emmaking-smith/HiTEA
The High Throughput Experimentation Analyzer (HiTEA) modules as described in "Probing the Chemical 'Reactome' with High Throughput Experimentation Data" (King-Smith et al.).
This helps chemists and materials scientists analyze data from high-throughput experiments, which generate large datasets from many reactions. You input your experimental reaction data, and it helps identify which variables (like reactants or catalysts) are most important for reaction outcomes, and visualize the chemical space. This is ideal for researchers in chemical R&D looking to understand and optimize reaction conditions.
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Use this if you conduct high-throughput chemical experiments and need to systematically analyze the factors influencing your reaction yields or selectivities.
Not ideal if you are analyzing small-scale, traditional lab experiments or looking for a general-purpose statistical analysis tool outside of chemical reaction data.
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Language
Python
License
MIT
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Last pushed
Feb 12, 2024
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