Privacy in Pangenomics
| 392232 | Schönhuth | Winter 2023/2024 | Thu 10-12 in U2-232 (S) |
Papers
| Title | Authors | Year | Journal | |
| A Framework for Adaptive Differential Privacy | Daniel Winograd-Cort et al. | 2017 | Proceedings of the ACM on Programming Languages | |
| Amadeus Beckmann | A Survey on Homomorphic Encryption Schemes: Theory and Implementation | Abbas Acar et al. | 2018 | ACM Computing Surveys |
| Annalena Franz | Blockchain-enabled Federated Learning: A Survey | Cheng Li, Yong Yuan, Fei-Yue Wang | 2021 | IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI) |
| Vignesh Natarajan | Blockchain Meets Federated Learning in Healthcare: A Systematic Review With Challenges and Opportunities | Raushan Myrzashova et al. | 2023 | IEEE INTERNET OF THINGS JOURNAL |
| Mumtaz Hussain | Cloud-based Secure Health Monitoring: Optimizing Fully-Homomorphic Encryption for Streaming Algorithms | Alex Page et al. | 2014 | 2014 IEEE Globecom Workshops (GC Wkshps) |
| Deep Learning with Differential Privacy | Martín Abadi et al | 2016 | Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security | |
| Marvin Mrowka | Flimma: a federated and privacy-aware tool for differential gene expression analysis | Olga Zolotareva et al. | 2021 | Genome Biology |
| Gaussian differential privacy | Jinshuo Dong et al. | 2022 | Journal of the Royal Statistical Society Series B: Statistical Methodology | |
| Khaled Bagh | Mechanisms for Hiding Sensitive Genotypes With Information-Theoretic Privacy | Fangwei Ye et al. | 2022 | IEEE Transactions on Information Theory |
| Mika Sempert | Privacy challenges and research opportunities for genomic data sharing | Luca Bonomi et al. | 2020 | Nature GeNetics |
| Aya Benzine | Functional genomics data: privacy risk assessment and technological mitigation | Gamze Gürsoy et al. | 2022 | Nature Reviews |
| Privacy-preserving genotype imputation in a trusted execution environment | Natnatee Dokmai et al. | 2021 | Cell Systems | |
| Secure human action recognition by encrypted neural network inference | Miran Kim et al. | 2022 | Nature Communications | |
| Johanna Pries | Sequre: a high‑performance framework for secure multiparty computation enables biomedical data sharing | Haris Smajlović et al. | 2023 | Genome Biology |
| Anna-Lena Rinke | Sociotechnical safeguards for genomic data privacy | Zhiyu Wan et al. | 2022 | Nature Reviews |
| Vali Florinel Craciun | Swarm: A federated cloud framework for large-scale variant analysis | Amir Bahmani | 2021 | PLOS Computational Biology |
| Kristin Willms | Swarm Learning for decentralized and confidential clinical machine learning | Stefanie Warnat-Herresthal | 2021 | Nature |
| Nils Witznick | AUTOENCODING VARIATIONAL INFERENCE FOR TOPIC MODELS | Akash Srivastava et al. | 2017 | ICLR |
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Time table lecture
| Date | Topic | |
| 12.10.2023 | Introduction (slides) | Privacy in Healthcare |
| 19.10.2023 | How to present (slides) | Presentations: Guidelines |
| 26.10.2023 | | |
| 02.05.2023 | ||
| 02.11.2023 | ||
| 09.11.2023 | ||
| 16.11.2023 | Deadline paper selection | |
| 23.11.2023 | ||
| 30.11.2023 | ||
| 14.12.2023 | Anna-Lena Rinke | |
| 21.12.2023 | Khaled Bagh, Vignesh Natarajan | |
| 11.01.2024 | Aya Benzine, Annalena Franz, | |
| 18.01.2024 | Marvin Mrowka, Kristin Willms, Nils Witznick | |
| 25.01.2024 | Johanna Pries, Vali Florinel Craciun, Amadeus Beckmann | |
| 01.02.2024 | Mumtaz Hussain |
Presentations each start at 9:30 AM.