Integrating machine learning methods to single-cell experimental workflow increases throughput and accuracy for target identification in immuno-oncology

Marielle Péré (1, 2) , Diego Oyarzun (3) , Asma Chalabi (2, 4) , Madalena Chaves (1) , Jérémie Roux (2, 1)

1 BIOCORE - Biological control of artificial ecosystems
2 IRCAN - Institut de Recherche sur le Cancer et le Vieillissement
3 School of Informatics [Edimbourg]
4 MORPHEME - Morphologie et Images

Domaines: Apprentissage [cs.LG]; Cancer; Intelligence artificielle [cs.AI]; Biotechnologie; Modélisation et simulation; Biologie cellulaire; Pharmacologie

Marielle Péré, Diego Oyarzun, Asma Chalabi, Madalena Chaves, Jérémie Roux. Integrating machine learning methods to single-cell experimental workflow increases throughput and accuracy for target identification in immuno-oncology. Sophia Summit AI, Nov 2022, Sophia Antipolis, France. ⟨hal-03868554⟩