scholarly article | Q13442814 |
P50 | author | Andrzej Kloczkowski | Q118958796 |
Yaoqi Zhou | Q37372227 | ||
P2093 | author name string | Eshel Faraggi | |
P2860 | cites work | The Protein Data Bank | Q24515306 |
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs | Q24545170 | ||
Amino acid substitution matrices from protein blocks | Q24563220 | ||
Characterization of protein-protein interfaces | Q24653393 | ||
Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure prediction | Q24655241 | ||
PISCES: recent improvements to a PDB sequence culling server | Q24812503 | ||
Protein secondary structure prediction based on position-specific scoring matrices | Q27860483 | ||
Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features | Q27860675 | ||
The interpretation of protein structures: Estimation of static accessibility | Q27860750 | ||
Combining prediction of secondary structure and solvent accessibility in proteins | Q28239844 | ||
Environment and exposure to solvent of protein atoms. Lysozyme and insulin | Q28245387 | ||
BLOSUM62 miscalculations improve search performance | Q28271956 | ||
Where did the BLOSUM62 alignment score matrix come from? | Q28275059 | ||
Critical assessment of methods of protein structure prediction (CASP)--round IX | Q29048192 | ||
Prediction of protein secondary structure at better than 70% accuracy | Q29547323 | ||
Application of multiple sequence alignment profiles to improve protein secondary structure prediction | Q29614377 | ||
PISCES: a protein sequence culling server | Q29615860 | ||
A sequence‐based computational model for the prediction of the solvent accessible surface area for α‐helix and β‐barrel transmembrane residues | Q30155468 | ||
Prediction of coordination number and relative solvent accessibility in proteins. | Q30330076 | ||
Accurate prediction of solvent accessibility using neural networks-based regression. | Q30342423 | ||
QBES: predicting real values of solvent accessibility from sequences by efficient, constrained energy optimization. | Q30353222 | ||
A global machine learning based scoring function for protein structure prediction. | Q30355895 | ||
Characterization of local geometry of protein surfaces with the visibility criterion. | Q30365524 | ||
Real-value prediction of backbone torsion angles. | Q30367302 | ||
GENN: a GEneral Neural Network for learning tabulated data with examples from protein structure prediction. | Q30369671 | ||
Solvent accessible surface area approximations for rapid and accurate protein structure prediction. | Q30375090 | ||
Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design | Q30431598 | ||
Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information | Q33287800 | ||
Derivatives of molecular surface area and volume: simple and exact analytical formulas | Q33927779 | ||
Improved prediction of protein secondary structure by use of sequence profiles and neural networks | Q34353245 | ||
SPINE X: improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles | Q35618898 | ||
Protein surface analysis for function annotation in high-throughput structural genomics pipeline | Q36476631 | ||
Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network. | Q37083941 | ||
Potential for protein surface shape analysis using spherical harmonics and 3D Zernike descriptors | Q37517294 | ||
Assessment of a novel scoring method based on solvent accessible surface area descriptors | Q43113439 | ||
Prediction of protein accessible surface areas by support vector regression | Q45070147 | ||
Hydrophobic bonding and accessible surface area in proteins | Q47881268 | ||
A two-stage classifier for identification of protein-protein interface residues | Q48533566 | ||
Prediction and evolutionary information analysis of protein solvent accessibility using multiple linear regression | Q51353182 | ||
Analytical shape computation of macromolecules: I. molecular area and volume through alpha shape | Q51647257 | ||
Analysis and prediction of RNA-binding residues using sequence, evolutionary conservation, and predicted secondary structure and solvent accessibility | Q51652208 | ||
Accurate prediction of protein folding rates from sequence and sequence-derived residue flexibility and solvent accessibility | Q51699017 | ||
On the relation between residue flexibility and local solvent accessibility in proteins | Q51775528 | ||
Real-SPINE: an integrated system of neural networks for real-value prediction of protein structural properties | Q51918600 | ||
Real value prediction of solvent accessibility in proteins using multiple sequence alignment and secondary structure. | Q51966304 | ||
Real value prediction of solvent accessibility from amino acid sequence | Q52022851 | ||
Amino acid hydrophobicity and accessible surface area | Q56428959 | ||
P433 | issue | 11 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | Accessible surface area | Q3622068 |
P304 | page(s) | 3170-3176 | |
P577 | publication date | 2014-09-25 | |
P1433 | published in | Proteins | Q7251514 |
P1476 | title | Accurate single-sequence prediction of solvent accessible surface area using local and global features | |
P478 | volume | 82 |
Q30394568 | Accurate Prediction of One-Dimensional Protein Structure Features Using SPINE-X. |
Q47281430 | Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains |
Q64264248 | Effects of Lid 1 Mutagenesis on Lid Displacement, Catalytic Performances and Thermostability of Cold-active Pseudomonas AMS8 Lipase in Toluene |
Q30394577 | Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile |
Q29306580 | FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues |
Q30400541 | Improving prediction of burial state of residues by exploiting correlation among residues |
Q40214668 | Logistic regression models to predict solvent accessible residues using sequence- and homology-based qualitative and quantitative descriptors applied to a domain-complete X-ray structure learning set. |
Q35906471 | PredRSA: a gradient boosted regression trees approach for predicting protein solvent accessibility |
Q60920804 | Reoptimized UNRES Potential for Protein Model Quality Assessment |
Q90064926 | SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences |
Q91708289 | Sequence-Derived Markers of Drug Targets and Potentially Druggable Human Proteins |
Search more.