Learning perturbation responses in high-throughput morphological assays through deep generative models - CONFIDENTIAL

Palma, A.

LIACS Thesis Repository

These webpages contain theses and reports by students affiliated with the various bachelor and master programmes offered at the Leiden Institute of Advanced Computer Science (LIACS), the computer science and artificial intelligence department of Leiden University.
Note: this thesis repository might be incomplete for certain programmes.

Master Computer Science

The following thesis was written by a student in the 2021-2022 class of the Master Computer Science programme at Leiden University.

Thesis details

Title	Learning perturbation responses in high-throughput morphological assays through deep generative models - CONFIDENTIAL
Student	Palma, A.
Programme	Master Computer Science
Year	2021-2022
Supervisors	Wolstencroft, dr. K.J. (Katy) Mohammad Lotfollahi (second supervisor)

Citation details

Palma, A., Learning perturbation responses in high-throughput morphological assays through deep generative models - CONFIDENTIAL, Thesis Master Computer Science, LIACS, Leiden University, 2022.