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Kerstin Lenhof

Showing results (1-10 of 10) with videos related to

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Briefings in Bioinformatics|May 27, 2024
A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity predictionLea Eckhart, Kerstin Lenhof, Lisa-Marie Rolli, et al.
Briefings in Bioinformatics|August 5, 2024
Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancerKerstin Lenhof, Lea Eckhart, Lisa-Marie Rolli, et al.
Scientific Reports|August 5, 2022
Simultaneous regression and classification for drug sensitivity prediction using an advanced random forest methodKerstin Lenhof, Lea Eckhart, Nico Gerstner, et al.
Scientific Reports|May 29, 2024
Reliable anti-cancer drug sensitivity prediction and prioritizationKerstin Lenhof, Lea Eckhart, Lisa-Marie Rolli, et al.
Iscience|June 12, 2025
How to predict effective drug combinations - moving beyond synergy scoresLea Eckhart, Kerstin Lenhof, Lutz Herrmann, et al.
Bioinformatics (Oxford, England)|August 5, 2021
MERIDA: a novel Boolean logic-based integer linear program for personalized cancer therapyKerstin Lenhof, Nico Gerstner, Tim Kehl, et al.
Frontiers in Molecular Biosciences|October 4, 2021
GeneTrail: A Framework for the Analysis of High-Throughput ProfilesNico Gerstner, Tim Kehl, Kerstin Lenhof, et al.
Nucleic Acids Research|September 29, 2020
Quantitative and time-resolved miRNA pattern of early human T cell activationCaroline Diener, Martin Hart, Tim Kehl, et al.
Nucleic Acids Research|May 8, 2020
GeneTrail 3: advanced high-throughput enrichment analysisNico Gerstner, Tim Kehl, Kerstin Lenhof, et al.
Bioinformatics (Oxford, England)|May 1, 2019
ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratificationLara Schneider, Tim Kehl, Kristina Thedinga, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Briefings in Bioinformatics|May 27, 2024
A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity predictionLea Eckhart, Kerstin Lenhof, Lisa-Marie Rolli, et al.
Briefings in Bioinformatics|August 5, 2024
Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancerKerstin Lenhof, Lea Eckhart, Lisa-Marie Rolli, et al.
Scientific Reports|August 5, 2022
Simultaneous regression and classification for drug sensitivity prediction using an advanced random forest methodKerstin Lenhof, Lea Eckhart, Nico Gerstner, et al.
Scientific Reports|May 29, 2024
Reliable anti-cancer drug sensitivity prediction and prioritizationKerstin Lenhof, Lea Eckhart, Lisa-Marie Rolli, et al.
Iscience|June 12, 2025
How to predict effective drug combinations - moving beyond synergy scoresLea Eckhart, Kerstin Lenhof, Lutz Herrmann, et al.
Bioinformatics (Oxford, England)|August 5, 2021
MERIDA: a novel Boolean logic-based integer linear program for personalized cancer therapyKerstin Lenhof, Nico Gerstner, Tim Kehl, et al.
Frontiers in Molecular Biosciences|October 4, 2021
GeneTrail: A Framework for the Analysis of High-Throughput ProfilesNico Gerstner, Tim Kehl, Kerstin Lenhof, et al.
Nucleic Acids Research|September 29, 2020
Quantitative and time-resolved miRNA pattern of early human T cell activationCaroline Diener, Martin Hart, Tim Kehl, et al.
Nucleic Acids Research|May 8, 2020
GeneTrail 3: advanced high-throughput enrichment analysisNico Gerstner, Tim Kehl, Kerstin Lenhof, et al.
Bioinformatics (Oxford, England)|May 1, 2019
ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratificationLara Schneider, Tim Kehl, Kristina Thedinga, et al.
Pageof 1