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Automated Data Analysis for Chiral Pooling with a YOLO Machine Learning Model
Automated Data Analysis for Chiral Pooling with a YOLO Machine Learning Model
Chiral pooling enables efficient screening, but data analysis remains a bottleneck. This poster presents a YOLO-based machine learning workflow that automates chromatographic peak detections, transforming hours of manual analysis into minutes.
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Integrating Hit Finding and Direct-to-Biology to Shorten Time to Development Candidate
Integrating Hit Finding and Direct-to-Biology to Shorten Time to Development Candidate
Helicases have been implicated in the progression of microsatellite instability-high (MSI-H) tumors and therefore represent…
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Why Early Process Chemistry Matters?
Why Early Process Chemistry Matters?
Build Scalable Chemistry from Day One With Early Process Chemistry Early-stage medicinal chemistry is…
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Rapid Deployment of HTS, Delivering Validated Hits for a Helicase
Rapid Deployment of HTS, Delivering Validated Hits for a Helicase
Helicases are important enzymes in the progression of microsatellite instability-high (MSI-H) tumors. Despite…
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Electrophysiological Characterization of iPSC-Deriver RealDRGx Sensory Neurons
Electrophysiological Characterization of iPSC-Deriver RealDRGx Sensory Neurons
Human dorsal root ganglion (DRG) neurons are central to sensing pain and environmental stimuli but…
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