Search Results for "python neural network"
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Showing 11 open source projects for "python neural network"
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GNNePCSAFT
Smart Thermodynamic Modeling with Graph Neural Networks
Our project harnesses the power of Graph Neural Network (GNN) to estimate pure-component parameters of the state-of-the-art Equation of State, PC-SAFT. We aim to empower users to leverage this robust equation without the need for prior experimental data, revolutionizing the calculation of thermodynamic properties and enhancing process simulations. FeOS is used for the PC-SAFT calculations. The estimated parameters can be used in DWSIM and Aspen HYSYS process simulators. -
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Pysces
PySCeS is the Python Simulator of Cellular Systems
PySCeS is the Python Simulator of Cellular Systems. For a network of coupled reactions it does a stoichiometric matrix analysis, calculates the time course and steady state, and does a complete control analysis. -
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Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It can be used from MATLAB, Python, C++, or Fortran.
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labman2
A web database for experimental results of research
A database with a web interface for storing the experimental results of research, aimed at ease of adding new types of data. Goal is to make adding as simple as one day for an unexperienced in programming scientist to add a new type of data similar to an existing type, by preparing two - three files analogues to the existing ones. An experienced programmer should need only one day to one week for adding a totally new kind of data like arrays with more dimensions that was available before. -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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CRP - Chemical Reaction Prediction
Predicting Organic Reactions using Neural Networks.
The intend is to solve the forward-reaction prediction problem, where the reactants are known and the interest is in generating the reaction products using Deep learning. This Graphical User Interface takes simplified molecular-input line-entry system (SMILES) as an input and generates the product SMILE & molecule. Beam search is used in Version 2, to generate top 5 predictions. Maximum input length for the model is 15 (excluding spaces). -
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RDKit
Open-Source Cheminformatics and Machine Learning
A collection of cheminformatics and machine-learning software written in C++ and Python. NOTE: the RDKit source code and downloads are now in github: https://github.com/rdkit/rdkit The core algorithms and data structures are written in C++. Wrappers are provided to use the toolkit from either Python or Java. Additionally, the RDKit distribution includes a PostgreSQL-based cartridge that allows molecules to be stored in relational database and retrieved via substructure and similarity... -
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Alchemy Linux
A linux distribution for chemists
Alchemy Linux is a Linux distribution (based on Fedora) for chemists (and mathematicians and physicists). This remix comes with a whole set of packages to help with experiments, simulations and publications. (This project is not maintained or endorsed by Red Hat or the Fedora project). -
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WISP
Weighted Implementation of Suboptimal Paths (WISP)
UPDATE: LATEST VERSION AT http://git.durrantlab.com//jdurrant/wisp Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site often many angstroms away. Traditionally, computational efforts have focused on the most optimal path... -
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UPDATE: The latest version of NNScore1 can be found here: http://git.durrantlab.com/jdurrant/nnscore1 The latest version of NNScore2 can be found here: http://git.durrantlab.com/jdurrant/nnscore2 ================ NNScore is a scoring function for characterizing the potency of receptor-ligand complexes. It is based on neural networks, computational models that simulate the microscopic organization of the brain.
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A univariate and multivariate analysis UI. This project is no longer under development. Please use as you wish.
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