AmberTools is a set of programs for biomolecular simulation and analysis. They are designedto work well with each other, and with the “regular” Amber suite of programs. You can performmany simulation tasks with AmberTools, and you can do more extensive simulations with thecombination of AmberTools and Amber itself.

References in zbMATH (referenced in 57 articles , 1 standard article )

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  1. Afrasiabi, M.; Klippel, H.; Roethlin, M.; Wegener, K.: An improved thermal model for SPH metal cutting simulations on GPU (2021)
  2. T. L. Underwood, J. A. Purton, J. R. H. Manning, A. V. Brukhno, K. Stratford, T. Düren, N. B. Wilding, S. C. Parker: dlmontepython: A Python library for automation and analysis of Monte Carlo molecular simulations (2021) arXiv
  3. Delle Site, Luigi; Klein, Rupert: Liouville-type equations for the (n)-particle distribution functions of an open system (2020)
  4. Dryden, Ian L.; Kim, Kwang-Rae; Laughton, Charles A.; Le, Huiling: Principal nested shape space analysis of molecular dynamics data (2019)
  5. Niu, Rui-Juan; Zheng, Qing-Chuan; Zhang, Hong-Xing: Molecular dynamics simulations study of influence of Tyr422Ala mutation on transcriptional enhancer activation domain 4 (TEAD4) and transcription co-activators complexes (2019)
  6. Younes Nejahi; Mohammad Soroush Barhaghi; Jason Mick; Brock Jackman; Kamel Rushaidat; Yuanzhe Li; Loren Schwiebert; Jeffrey Potoff: GOMC: GPU Optimized Monte Carlo for the simulation of phase equilibria and physical properties of complex fluids (2019) not zbMATH
  7. Hinze, Thomas: The Java environment for nature-inspired approaches (JENA): a workbench for biocomputing and biomodelling enthusiasts (2018)
  8. Chen, Duan: Fractional Poisson-Nernst-Planck model for ion channels. I: Basic formulations and algorithms (2017)
  9. Griebel, Michael (ed.); Schüller, Anton (ed.); Schweitzer, Marc Alexander (ed.): Scientific computing and algorithms in industrial simulations. Projects and products of Fraunhofer SCAI (2017)
  10. Liang, Yihao; Xing, Xiangjun; Li, Yaohang: A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions (2017)
  11. Michael E. Fortunato, Coray M. Colina: pysimm: A python package for simulation of molecular systems (2017) not zbMATH
  12. Biyikli, Emre; To, Albert C.: Multiresolution molecular mechanics: adaptive analysis (2016)
  13. Dryden, Ian L.; Mardia, Kanti V.: Statistical shape analysis. With applications in R (2016)
  14. Gebbie-Rayet, J., Shannon, G., Loeffler, H.H., Laughton, C.A.: Longbow: A Lightweight Remote Job Submission Tool (2016) not zbMATH
  15. Kulik, Marta; Trylska, Joanna: Structural and energetic comparison of the complexes of aminoglycosides with the model of the ribosomal A-site (2016)
  16. Leimkuhler, Benedict; Shang, Xiaocheng: Adaptive thermostats for noisy gradient systems (2016)
  17. Preto, Jordane: Classical investigation of long-range coherence in biological systems (2016)
  18. Trȩdak, Przemysław; Rudnicki, Witold R.; Majewski, Jacek A.: Efficient implementation of the many-body reactive bond order (REBO) potential on GPU (2016)
  19. Mark James Abraham; Teemu Murtola; Roland Schulz; Szilárd Páll; Jeremy C.Smith; Berk Hess; Erik Lindahl: GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers (2015) not zbMATH
  20. Nicholas P. Bailey, Trond S. Ingebrigtsen, Jesper Schmidt Hansen, Arno A. Veldhorst, Lasse Bohling, Claire A. Lemarchand, Andreas E. Olsen, Andreas K. Bacher, Lorenzo Costigliola, Ulf R. Pedersen, Heine Larsen, Jeppe C. Dyre, Thomas B. Schroder: RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles (2015) arXiv

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