The CFD General Notation System (CGNS) provides a general, portable, and extensible standard for the storage and retrieval of computational fluid dynamics (CFD) analysis data. CGNS is designed to facilitate the exchange of data between sites and applications, and to help stabilize the archiving of aerodynamic data.
Electron Gamma Shower (EGS) is a general purpose package for the Monte Carlo simulation of the coupled transport of electrons and photons in an arbitrary geometry for particles with energies from a few keV up to several TeV. Simulations can be performed in arbitrarily complex physical geometries, and a wide range of physical processes are modeled.
MPI Parallel Environment (MPE) is a software package for MPI (Message Passing Interface) programmers. It provides users with a number of useful tools for their MPI programs such as a set of profiling libraries that collect information about the behavior of MPI programs, graphical trace file analyzers, serializers, type checkers, collective operations validators, etc.
PDB2PQR is a Python software package that automates many of the common tasks of preparing structures for continuum electrostatics calculations, providing a platform-independent utility for converting protein files in PDB format to PQR format. These tasks include adding a limited number of missing heavy atoms to biomolecular structures, determining side-chain pKas, placing missing hydrogens, optimizing the protein for favorable hydrogen bonding, assigning charge and radius parameters from a variety of force fields.
APBS is a software package for the numerical solution of the Poisson-Boltzmann equation (PBE), one of the most popular continuum models for describing electrostatic interactions between molecular solutes in salty, aqueous media. Continuum electrostatics plays an important role in several areas of biomolecular simulation, including simulation of diffusional processes to determine ligand-protein and protein-protein binding kinetics, implicit solvent molecular dynamics of biomolecules, solvation and binding energy calculations to determine ligand-protein and protein-protein equilibrium binding constants and aid in rational drug design, and biomolecular titration studies.
ffnet is a fast and easy-to-use feed-forward neural network training solution for Python. You can use it to train, test, save, load, and use an artificial neural network with sigmoid activation functions. Any network connectivity without cycles is allowed (not only layered). Training can be performed with several optimization schemes, including genetic alorithm based optimization. There is access to exact partial derivatives of network outputs versus its inputs. Normalization of data is handled automatically by ffnet.