Calibration-free quantification and automated data analysis for high-throughput reaction screening

2024/12/17 by Felix Katzenburg, Florian Boser, Felix Schäfer +2 · 2 voices · 1 citation
Computer Science · #Computational Drug Discovery Methods

paper · pdf · doi:10.1039/d4dd00347k

Abstract

Calibration-free quantitative analysis for high-throughput reaction screening using pyGecko: an open-source Python library for GC-MS and GC-FID data analysis.

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• Yield Prediction of Organic Reactions in Biased Data Sets via Positive-Unlabeled Learning

Discussions

• What a catch! 🎣 Huge congratulations to @boser-florian.bsky.social for winning the first place poster prize at this year’s @accelerationc.bsky.social Conference in Toronto awarded by @digital-disco [bsky, 8 points, 0 comments]
• You want to get HTE yields (fast)?🚀 Check out our calibration-free quantification for HTE in Digital Discovery, featuring pyGecko 🦎—our open-source Python library for rapid and automated GC data ana [bsky, 1 points, 0 comments]

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