Search Results for "python source"
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8 projects for "python source" with 2 filters applied:
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APBS
Biomolecular electrostatics software
This software has moved to http://www.poissonboltzmann.org/. -
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Avogadro
An intuitive molecular editor and visualization tool
Avogadro is an advanced molecular editor designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science and related areas. It offers a flexible rendering framework and a powerful plugin architecture. -
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pyxaid
PYthon eXtension for Ab Initio Dynamics
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Deploy Apps in Seconds with Cloud RunCloud Run is the fastest way to deploy containerized apps. Push your code in Go, Python, Node.js, Java, or any language and Cloud Run builds and deploys it automatically. Get fast autoscaling, pay only when your code runs, and skip the infrastructure headaches. Two million requests free per month. And new customers get $300 in free credit.
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quichem
Utilities for fast input of chemical formulae and equations.
*** New releases of quichem will only be available on GitHub. *** quichem is a utility written in pure Python allowing for fast input and parsing of chemical formulae and equations. Entering data does not require any modifier keys or keystrokes to be pressed. This SourceForge page provided pre-built Windows binaries of quichem-pyside. **To run quichem on Mac OS X or Linux**, or with the wxPython front-end, please download the source from quichem's GitHub page at: github.com/spamalot/quichem. -
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ASCEND is a modelling environment and solver for large or small systems of non-linear equations, for use in engineering, thermodynamics, chemistry, physics, mathematics and biology. Solvers for both steady and dynamic (NLA & DAE) problems, are provid
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Viewmol is a graphical front end for computational chemistry programs. It is able to graphically aid in the generation of molecular structures for computations and to visualize their results.
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ABE is a small, fast and convenient program for visualizing and modeling experimental bioassay data. The data can be modeled using either polynomials or a more specific four-parameter model based upon the standard, sigmoidal dose-response curve.
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