Congratulations to Justin Hong and Achille Nazaret, two PhD students in computer science (Azizi lab), who won the first prize award in the GSK.ai CausalBench Challenge. The CausalBench Challenge invites the machine-learning community to advance the state-of-the-art in deriving gene–gene networks from large-scale real-world perturbational single-cell datasets to improve our ability to glean causal insights into disease-relevant biology. The winners of the challenge were announced on May 5th, during the 2023 Machine Learning for Drug Discovery Workshop at the 11th International Conference on Learning Representations (ICLR).
Justin Hong and Achille Nazaret's project aimed to enhance the derivation of gene-gene interaction networks from single-cell datasets using machine learning techniques. They developed a novel algorithm that improved upon existing graph inference methods by leveraging perturbational single-cell data to identify causal gene-gene interactions. Justin presented the method at the workshop.