36 citations · 47 across the 5 of their papers we have counts for
5 papers
Effective Biological Representation Learning by Masking Gene Expression
Kian Kenyon-Dean, Alina Selega, Ihab Bendidi +5
RNA sequencing produces rich and diverse datasets of gene expression, offering compelling insights into cellular state and function that have many applications in drug discovery. M…
RxRx3-core: Benchmarking drug-target interactions in High-Content Microscopy
Oren Kraus, Federico Comitani, John Urbanik +6
High Content Screening (HCS) microscopy datasets have transformed the ability to profile cellular responses to genetic and chemical perturbations, enabling cell-based inference of…
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik +10
Large-scale cell microscopy screens are used in drug discovery and molecular biology research to study the effects of millions of chemical and genetic perturbations on cells. To us…
Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology
Oren Kraus, Kian Kenyon-Dean, Saber Saberian +14
Featurizing microscopy images for use in biological research remains a significant challenge, especially for large-scale experiments spanning millions of images. This work explores…
Masked Autoencoders are Scalable Learners of Cellular Morphology
Oren Kraus, Kian Kenyon-Dean, Saber Saberian +13
Inferring biological relationships from cellular phenotypes in high-content microscopy screens provides significant opportunity and challenge in biological research. Prior results…