediction

Molecular crystals structure predictions

Molecular modeling protein structure prediction

Motif-based secondary structure prediction

Online protein structure prediction

Organic crystal structure prediction

Pair interactions sequence-structure-function prediction

Peptides tertiary structure prediction

Performance in Structure Prediction

Poisson-Boltzmann equation structure prediction

Polypeptides structure-prediction methods

Predicting Biodegradation from Chemical Structure

Predicting Protein Tertiary Structure

Predicting Structures and Assigning Notations

Predicting Structures from Formulae

Predicting and Evaluating Crystal Structures

Predicting bulk structure-property relationships

Predicting structures

Predicting structures

Predicting the hyperfine structure of an EPR spectrum

Prediction Methods Based on 3-D Molecular Structure

Prediction from structural groups

Prediction of Molecular Structure-Property Relationships

Prediction of Open-framework Aluminophosphate Structures by using the AASBU Method with Lowensteins Constraints

Prediction of Organic Crystal Structure, Thermodynamics, and Solubility

Prediction of Protein Secondary Structures from Sequences

Prediction of Secondary Structure in Proteins

Prediction of Tertiary Structure

Prediction of crystal structures

Prediction of secondary and tertiary protein structure

Prediction of secondary structure

Prediction of structure

Prediction structure relationship

Prediction techniques sequence-structure-function

Prediction techniques structural reproducibility

Prediction techniques structure

Prediction techniques threaded structures

Prediction, structure-based

Predictions 1 Perfect Planar Structure

Predictions for Proteins with Known 3D Structure

Protein Secondary Structure Prediction Suite

Protein Structure Prediction in ID, 2D, and

Protein folding quaternary structure prediction

Protein folding tertiary structure prediction

Protein secondary structure prediction

Protein secondary structures predicting

Protein secondary structures structure prediction from

Protein structure predicting

Protein structure prediction

Protein structure prediction approaches

Protein structure prediction from

Protein structure prediction from amino acid sequences

Protein tertiary structure prediction

Proteomics prediction of protein structures

Quantitative structure-activity relationship prediction

Quantitative structure-activity relationships predicting with QSARs

Quantitative structure-activity relationships predictive models

Quantitative structure-retention relationships , predicting

Quantum mechanical structural predictions

Quaternary structure prediction, protein

Radius Ratios and Predicting Structure

Retention index prediction from structure

Secondary structural prediction, tertiary

Secondary structure prediction

Secondary structure prediction algorithm evaluation

Secondary structure prediction methods

Secondary structure predictions approaches

Secondary structures predicting

Shell predicting crystal structures

Skill 1.3c-Predict molecular geometries using Lewis dot structures and hybridized atomic orbitals, e.g., valence shell electron pair repulsion model (VSEPR)

Solvates structure prediction

Solvation energy models structure prediction

Statistical methods, structure prediction from sequence

Structural predictions

Structure Analysis and Prediction

Structure Prediction Methods

Structure Prediction and Molecular Docking

Structure Prediction from Sequence by Statistical Methods

Structure determination predictive methods

Structure predicting from mass spectra

Structure prediction

Structure prediction assessment

Structure prediction blind tests

Structure prediction flexible molecules

Structure prediction from infrared spectra

Structure prediction goals

Structure prediction search methods

Structure prediction techniques computational models

Structure prediction techniques free energy modeling

Structure prediction techniques identification

Structure prediction techniques polypeptides

Structure prediction techniques potential energy models

Structure prediction, from

Structure prediction, from sequence

Structure-property predictions

Structure-property predictions alternation

Tertiary protein structure knowledge-based prediction

Tertiary protein structure predictions, derivation from

Testing for false positive predictions in membrane and soluble proteins of crystallographically known structure

The Challenge of Affinity Prediction Scoring Functions for Structure-Based Virtual Screening

The Polymers Structure and Mechanical Properties Prediction

Tropomyosin structure prediction

Troponin structure prediction

Understanding and Predicting Protein Structure

Understanding and predicting stiffness in advanced fibre-reinforced polymer (FRP) composites for structural applications

VSEPR structures predicted/rationalized

Valence shell electron pair repulsion predicting molecular structure using

Valence shell electron-pair repulsion predicting molecular structure

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