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SLAS Technology|January 21, 2022
Benchmarking feature selection methods for compressing image information in high-content screeningDaniel Siegismund, Matthias Fassler, Stephan Heyse, et al.
SLAS Discovery : Advancing Life Sciences R & D|November 22, 2025
PCIM: Learning pixel attributions via pixel-wise channel isolation mixing in high content imagingDaniel Siegismund, Mario Wieser, Stephan Heyse, et al.
SLAS Discovery : Advancing Life Sciences R & D|May 21, 2020
Deep Learning-Based HCS Image Analysis for the EnterpriseStephan Steigele, Daniel Siegismund, Matthias Fassler, et al.
Drug Research|January 18, 2018
Developing Deep Learning Applications for Life Science and Pharma IndustryDaniel Siegismund, Vasily Tolkachev, Stephan Heyse, et al.
SLAS Discovery : Advancing Life Sciences R & D|February 5, 2026
AI-Based Analysis of Label-Free Live Cell Imaging of T-Cell Mediated Tumor Killing Assay Enables Competitive and Robust Hit CallingJosefa Chuh, Daniel Siegismund, John Moffat, et al.
Assay and Drug Development Technologies|August 28, 2018
Know When You Don't Know: A Robust Deep Learning Approach in the Presence of Unknown PhenotypesOliver Dürr, Elvis Murina, Daniel Siegismund, et al.
SLAS Discovery : Advancing Life Sciences R & D|January 21, 2022
An efficient and scalable data analysis solution for automated electrophysiology platformsTianbo Li, Martin Ginkel, Ada X Yee, et al.
SLAS Discovery : Advancing Life Sciences R & D|July 5, 2024
A robust CETSA data analysis automation workflow for routine screeningJuan Daniel Florez Weidinger, Moritz Pfreundschuh, Diana Zörb, et al.
SLAS Discovery : Advancing Life Sciences R & D|September 26, 2022
High-throughput mechanistic screening of non-equilibrium inhibitors by a fully automated data analysis pipeline in early drug-discoveryBharath Srinivasan, Juan Daniel Flórez Weidinger, Xiang Zhai, et al.
Nucleic Acids Research|September 9, 2005
Open reading frames provide a rich pool of potential natural antisense transcripts in fungal genomesStephan Steigele, Kay Nieselt
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