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.
3. Accelerating molecular simulations of proteins using Bayesian inference on weak information. Perez A; MacCallum JL; Dill KA Proc Natl Acad Sci U S A; 2015 Sep; 112(38):11846-51. PubMed ID: 26351667 [TBL] [Abstract][Full Text] [Related]
4. Protein structure modeling and refinement by global optimization in CASP12. Hong SH; Joung I; Flores-Canales JC; Manavalan B; Cheng Q; Heo S; Kim JY; Lee SY; Nam M; Joo K; Lee IH; Lee SJ; Lee J Proteins; 2018 Mar; 86 Suppl 1():122-135. PubMed ID: 29159837 [TBL] [Abstract][Full Text] [Related]
5. Physics-based protein structure refinement in the era of artificial intelligence. Heo L; Janson G; Feig M Proteins; 2021 Dec; 89(12):1870-1887. PubMed ID: 34156124 [TBL] [Abstract][Full Text] [Related]
6. Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14. Zheng W; Li Y; Zhang C; Zhou X; Pearce R; Bell EW; Huang X; Zhang Y Proteins; 2021 Dec; 89(12):1734-1751. PubMed ID: 34331351 [TBL] [Abstract][Full Text] [Related]
7. Trajectory-based training enables protein simulations with accurate folding and Boltzmann ensembles in cpu-hours. Jumper JM; Faruk NF; Freed KF; Sosnick TR PLoS Comput Biol; 2018 Dec; 14(12):e1006578. PubMed ID: 30589834 [TBL] [Abstract][Full Text] [Related]
8. The trRosetta server for fast and accurate protein structure prediction. Du Z; Su H; Wang W; Ye L; Wei H; Peng Z; Anishchenko I; Baker D; Yang J Nat Protoc; 2021 Dec; 16(12):5634-5651. PubMed ID: 34759384 [TBL] [Abstract][Full Text] [Related]
9. Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning. Adhikari B; Hou J; Cheng J Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):84-96. PubMed ID: 29047157 [TBL] [Abstract][Full Text] [Related]
18. Assessment of the utility of contact-based restraints in accelerating the prediction of protein structure using molecular dynamics simulations. Raval A; Piana S; Eastwood MP; Shaw DE Protein Sci; 2016 Jan; 25(1):19-29. PubMed ID: 26266489 [TBL] [Abstract][Full Text] [Related]
19. Machine learning/molecular dynamic protein structure prediction approach to investigate the protein conformational ensemble. Audagnotto M; Czechtizky W; De Maria L; Käck H; Papoian G; Tornberg L; Tyrchan C; Ulander J Sci Rep; 2022 Jun; 12(1):10018. PubMed ID: 35705565 [TBL] [Abstract][Full Text] [Related]
20. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model. Wang S; Sun S; Li Z; Zhang R; Xu J PLoS Comput Biol; 2017 Jan; 13(1):e1005324. PubMed ID: 28056090 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]