Océane Cassan

STOIC : A machine-learning guided approach to explore the cis-regulatory code involved in neuronal differentiation.

A machine-learning guided approach to explore the cis-regulatory code involved in neuronal differentiation. Awarded Best Poster in the Regsys track.

Gene-specific optimization of data integration in regression-based Gene Regulatory Network inference.

Gene-specific optimization of data integration improves regression-based Gene Regulatory Network inference in Arabidopsis. Awarded Best Talk in the NetBio track.

Probing regulatory DNA sequence features at play during neuronal differentiation

Gene-specific optimization of data integration improves regression-based Gene Regulatory Network inference in Arabidopsis

GWAS identifies candidate polymorphisms involved in the mineral depletion of Arabidopsis under elevated CO2

Discussing the 2019 paper from Belkin et al. "Reconciling modern machine-learning practice and the classical bias–variance trade-off"

Presentation of DIANE, the Dashboard for the Inference and Analysis of Networks from Expression data.

Statistical inference of a gene regulatory network in Arabidopsis under the combination of elevated CO2 and nutritional limitations

Presentation of DIANE, the Dashboard for the Inference and Analysis of Networks from Expression data.