Feel free to use these slides and their content for any purpose under the cc-by license.
Student presentations (10 mins + 5 mins Q&A) on selected papers:
May 11, 2022, Noam Siegel (M.Sc. CS): Wang, Xu, Wang, et al. Hierarchical deep reinforcement learning reveals a modular mechanism of cell movement. Nat Mach Intell (2022). https://doi.org/10.1038/s42256-021-00431-x
May 25, 2022, Yonatan Yaniv (B.Sc. cognitive sciences): Méndez-Lucio et al. Cell morphology-guided de novo hit design by conditioning generative adversarial networks on phenotypic image features. ChemRxiv (2020). 10.26434/chemrxiv.11594067.v1
May 25, 2022, Edo Lior & Ido Rom (M.Sc. ISE): Janssens et al. Fully unsupervised deep mode of action learning for phenotyping high-content cellular images. Bioinformatics (2021). https://doi.org/10.1093/bioinformatics/btab497
June 1, 2022, Itay Almoznino & Netanel Sabah (M.Sc. ISE): Wang, Xie and Ji. Global voxel transformer networks for augmented microscopy. Nature Machine Intelligence (2021).
June 8, 2022, Ophir Almagor & Ofer Avin (M.Sc. Cognition): Doan, et al. Objective assessment of stored blood quality by deep learning. Proceedings of the National Academy of Sciences (2020). https://www.pnas.org/content/117/35/21381
June 15, 2022, Wei Wu (M.Sc. ISE): Saberian et al. DEEMD: Drug Efficacy Estimation Against SARS-CoV-2 Based on Cell Morphology with deep multiple instance learning. IEEE Trans Med Imaging (2022). https://ieeexplore.ieee.org/document/9783182
June 15, 2022, Adi Nissim (M.Sc. Cognition) & Nimrod Berman (M.Sc. CS): Rappez et al. DeepCycle reconstructs a cyclic cell cycle trajectory from unsegmented cell images using convolutional neural networks. Mol Syst Biol (2020). https://www.embopress.org/doi/full/10.15252/msb.20209474
June 22, 2022, Tomer Laor (M.Sc. ISE): Jacques et al. CODEX, a neural network approach to explore signaling dynamics landscapes. Mol Syst Biol (2021). https://www.embopress.org/doi/full/10.15252/msb.202010026
June 22, 2022, Leor Rose & Sarit Hollander (M.Sc. ISE): Rivenson, Liu, Wei et al. PhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learning. Light, Science and Application (2019). https://www.nature.com/articles/s41377-019-0129-y
June 29, 2022, Amit Damri (M.Sc. ISE): Fischer et al. Learning cell communication from spatial graphs of cells. bioRxiv (2021). https://www.biorxiv.org/content/10.1101/2021.07.11.451750v1
June 29, 2022, Omer Reichstein and Yael Hochma (M.Sc. / Ph.D. ISE): Lu et al. Integrating images from multiple microscopy screens reveals diverse patterns of change in the subcellular localization of proteins. eLife (2018). https://elifesciences.org/articles/31872
Video recordings of DSCI 2021 are publicly available here