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David B Blumenthal

Showing results (1-10 of 41) with videos related to

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Briefings in Bioinformatics|November 20, 2023
Demographic confounders distort inference of gene regulatory and gene co-expression networks in cancerAnna Ketteler, David B Blumenthal
Briefings in Bioinformatics|March 6, 2024
Cracking the black box of deep sequence-based protein-protein interaction predictionJudith Bernett, David B Blumenthal, Markus List
Nature Communications|February 13, 2026
Addendum: Data splitting against information leakage with DataSAILRoman Joeres, David B Blumenthal, Olga V Kalinina
Nature Communications|April 8, 2025
Data splitting to avoid information leakage with DataSAILRoman Joeres, David B Blumenthal, Olga V Kalinina
Briefings in Bioinformatics|June 26, 2022
Online in silico validation of disease and gene sets, clusterings or subnetworks with DIGESTKlaudia Adamowicz, Andreas Maier, Jan Baumbach, et al.
Briefings in Bioinformatics|March 30, 2021
On the limits of active module identificationOlga Lazareva, Jan Baumbach, Markus List, et al.
Bioinformatics (Oxford, England)|November 30, 2020
A framework for modeling epistatic interactionDavid B Blumenthal, Jan Baumbach, Markus Hoffmann, et al.
Bioinformatics (Oxford, England)|June 27, 2025
Inference of differential kinase interaction networks with KINferenceNicolai Meyerhöfer, Nevan J Krogan, Benjamin J Polacco, et al.
Gigascience|November 9, 2025
NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing dataFabian Woller, Lis Arend, Christian Fuchsberger, et al.
Bioinformatics (Oxford, England)|July 15, 2025
Deep learning models for unbiased sequence-based PPI prediction plateau at an accuracy of 0.65Timo Reim, Anne Hartebrodt, David B Blumenthal, et al.
Pageof 5

Showing results (1-10 of 41) with videos related to

Sort By:
Pageof 5
Briefings in Bioinformatics|November 20, 2023
Demographic confounders distort inference of gene regulatory and gene co-expression networks in cancerAnna Ketteler, David B Blumenthal
Briefings in Bioinformatics|March 6, 2024
Cracking the black box of deep sequence-based protein-protein interaction predictionJudith Bernett, David B Blumenthal, Markus List
Nature Communications|February 13, 2026
Addendum: Data splitting against information leakage with DataSAILRoman Joeres, David B Blumenthal, Olga V Kalinina
Nature Communications|April 8, 2025
Data splitting to avoid information leakage with DataSAILRoman Joeres, David B Blumenthal, Olga V Kalinina
Briefings in Bioinformatics|June 26, 2022
Online in silico validation of disease and gene sets, clusterings or subnetworks with DIGESTKlaudia Adamowicz, Andreas Maier, Jan Baumbach, et al.
Briefings in Bioinformatics|March 30, 2021
On the limits of active module identificationOlga Lazareva, Jan Baumbach, Markus List, et al.
Bioinformatics (Oxford, England)|November 30, 2020
A framework for modeling epistatic interactionDavid B Blumenthal, Jan Baumbach, Markus Hoffmann, et al.
Bioinformatics (Oxford, England)|June 27, 2025
Inference of differential kinase interaction networks with KINferenceNicolai Meyerhöfer, Nevan J Krogan, Benjamin J Polacco, et al.
Gigascience|November 9, 2025
NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing dataFabian Woller, Lis Arend, Christian Fuchsberger, et al.
Bioinformatics (Oxford, England)|July 15, 2025
Deep learning models for unbiased sequence-based PPI prediction plateau at an accuracy of 0.65Timo Reim, Anne Hartebrodt, David B Blumenthal, et al.
Pageof 5