scE(match): Privacy-Preserving Cluster Matching of Single-Cell Data

This file was created by the TYPO3 extension bib --- Timezone: UTC Creation date: 2024-12-03 Creation time: 18-34-20 --- Number of references 6 inproceedings 2024_lohmoeller_scematch scE(match): Privacy-Preserving Cluster Matching of Single-Cell Data 2024 12 16 Advances in single-cell RNA sequencing (scRNA-seq) have dramatically enhanced our understanding of cellular functions and disease mechanisms. Despite its potential, scRNA-seq faces significant challenges related to data privacy, cost, and Intellectual Property (IP) protection, which hinder the sharing and collaborative use of these sensitive datasets. In this paper, we introduce a novel method, scE(match), a privacy-preserving tool that facilitates the matching of single-cell clusters between different datasets by relying on scmap as an established projection tool, but without compromising data privacy or IP. scE(match) utilizes homomorphic encryption to ensure that data and unique cell clusters remain confidential while enabling the identification of overlapping cell types for further collaboration and downstream analysis. Our evaluation shows that scE(match) performantly matches cell types across datasets with high precision, addressing both practical and ethical concerns in sharing scRNA-seq data. This approach not only supports secure data collaboration but also fosters advances in biomedical research by reliably protecting sensitive information and IP rights. confidentiality; scmap; privacy-preserving computations; offloading; healthcare rfc;health https://www.comsys.rwth-aachen.de/fileadmin/papers/2024/2024-lohmoeller-scEmatch.pdf IEEE Proceedings of the International Workshop on AI-Driven Trust, Security and Privacy in Computer Networks (AI-Driven TSP '24), co-located with the 23rd IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom '24), December 17-21, 2024, Sanya, China Sanya, China TrustCom 2024 December 17-21, 2024 accepted en 1 JohannesLohmöller JannisScheiber RafaelKramann KlausWehrle SikanderHayat JanPennekamp article 2024_querfurth_mcbert mcBERT: Patient-Level Single-cell Transcriptomics Data Representation bioRxiv 2024 11 7 health 10.1101/2024.11.04.621897 Benediktvon Querfurth JohannesLohmöller JanPennekamp ToreBleckwehl RafaelKramann KlausWehrle SikanderHayat inproceedings 2024-wagner-madtls Madtls: Fine-grained Middlebox-aware End-to-end Security for Industrial Communication 2024 7 1 https://www.comsys.rwth-aachen.de/fileadmin/papers/2024/2024-wagner-madtls.pdf ACM 19th ACM ASIA Conference on Computer and Communications Security (ACM AsiaCCS '24), Singapur Singapur ACM ASIA Conference on Computer and Communications Security (AsiaCCS) July 1-5, 2024 10.1145/3634737.3637640 1 EricWagner DavidHeye MartinSerror IkeKunze KlausWehrle MartinHenze inproceedings 2024-kunze-spintrap SpinTrap: Catching Speeding QUIC Flows 2024 5 7 legato https://www.comsys.rwth-aachen.de/fileadmin/papers/2024/2024-kunze-spintrap.pdf IEEE/IFIP Proceedings of the 2024 IEEE/IFIP Network Operations and Management Symposium (NOMS '24) 2024 IEEE/IFIP Network Operations and Management Symposium 10.1109/NOMS59830.2024.10575719 1 IkeKunze ConstantinSander LarsTissen BenediktBode KlausWehrle inproceedings 2024-kunze-civic In-Situ Model Validation for Continuous Processes Using In-Network Computing 2024 5 internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2024/2024-kunze-civic.pdf IEEE Proceedings of the 7th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS '24) 10.1109/ICPS59941.2024.10639999 1 IkeKunze DominikScheurenberg LiamTirpitz SandraGeisler KlausWehrle article 2024_pennekamp_supply-chain-survey An Interdisciplinary Survey on Information Flows in Supply Chains ACM Computing Surveys 2024 2 1 56 2 Supply chains form the backbone of modern economies and therefore require reliable information flows. In practice, however, supply chains face severe technical challenges, especially regarding security and privacy. In this work, we consolidate studies from supply chain management, information systems, and computer science from 2010--2021 in an interdisciplinary meta-survey to make this topic holistically accessible to interdisciplinary research. In particular, we identify a significant potential for computer scientists to remedy technical challenges and improve the robustness of information flows. We subsequently present a concise information flow-focused taxonomy for supply chains before discussing future research directions to provide possible entry points. information flows; data communication; supply chain management; data security; data sharing; systematic literature review internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2024/2024-pennekamp-supply-chain-survey.pdf ACM 0360-0300 10.1145/3606693 1 JanPennekamp RomanMatzutt ChristopherKlinkmüller LennartBader MartinSerror EricWagner SidraMalik MariaSpiß JessicaRahn TanGürpinar EduardVlad Sander J. J.Leemans Salil S.Kanhere VolkerStich KlausWehrle