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ACS2023 / Lab1-Template
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This repository is to brainstorm,and organize ideas to apply machine learning algorithms to meaningful biological problems. One of our focus is predicting genetic/physical interactions between unknown genes pairs in budding yeast. We would like to extend this analysis to multiple knockout mutants.
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This contains codes and workflows for data analysis regarding SATAY experiments.
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Giacomo Marangoni / spatial-data-science
MIT License[EPA122A] Spatial Data Science Course offered at TU Delft
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