| 1 | Phyre2.2: A Community Resource for Template-based Protein Structure Prediction | 3.0 | 131 | Citations (PDF) |
| 2 | Missense3D-TM: Predicting the Effect of Missense Variants in Helical Transmembrane Protein Regions Using 3D Protein Structures | 3.0 | 14 | Citations (PDF) |
| 3 | Missense3D-PPI: A Web Resource to Predict the Impact of Missense Variants at Protein Interfaces Using 3D Structural Data | 3.0 | 20 | Citations (PDF) |
| 4 | Protein structure-based evaluation of missense variants: Resources, challenges and future directions | 4.8 | 15 | Citations (PDF) |
| 5 | The AlphaFold Database of Protein Structures: A Biologist’s Guide | 3.0 | 251 | Citations (PDF) |
| 6 | 3DLigandSite: structure-based prediction of protein–ligand binding sites | 11.2 | 53 | Citations (PDF) |
| 7 | GWYRE: A Resource for Mapping Variants onto Experimental and Modeled Structures of Human Protein Complexes | 3.0 | 7 | Citations (PDF) |
| 8 | Missense3D-DB web catalogue: an atom-based analysis and repository of 4M human protein-coding genetic variants | 1.9 | 69 | Citations (PDF) |
| 9 | Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation | 11.2 | 14 | Citations (PDF) |
| 10 | A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin | 1.0 | 16 | Citations (PDF) |
| 11 | Application of docking methodologies to modeled proteins | 1.9 | 42 | Citations (PDF) |
| 12 | PhyreRisk: A Dynamic Web Application to Bridge Genomics, Proteomics and 3D Structural Data to Guide Interpretation of Human Genetic Variants | 3.0 | 28 | Citations (PDF) |
| 13 | Identification of disease-associated loci using machine learning for genotype and network data integration | 3.2 | 10 | Citations (PDF) |
| 14 | Can Predicted Protein 3D Structures Provide Reliable Insights into whether Missense Variants Are Disease Associated? | 3.0 | 514 | Citations (PDF) |
| 15 | Phylotranscriptomic Insights into the Diversification of EndothermicThunnusTunas | 3.1 | 29 | Citations (PDF) |
| 16 | EzMol: A Web Server Wizard for the Rapid Visualization and Image Production of Protein and Nucleic Acid Structures | 3.0 | 172 | Citations (PDF) |
| 17 | PhenoRank: reducing study bias in gene prioritization through
simulation | 3.2 | 35 | Citations (PDF) |
| 18 | Structure-based prediction of protein allostery | 4.8 | 104 | Citations (PDF) |
| 19 | k-SLAM: accurate and ultra-fast taxonomic classification and gene identification for large metagenomic data sets | 11.2 | 54 | Citations (PDF) |
| 20 | Thienopyrimidinone Based Sirtuin-2 (SIRT2)-Selective Inhibitors Bind in the Ligand Induced Selectivity Pocket | 4.7 | 69 | Citations (PDF) |
| 21 | Predicting Protein Dynamics and Allostery Using Multi-Protein Atomic Distance Constraints | 2.5 | 50 | Citations (PDF) |
| 22 | Landscape of Pleiotropic Proteins Causing Human Disease: Structural and System Biology Insights | 1.0 | 40 | Citations (PDF) |
| 23 | ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology | 5.8 | 462 | Citations (PDF) |
| 24 | In Silico Analysis of the Small Molecule Content of Outer Membrane Vesicles Produced by Bacteroides thetaiotaomicron Indicates an Extensive Metabolic Link between Microbe and Host | 2.9 | 61 | Citations (PDF) |
| 25 | An expanded evaluation of protein function prediction methods shows an improvement in accuracy | 4.8 | 386 | Citations (PDF) |
| 26 | PhyreStorm: A Web Server for Fast Structural Searches Against the PDB | 3.0 | 15 | Citations (PDF) |
| 27 | Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types | 5.9 | 14 | Citations (PDF) |
| 28 | Genome3D: exploiting structure to help users understand their sequences | 11.2 | 47 | Citations (PDF) |
| 29 | The Contribution of Missense Mutations in Core and Rim Residues of Protein–Protein Interfaces to Human Disease | 3.0 | 134 | Citations (PDF) |
| 30 | A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic BrainsCell, 2014, 159, 1511-1523 | 23.8 | 744 | Citations (PDF) |
| 31 | SuSPect: Enhanced Prediction of Single Amino Acid Variant (SAV) Phenotype Using Network Features | 3.0 | 242 | Citations (PDF) |
| 32 | The Effects of Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) on Protein–Protein Interactions | 3.0 | 239 | Citations (PDF) |
| 33 | Proteins and Domains Vary in Their Tolerance of Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) | 3.0 | 38 | Citations (PDF) |
| 34 | Polyproline-II Helix in Proteins: Structure and Function | 3.0 | 556 | Citations (PDF) |
| 35 | Gene Function Hypotheses for the Campylobacter jejuni Glycome Generated by a Logic-Based Approach | 3.0 | 23 | Citations (PDF) |
| 36 | Protein flexibility, not disorder, is intrinsic to molecular recognition | 2.3 | 8 | Citations (PDF) |
| 37 | Protein flexibility, not disorder, is intrinsic to molecular recognition | 2.3 | 73 | Citations (PDF) |
| 38 | CombFunc: predicting protein function using heterogeneous data sources | 11.2 | 69 | Citations (PDF) |
| 39 | PINALOG: a novel approach to align protein interaction networks—implications for complex detection and function prediction | 3.2 | 89 | Citations (PDF) |
| 40 | Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains | 11.2 | 55 | Citations (PDF) |
| 41 | Assessment of a Rule-Based Virtual Screening Technology (INDDEx) on a Benchmark Data Set | 2.1 | 7 | Citations (PDF) |
| 42 | Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study | 2.5 | 13 | Citations (PDF) |
| 43 | Challenges for the prediction of macromolecular interactions | 4.8 | 85 | Citations (PDF) |
| 44 | Functional significance of mutations in the Snf2 domain of ATRX | 2.1 | 54 | Citations (PDF) |
| 45 | 3DLigandSite: predicting ligand-binding sites using similar structures | 11.2 | 593 | Citations (PDF) |
| 46 | Sequencing delivers diminishing returns for homology detection: implications for mapping the protein universe | 3.2 | 24 | Citations (PDF) |
| 47 | Protein Folding Requires Crowd Control in a Simulated Cell | 3.0 | 83 | Citations (PDF) |
| 48 | Discovering rules for protein-ligand specificity using support vector inductive logic programming | 2.2 | 8 | Citations (PDF) |
| 49 | Scaffold Hopping in Drug Discovery Using Inductive Logic Programming | 3.3 | 41 | Citations (PDF) |
| 50 | Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking | 5.3 | 217 | Citations (PDF) |
| 51 | Integrative Top-Down System Metabolic Modeling in Experimental Disease States via Data-Driven Bayesian Methods | 2.3 | 30 | Citations (PDF) |
| 52 | ConFunc—functional annotation in the twilight zone | 3.2 | 101 | Citations (PDF) |
| 53 | 3D-Garden: a system for modelling protein–protein complexes based on conformational refinement of ensembles generated with the marching cubes algorithm | 3.2 | 62 | Citations (PDF) |
| 54 | The Identification of Similarities between Biological Networks: Application to the Metabolome and Interactome | 3.0 | 32 | Citations (PDF) |
| 55 | Convergent Evolution of Enzyme Active Sites Is not a Rare Phenomenon | 3.0 | 131 | Citations (PDF) |
| 56 | A Novel Logic-Based Approach for Quantitative Toxicology Prediction | 3.3 | 41 | Citations (PDF) |
| 57 | Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB) | 1.1 | 2 | Citations (PDF) |
| 58 | A general approach for developing system‐specific functions to score protein–ligand docked complexes using support vector inductive logic programming | 1.9 | 31 | Citations (PDF) |
| 59 | Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds | 1.9 | 43 | Citations (PDF) |
| 60 | Capturing expert knowledge with argumentation: a case study in bioinformatics | 3.2 | 14 | Citations (PDF) |
| 61 | Prediction of viable circular permutants using a graph theoretic approach | 3.2 | 18 | Citations (PDF) |
| 62 | The proteome: structure, function and evolution | 2.6 | 18 | Citations (PDF) |
| 63 | Prediction of the conformation and geometry of loops in globular proteins: Testing ArchDB, a structural classification of loops | 1.9 | 22 | Citations (PDF) |
| 64 | The Relationship between the Flexibility of Proteins and their Conformational States on Forming Protein–Protein Complexes with an Application to Protein–Protein Docking | 3.0 | 169 | Citations (PDF) |
| 65 | Assessing Protein Co-evolution in the Context of the Tree of Life Assists in the Prediction of the Interactome | 3.0 | 133 | Citations (PDF) |
| 66 | 3D-GENOMICS: a database to compare structural and functional annotations of proteins between sequenced genomes | 11.2 | 14 | Citations (PDF) |
| 67 | Automated prediction of protein function and detection of functional sites from structure | 5.3 | 169 | Citations (PDF) |
| 68 | ArchDB: automated protein loop classification as a tool for structural genomics | 11.2 | 62 | Citations (PDF) |
| 69 | Clustering of Protein Domains in the Human Genome | 3.0 | 12 | Citations (PDF) |
| 70 | The Automatic Discovery of Structural Principles Describing Protein Fold Space | 3.0 | 22 | Citations (PDF) |
| 71 | Structural Characterization of the Human Proteome | 3.2 | 69 | Citations (PDF) |
| 72 | Evolution of Enzymes in Metabolism: A Network Perspective | 3.0 | 76 | Citations (PDF) |
| 73 | Prediction of protein–protein interactions by docking methods | 4.8 | 441 | Citations (PDF) |
| 74 | Automated discovery of structural signatures of protein fold and function11Edited by J. Thornton | 3.0 | 35 | Citations (PDF) |
| 75 | Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking | 3.0 | 230 | Citations (PDF) |
| 76 | A structural census of metabolic networks for E. coli 1 1Edited by B. Honig | 3.0 | 16 | Citations (PDF) |
| 77 | Title is missing! | 2.2 | 21 | Citations (PDF) |
| 78 | An approach to improving multiple alignments of protein sequences using predicted secondary structure | 2.2 | 28 | Citations (PDF) |
| 79 | SAWTED: Structure Assignment With Text Description--Enhanced detection of remote homologues with automated SWISS-PROT annotation comparisons | 3.2 | 58 | Citations (PDF) |
| 80 | Enhanced genome annotation using structural profiles in the program 3D-PSSM 1 1Edited by J. Thornton | 3.0 | 1,365 | Citations (PDF) |
| 81 | An analysis of conformational changes on protein–protein association: implications for predictive docking | 2.2 | 193 | Citations (PDF) |
| 82 | Benchmarking PSI-BLAST in genome annotation 1 1Edited by G. von Heijne | 3.0 | 107 | Citations (PDF) |
| 83 | Rapid refinement of protein interfaces incorporating solvation: application to the docking problem | 3.0 | 230 | Citations (PDF) |
| 84 | Automated classification of antibody complementarity determining region 3 of the heavy chain (H3) loops into canonical forms and its application to protein structure prediction | 3.0 | 81 | Citations (PDF) |
| 85 | Supersites within superfolds. Binding site similarity in the absence of homology 1 1Edited by J. Thornton | 3.0 | 228 | Citations (PDF) |
| 86 | Crystal structure at 1.95 å resolution of the breast tumour-specific antibody SM3 complexed with its peptide epitope reveals novel hypervariable loop recognition | 3.0 | 79 | Citations (PDF) |
| 87 | Conformational analysis of the first observed non-proline cis-peptide bond occurring within the complementarity determining region (CDR) of an antibody | 3.0 | 21 | Citations (PDF) |
| 88 | DSC: public domain protein secondary structure prediction | 3.2 | 40 | Citations (PDF) |
| 89 | An automated classification of the structure of protein loops | 3.0 | 194 | Citations (PDF) |
| 90 | Recognition of analogous and homologous protein folds: analysis of sequence and structure conservation 1 1Edited by F. E. Cohen | 3.0 | 207 | Citations (PDF) |
| 91 | Modelling protein docking using shape complementarity, electrostatics and biochemical information 1 1Edited by J. Thornton | 3.0 | 820 | Citations (PDF) |
| 92 | A novel binding site in catalase is suggested by structural similarity to the calycin superfamily | 2.2 | 7 | Citations (PDF) |
| 93 | A test of the applicability of small-molecule group additivity parameters in the estimation of fusion entropies of macromolecules | 2.6 | 1 | Citations (PDF) |
| 94 | Identification and analysis of domains in proteins | 2.2 | 114 | Citations (PDF) |
| 95 | A Continuum Model for Protein–Protein Interactions: Application to the Docking Problem | 3.0 | 158 | Citations (PDF) |
| 96 | COMPARISON OF ARTIFICIAL INTELLIGENCE METHODS FOR MODELING PHARMACEUTICAL QSARS | 1.7 | 38 | Citations (PDF) |
| 97 | Identification of sequence motifs from a set of porteins with related function | 2.2 | 25 | Citations (PDF) |
| 98 | On the use of machine learning to identify topological rules in the packing of β-strands | 2.2 | 12 | Citations (PDF) |
| 99 | Protien side-chain conformational entropy derived from fusion data-comparison with other empirical scales | 2.2 | 35 | Citations (PDF) |
| 100 | Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines | 1.9 | 63 | Citations (PDF) |
| 101 | Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines | 1.9 | 57 | Citations (PDF) |
| 102 | Application of scaled particle theory to model the hydrophobic effect: implications for molecular association and protein stability | 2.2 | 86 | Citations (PDF) |
| 103 | Application of machine learning to structural molecular biology | 2.6 | 32 | Citations (PDF) |
| 104 | Protein surface area defined | 31.3 | 39 | Citations (PDF) |
| 105 | New approaches to QSAR: Neural networks and machine learning | 0.1 | 29 | Citations (PDF) |
| 106 | Empirical Scale of Side-Chain Conformational Entropy in Protein Folding | 3.0 | 265 | Citations (PDF) |
| 107 | Autoimmune disease and molecular mimicry: an hypothesis | 7.4 | 66 | Citations (PDF) |
| 108 | Towards an automatic method of predicting protein stucture by homology: an evaluation of suboptimal sequence alignments | 2.2 | 19 | Citations (PDF) |
| 109 | Secondary structure prediction | 4.8 | 18 | Citations (PDF) |
| 110 | Modelling the structure and function of enzymes by machine learning | 2.7 | 19 | Citations (PDF) |
| 111 | The binding site on ICAM-1 for plasmodium falciparum-infected erythrocytes overlaps, but is distinct from, the LFA-1-binding site | 23.8 | 280 | Citations (PDF) |
| 112 | Prediction of structural and functional features of protein and nucleic acid sequences by artificial neural networks | 1.8 | 135 | Citations (PDF) |
| 113 | Evaluation of the sequence template method for protein structure prediction | 3.0 | 33 | Citations (PDF) |
| 114 | New algorithm to model protein-protein recognition based on surface complementarity | 3.0 | 152 | Citations (PDF) |
| 115 | A simple method to generate non-trivial alternate alignments of protein sequences | 3.0 | 43 | Citations (PDF) |
| 116 | Protein sequences — homologies and motifs | 8.0 | 4 | Citations (PDF) |
| 117 | Prediction of ATP-binding motifs: a comparison of a perceptron-type neural network and a consensus sequence method | 2.2 | 26 | Citations (PDF) |
| 118 | Library of common protein motifs | 31.3 | 12 | Citations (PDF) |
| 119 | PROMOT: a FORTRAN program to scan protein sequences against a library of known motifs | 3.2 | 11 | Citations (PDF) |
| 120 | A three-dimensional molecular template for substrates of human cytochrome P450 involved in debrisoquine 4-hydroxylation | 2.2 | 108 | Citations (PDF) |
| 121 | A predicted three-dimensional structure of human cytochrome P450: implications for substrate specificity | 2.2 | 71 | Citations (PDF) |
| 122 | A sequence motif in the transmembrane region of growth factor receptors with tyrosine kinase activity mediates dimerization | 2.2 | 144 | Citations (PDF) |
| 123 | Local protein sequence similarity does not imply a structural relationship | 2.2 | 24 | Citations (PDF) |
| 124 | Inter-species sequence conservation of single-spanning transmembrane regions | 2.2 | 3 | Citations (PDF) |
| 125 | Prediction of protein structure from sequence | 0.7 | 8 | Citations (PDF) |
| 126 | Machine learning approach for the prediction of protein secondary structure | 3.0 | 104 | Citations (PDF) |
| 127 | Flexible protein sequence patterns | 3.0 | 131 | Citations (PDF) |
| 128 | Prediction of β-turns in proteins using neural networks | 2.2 | 95 | Citations (PDF) |
| 129 | A predicted three-dimensional structure for the human immunodeficiency virus binding domains of CD4 antigen | 2.2 | 24 | Citations (PDF) |
| 130 | Neu receptor dimerization | 31.3 | 150 | Citations (PDF) |
| 131 | Similarity in membrane proteins | 31.3 | 90 | Citations (PDF) |
| 132 | A relational database of protein structures designed for flexible enquiries about conformation | 2.2 | 50 | Citations (PDF) |
| 133 | LOPAL and SCAMP: techniques for the comparison and display of protein structures | 2.8 | 21 | Citations (PDF) |
| 134 | Analysis and prediction of the location of catalytic residues in enzymes | 2.2 | 81 | Citations (PDF) |
| 135 | Evaluation and improvements in the automatic alignment of protein sequences | 2.2 | 110 | Citations (PDF) |
| 136 | Comparison of protein structural profiles by interactive computer graphics | 2.8 | 7 | Citations (PDF) |
| 137 | A strategy for the rapid multiple alignment of protein sequences | 3.0 | 471 | Citations (PDF) |
| 138 | Prediction of protein secondary structure and active sites using the alignment of homologous sequences | 3.0 | 454 | Citations (PDF) |
| 139 | Analysis of the relationship between side-chain conformation and secondary structure in globular proteins | 3.0 | 431 | Citations (PDF) |
| 140 | AIDS vaccine predictions | 31.3 | 50 | Citations (PDF) |
| 141 | Prediction of electrostatic effects of engineering of protein charges | 31.3 | 214 | Citations (PDF) |
| 142 | Three-dimensional structural aspects of the design of new protein molecules | 1.0 | 14 | Citations (PDF) |
| 143 | Computer-aided design in protein engineering | 8.0 | 27 | Citations (PDF) |
| 144 | The aging of the AlphaFold database | 5.9 | 1 | Citations (PDF) |
