Data Science and AI

(1011-D) Advancing Phenotypic Drug Hunting: AI for Biologists

(1045-B) Exploring relationships of gene function and chemical regulators using JUMP Cell Painting Consortium data

(1130-C) A machine learning-assisted image-based profiling methodology for phenotypic drug discovery

(1137-B) Label-free High-Throughput Viability Analysis using Advanced Machine Learning Algorithms

(1162-C) Nuclei Segmentation on Brightfield Images using a pre-trained Artificial Intelligence (AI) Model

(1197-B) A Graphical User Interface for ML-Based Modeling of Single-Cell and Well-Level Imaging Data

(1206-C) Absolute quantification of polar analytes using machine learning and StandardCandlesTM as universal calibrators

(1218-C) Application of parallel machine learning methodologies to surface mechanistically distinct classes of compound hits in a high-content imaging screen for inflammasome inhibitors

(1230-C) Automatic Assignment of Biacore SPR and Octet BLI Kinetic Binding Curve Profiles with Artificial Intelligence.

(1254-C) Deciphering Cellular Mechanisms through Phenotype: CRISPR-Induced Perturbations Analyzed through Cell Painting and Machine Learning

(1256-A) Deep Learning-based Morphological Profiling as a Screening Method for Human Macrophage Polarization Modulators

(1274-C) DiscoveryAI SAFIRE: a collection of machine learning models to predict ADMET liabilities for small molecule drug discovery

(1321-B) Informatics resources and databases to support identification of E3 ligase ligands using machine learning

(1338-C) Mastering complex challenges in controlled substance compliance using advanced Markush and similarity search technologies

(1350-C) NCATS OpenData Portal: a scalable open science platform to share and explore SARS-CoV-2 screening data

(1371-D) Scalable Instrument Data Management and Integration Using Standards and Patterns

(1373-B) Scheduling methods for streamlining and designing laboratory automation