Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Eszter Lakatos

Showing results (1-10 of 25) with videos related to

Pageof 3
Sort By:
Briefings in Bioinformatics|March 16, 2026
Sensitive detection of copy number alterations in low-pass liquid biopsy sequencing dataLotta Eriksson, Eszter Lakatos
Royal Society Open Science|September 8, 2017
Control mechanisms for stochastic biochemical systems via computation of reachable setsEszter Lakatos, Michael P H Stumpf
Plos Computational Biology|September 21, 2018
Transition state characteristics during cell differentiationRowan D Brackston, Eszter Lakatos, Michael P H Stumpf
The Journal of Chemical Physics|September 7, 2015
Multivariate moment closure techniques for stochastic kinetic modelsEszter Lakatos, Angelique Ale, Paul D W Kirk, et al.
Journal of Structural Biology|May 9, 2018
Topology of interaction between titin and myosin thick filamentsMiklós Kellermayer, Dominik Sziklai, Zsombor Papp, et al.
Iscience|August 17, 2021
LiquidCNA: Tracking subclonal evolution from longitudinal liquid biopsies using somatic copy number alterationsEszter Lakatos, Helen Hockings, Maximilian Mossner, et al.
BMC Bioinformatics|May 24, 2019
NeoPredPipe: high-throughput neoantigen prediction and recognition potential pipelineRyan O Schenck, Eszter Lakatos, Chandler Gatenbee, et al.
Plos One|May 11, 2017
Protein degradation rate is the dominant mechanism accounting for the differences in protein abundance of basal p53 in a human breast and colorectal cancer cell lineEszter Lakatos, Ali Salehi-Reyhani, Michael Barclay, et al.
Nature Communications|September 6, 2022
The mutational signatures of formalin fixation on the human genomeQingli Guo, Eszter Lakatos, Ibrahim Al Bakir, et al.
Bioinformatics (Oxford, England)|May 7, 2016
MEANS: python package for Moment Expansion Approximation, iNference and SimulationSisi Fan, Quentin Geissmann, Eszter Lakatos, et al.
Pageof 3

Showing results (1-10 of 25) with videos related to

Sort By:
Pageof 3
Briefings in Bioinformatics|March 16, 2026
Sensitive detection of copy number alterations in low-pass liquid biopsy sequencing dataLotta Eriksson, Eszter Lakatos
Royal Society Open Science|September 8, 2017
Control mechanisms for stochastic biochemical systems via computation of reachable setsEszter Lakatos, Michael P H Stumpf
Plos Computational Biology|September 21, 2018
Transition state characteristics during cell differentiationRowan D Brackston, Eszter Lakatos, Michael P H Stumpf
The Journal of Chemical Physics|September 7, 2015
Multivariate moment closure techniques for stochastic kinetic modelsEszter Lakatos, Angelique Ale, Paul D W Kirk, et al.
Journal of Structural Biology|May 9, 2018
Topology of interaction between titin and myosin thick filamentsMiklós Kellermayer, Dominik Sziklai, Zsombor Papp, et al.
Iscience|August 17, 2021
LiquidCNA: Tracking subclonal evolution from longitudinal liquid biopsies using somatic copy number alterationsEszter Lakatos, Helen Hockings, Maximilian Mossner, et al.
BMC Bioinformatics|May 24, 2019
NeoPredPipe: high-throughput neoantigen prediction and recognition potential pipelineRyan O Schenck, Eszter Lakatos, Chandler Gatenbee, et al.
Plos One|May 11, 2017
Protein degradation rate is the dominant mechanism accounting for the differences in protein abundance of basal p53 in a human breast and colorectal cancer cell lineEszter Lakatos, Ali Salehi-Reyhani, Michael Barclay, et al.
Nature Communications|September 6, 2022
The mutational signatures of formalin fixation on the human genomeQingli Guo, Eszter Lakatos, Ibrahim Al Bakir, et al.
Bioinformatics (Oxford, England)|May 7, 2016
MEANS: python package for Moment Expansion Approximation, iNference and SimulationSisi Fan, Quentin Geissmann, Eszter Lakatos, et al.
Pageof 3