These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

579 related articles for article (PubMed ID: 29309725)

  • 41. Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions.
    Liu Z; Su M; Han L; Liu J; Yang Q; Li Y; Wang R
    Acc Chem Res; 2017 Feb; 50(2):302-309. PubMed ID: 28182403
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Machine learning models for drug-target interactions: current knowledge and future directions.
    D'Souza S; Prema KV; Balaji S
    Drug Discov Today; 2020 Apr; 25(4):748-756. PubMed ID: 32171918
    [TBL] [Abstract][Full Text] [Related]  

  • 43. ChemBoost: A Chemical Language Based Approach for Protein - Ligand Binding Affinity Prediction.
    Özçelik R; Öztürk H; Özgür A; Ozkirimli E
    Mol Inform; 2021 May; 40(5):e2000212. PubMed ID: 33225594
    [TBL] [Abstract][Full Text] [Related]  

  • 44. SFCscore: scoring functions for affinity prediction of protein-ligand complexes.
    Sotriffer CA; Sanschagrin P; Matter H; Klebe G
    Proteins; 2008 Nov; 73(2):395-419. PubMed ID: 18442132
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Computationally predicting binding affinity in protein-ligand complexes: free energy-based simulations and machine learning-based scoring functions.
    Wang DD; Zhu M; Yan H
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32591817
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Prediction of 8-state protein secondary structures by a novel deep learning architecture.
    Zhang B; Li J; Lü Q
    BMC Bioinformatics; 2018 Aug; 19(1):293. PubMed ID: 30075707
    [TBL] [Abstract][Full Text] [Related]  

  • 47. WDL-RF: predicting bioactivities of ligand molecules acting with G protein-coupled receptors by combining weighted deep learning and random forest.
    Wu J; Zhang Q; Wu W; Pang T; Hu H; Chan WKB; Ke X; Zhang Y
    Bioinformatics; 2018 Jul; 34(13):2271-2282. PubMed ID: 29432522
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Persistent spectral hypergraph based machine learning (PSH-ML) for protein-ligand binding affinity prediction.
    Liu X; Feng H; Wu J; Xia K
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33837771
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Prediction of protein-ligand binding affinity with deep learning.
    Wang Y; Jiao Q; Wang J; Cai X; Zhao W; Cui X
    Comput Struct Biotechnol J; 2023; 21():5796-5806. PubMed ID: 38213884
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Convolutional neural network scoring and minimization in the D3R 2017 community challenge.
    Sunseri J; King JE; Francoeur PG; Koes DR
    J Comput Aided Mol Des; 2019 Jan; 33(1):19-34. PubMed ID: 29992528
    [TBL] [Abstract][Full Text] [Related]  

  • 51. GB-score: Minimally designed machine learning scoring function based on distance-weighted interatomic contact features.
    Rayka M; Firouzi R
    Mol Inform; 2023 Mar; 42(3):e2200135. PubMed ID: 36722733
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Learning protein-ligand binding affinity with atomic environment vectors.
    Meli R; Anighoro A; Bodkin MJ; Morris GM; Biggin PC
    J Cheminform; 2021 Aug; 13(1):59. PubMed ID: 34391475
    [TBL] [Abstract][Full Text] [Related]  

  • 53. DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network.
    Pu L; Govindaraj RG; Lemoine JM; Wu HC; Brylinski M
    PLoS Comput Biol; 2019 Feb; 15(2):e1006718. PubMed ID: 30716081
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.
    Ji B; He X; Zhai J; Zhang Y; Man VH; Wang J
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33758923
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Analysis of deep learning methods for blind protein contact prediction in CASP12.
    Wang S; Sun S; Xu J
    Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):67-77. PubMed ID: 28845538
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Effects of data quality and quantity on deep learning for protein-ligand binding affinity prediction.
    Fan FJ; Shi Y
    Bioorg Med Chem; 2022 Oct; 72():117003. PubMed ID: 36103795
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Predicting Drug-Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation.
    Lim J; Ryu S; Park K; Choe YJ; Ham J; Kim WY
    J Chem Inf Model; 2019 Sep; 59(9):3981-3988. PubMed ID: 31443612
    [TBL] [Abstract][Full Text] [Related]  

  • 58. PLANET: A Multi-objective Graph Neural Network Model for Protein-Ligand Binding Affinity Prediction.
    Zhang X; Gao H; Wang H; Chen Z; Zhang Z; Chen X; Li Y; Qi Y; Wang R
    J Chem Inf Model; 2024 Apr; 64(7):2205-2220. PubMed ID: 37319418
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Statistical and machine learning approaches to predicting protein-ligand interactions.
    Colwell LJ
    Curr Opin Struct Biol; 2018 Apr; 49():123-128. PubMed ID: 29452923
    [TBL] [Abstract][Full Text] [Related]  

  • 60. IGPRED: Combination of convolutional neural and graph convolutional networks for protein secondary structure prediction.
    Görmez Y; Sabzekar M; Aydın Z
    Proteins; 2021 Oct; 89(10):1277-1288. PubMed ID: 33993559
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 29.