Deadline: 2019-01-03 Award: $37,000 Open to: Everyone*
Historically, classification of cell proteins has been limited to single patterns in one or a few cell types, but in order to fully understand the complexity of the human cell, models must classify mixed patterns across a range of different human cells.
Images visualizing proteins in cells are commonly used for biomedical research, and these cells could hold the keys for the next breakthrough in medicine. However, thanks to advances in high-throughput microscopy, these images are generated at a far greater pace than what can be manually evaluated. Therefore, the need is greater than ever for automating biomedical image analysis to accelerate the understanding of human cells and disease.
The Human Protein Atlas Image Classification calls on participants to train machine learning models to classify the patterns of protein expression within images of human cells. Creators of the best algorithms will split $37,000 in cash provided by Leica Microsystems, and an NVIDIA Quadro GV100 GPU.