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Thomas Sakoparnig

Showing results (1-10 of 11) with videos related to

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Bioinformatics (Oxford, England)|July 12, 2012
Efficient sampling for Bayesian inference of conjunctive Bayesian networksThomas Sakoparnig, Niko Beerenwinkel
Plos Computational Biology|January 9, 2015
Identification of constrained cancer driver genes based on mutation timingThomas Sakoparnig, Patrick Fried, Niko Beerenwinkel
Plos Computational Biology|July 12, 2024
Identifying cell states in single-cell RNA-seq data at statistically maximal resolutionPascal Grobecker, Thomas Sakoparnig, Erik van Nimwegen
Elife|January 8, 2021
Whole genome phylogenies reflect the distributions of recombination rates for many bacterial speciesThomas Sakoparnig, Chris Field, Erik van Nimwegen
Genome Biology|March 19, 2015
BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogeniesKe Yuan, Thomas Sakoparnig, Florian Markowetz, et al.
Genome Medicine|November 30, 2017
Predicting cancer type from tumour DNA signaturesKee Pang Soh, Ewa Szczurek, Thomas Sakoparnig, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 4, 2012
Binding profiles of chromatin-modifying proteins are predictive for transcriptional activity and promoter-proximal pausingThomas Sakoparnig, Tobias Kockmann, Renato Paro, et al.
Swiss Medical Weekly|September 13, 2020
Bayesian networks to identify potential high-risk multimorbidity and intervention clusters in inpatients: an explorative data mining studyJan A Roth, Thomas Sakoparnig, Martin Gerber, et al.
Journal of Clinical Epidemiology|January 15, 2019
Medical diagnoses showed low relatedness in an explorative mutual information analysis of 190,837 inpatient casesJan A Roth, Thomas Sakoparnig, Simon Neubauer, et al.
JAMIA Open|January 28, 2020
Secondary use of routine data in hospitals: description of a scalable analytical platform based on a business intelligence systemJan A Roth, Nicole Goebel, Thomas Sakoparnig, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|July 12, 2012
Efficient sampling for Bayesian inference of conjunctive Bayesian networksThomas Sakoparnig, Niko Beerenwinkel
Plos Computational Biology|January 9, 2015
Identification of constrained cancer driver genes based on mutation timingThomas Sakoparnig, Patrick Fried, Niko Beerenwinkel
Plos Computational Biology|July 12, 2024
Identifying cell states in single-cell RNA-seq data at statistically maximal resolutionPascal Grobecker, Thomas Sakoparnig, Erik van Nimwegen
Elife|January 8, 2021
Whole genome phylogenies reflect the distributions of recombination rates for many bacterial speciesThomas Sakoparnig, Chris Field, Erik van Nimwegen
Genome Biology|March 19, 2015
BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogeniesKe Yuan, Thomas Sakoparnig, Florian Markowetz, et al.
Genome Medicine|November 30, 2017
Predicting cancer type from tumour DNA signaturesKee Pang Soh, Ewa Szczurek, Thomas Sakoparnig, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|February 4, 2012
Binding profiles of chromatin-modifying proteins are predictive for transcriptional activity and promoter-proximal pausingThomas Sakoparnig, Tobias Kockmann, Renato Paro, et al.
Swiss Medical Weekly|September 13, 2020
Bayesian networks to identify potential high-risk multimorbidity and intervention clusters in inpatients: an explorative data mining studyJan A Roth, Thomas Sakoparnig, Martin Gerber, et al.
Journal of Clinical Epidemiology|January 15, 2019
Medical diagnoses showed low relatedness in an explorative mutual information analysis of 190,837 inpatient casesJan A Roth, Thomas Sakoparnig, Simon Neubauer, et al.
JAMIA Open|January 28, 2020
Secondary use of routine data in hospitals: description of a scalable analytical platform based on a business intelligence systemJan A Roth, Nicole Goebel, Thomas Sakoparnig, et al.
Pageof 2