Search Results for "multi"

PUPIL (Program for User Package Interface and Linking), is a software environment that allows developers to link quickly and efficiently together multiple pieces of software in a fully automated multi-scale simulation. More specifically, it supports QM/MM MD simulations where the user might choose among any of the different MD engines and QM engines, which are connected to PUPIL as external programs through a tiny specific interface. One of the main advantages here is that the user can use most of the functionalities that may have those external programs interfaced without the necessity to be reimplemented again on independent interfaces. ...

An open-source software to convert SDF files into TINKER XYZ files (and viceversa) with automatic assignment of MMFF94 atom types, bond types and charges

The Gecko Hamaker open-source software project is a full implementation of the fully retarded Lifshitz formulations for isotropic and anisotropic plane-plane and cylinder-cylinder interactions with intervening interlayer materials, planar systems of up to 99 layers, and graded interfaces for the modeling of grain boundaries or other continuously changing systems, accompanied by a database of material optical properties spectra. The machine-readable optical property database is available...

MDcore is an Open-Source library implementing the core functionality of a Molecular Dynamics engine. The engine is inherently multi-threaded and runs efficiently on multi-processor/multi-core shared-memory architectures.

CellMC is a multi-platform XSLT-based SBML compiler producing executable SSA models based on the optimised direct method.

Noemol is a graphical program for calculation of multi-spin nuclear Overhauser effects (nOes) in nuclear magnetic resonance (NMR) spectroscopy, it is a valuable tool for scientists involved in structural biology and chemistry.

Tools to build molecular-docking activity prediction models by PLS regression with iterative training and pose-selection. Descriptors include (i) docking score(s), (ii) pharmacophore features, (iii) multi-feature descriptors learned by decision trees.