Dr. Charles Wang will address the need for guidance in selecting algorithms for accurate biological interpretations of varied data types acquired with different single-cell RNA sequencing platforms.

Dr. Noémie Elhadad will show how patient-record summation tools can help clinicians make sense of seemingly overwhelming amounts of patient data at the point of care.

Dr. Nicolas Fernandez will demonstrate the latest version of Clustergrammer2, a visualization tool that allows users to perform more refined clustering on cell lines and genes.

Dr. James Zou will present new computer vision algorithms and describe how these can help identify the morphologies and phenotypes associated with complex diseases, such as cancer. He will also discuss the general principles behind this technology as well as current machine learning tools, such as Ghorbani, NeurIPS 2020, Abid, and Nature MI 2020.