2020 Virtual Poster Presentations:

P01: A New Data Container Construct Enables Rapid Processing of Analytical Data to Support High-Throughput Chemistry, Presented by Richard L., Advanced Chemistry Development, Inc. (ACD/Labs)

P02: Predicting Antibody Developability from Sequence Using Machine Learning, Presented by Ian K., Dassault Systemes

P03: Columbia University Case Study: A Research Platform for Academic-Industry Collaboration, Presented by Can A., Flywheel Exchange, LLC

P04: Applying Deep Learning for High Content Image Analysis, Presented by Spencer C., Genedata, Inc.

P05: Completing End-to-End Assay Automation with Automated Data Analysis, Presented by Renee E., Genedata, Inc.

P06: Using Chest CT Image Annotations to Predict Tuberculosis Patient Treatment Outcomes: Leveraging Real World Clinical Data in TB Portals with Data Science, Presented by Gabriel R., National Institutes of Health, National Institute of Allergy and Infectious Diseases

P07: RAPT: A Stand-Alone Pipeline to Assemble and Annotate Proteins on Bacterial Genomes, Presented by Dave A., National Institutes of Health, National Library of Medicine

P08: ElasticBLAST, Presented by Christiam C., National Institutes of Health, National Library of Medicine

P09: BLAST in a Container, Presented by Thomas M., National Institutes of Health, National Library of Medicine

P10: Machine Learning for Drug Discovery with Variable Reduction and De Novo Generation, Presented by Taotao T., New York University

P11: NCSA Industry Uses Multiple Techniques to Solve Complex Large-Scale Biological Questions, Presented by Christina F., University of Illinois at Urbana–Champaign, NCSA

P12: Tumor Growth Following Genetic Modifications of Mouse Prostate Tumor Cells, Presented by Robert A., Western Reserve Academy




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