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Baiba Vilne

Showing results (1-10 of 37) with videos related to

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Frontiers in Cardiovascular Medicine|August 2, 2018
Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs ApproachBaiba Vilne, Heribert Schunkert
Genes|March 25, 2022
Examining the Association between Mitochondrial Genome Variation and Coronary Artery DiseaseBaiba Vilne, Aniket Sawant, Irina Rudaka
EMBO Molecular Medicine|May 19, 2016
The impact of genome-wide association studies on the pathophysiology and therapy of cardiovascular diseaseThorsten Kessler, Baiba Vilne, Heribert Schunkert
Mitochondrion|July 22, 2025
Comprehensive analysis of the mitochondrial DNA variants using multivariate covariate and multiple-testing models to enhance reliability reveals potential associations with coronary artery disease traits and dietary preferencesAniket Sawant, Irina Griķe, Baiba Vilne
Nucleic Acids Research|November 25, 2010
DIMA 3.0: Domain Interaction MapQibin Luo, Philipp Pagel, Baiba Vilne, et al.
Frontiers in Microbiology|August 27, 2019
Machine Learning Approaches for Epidemiological Investigations of Food-Borne Disease OutbreaksBaiba Vilne, Irēna Meistere, Lelde Grantiņa-Ieviņa, et al.
Cancers|June 10, 2023
Polygenic Risk Score Predicts Modified Risk in Egija Berga-Švītiņa, Jeļena Maksimenko, Edvīns Miklaševičs, et al.
Journal of Cardiovascular Development and Disease|March 28, 2023
Genetic Basis of Early Onset Atrial Fibrillation in Patients without Risk FactorsIrina Rudaka, Baiba Vilne, Jekaterina Isakova, et al.
Frontiers in Microbiology|April 28, 2022
Could Artificial Intelligence/Machine Learning and Inclusion of Diet-Gut Microbiome Interactions Improve Disease Risk Prediction? Case Study: Coronary Artery DiseaseBaiba Vilne, Juris Ķibilds, Inese Siksna, et al.
Clinical Research in Cardiology : Official Journal of the German Cardiac Society|July 20, 2018
Genetics of coronary artery disease in the light of genome-wide association studiesHeribert Schunkert, Moritz von Scheidt, Thorsten Kessler, et al.
Pageof 4

Showing results (1-10 of 37) with videos related to

Sort By:
Pageof 4
Frontiers in Cardiovascular Medicine|August 2, 2018
Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs ApproachBaiba Vilne, Heribert Schunkert
Genes|March 25, 2022
Examining the Association between Mitochondrial Genome Variation and Coronary Artery DiseaseBaiba Vilne, Aniket Sawant, Irina Rudaka
EMBO Molecular Medicine|May 19, 2016
The impact of genome-wide association studies on the pathophysiology and therapy of cardiovascular diseaseThorsten Kessler, Baiba Vilne, Heribert Schunkert
Mitochondrion|July 22, 2025
Comprehensive analysis of the mitochondrial DNA variants using multivariate covariate and multiple-testing models to enhance reliability reveals potential associations with coronary artery disease traits and dietary preferencesAniket Sawant, Irina Griķe, Baiba Vilne
Nucleic Acids Research|November 25, 2010
DIMA 3.0: Domain Interaction MapQibin Luo, Philipp Pagel, Baiba Vilne, et al.
Frontiers in Microbiology|August 27, 2019
Machine Learning Approaches for Epidemiological Investigations of Food-Borne Disease OutbreaksBaiba Vilne, Irēna Meistere, Lelde Grantiņa-Ieviņa, et al.
Cancers|June 10, 2023
Polygenic Risk Score Predicts Modified Risk in Egija Berga-Švītiņa, Jeļena Maksimenko, Edvīns Miklaševičs, et al.
Journal of Cardiovascular Development and Disease|March 28, 2023
Genetic Basis of Early Onset Atrial Fibrillation in Patients without Risk FactorsIrina Rudaka, Baiba Vilne, Jekaterina Isakova, et al.
Frontiers in Microbiology|April 28, 2022
Could Artificial Intelligence/Machine Learning and Inclusion of Diet-Gut Microbiome Interactions Improve Disease Risk Prediction? Case Study: Coronary Artery DiseaseBaiba Vilne, Juris Ķibilds, Inese Siksna, et al.
Clinical Research in Cardiology : Official Journal of the German Cardiac Society|July 20, 2018
Genetics of coronary artery disease in the light of genome-wide association studiesHeribert Schunkert, Moritz von Scheidt, Thorsten Kessler, et al.
Pageof 4