Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Yana Hrytsenko"'
Autor:
Yana Hrytsenko, Benjamin Shea, Michael Elgart, Nuzulul Kurniansyah, Genevieve Lyons, Alanna C. Morrison, April P. Carson, Bernhard Haring, Braxton D. Mitchell, Bruce M. Psaty, Byron C. Jaeger, C. Charles Gu, Charles Kooperberg, Daniel Levy, Donald Lloyd-Jones, Eunhee Choi, Jennifer A. Brody, Jennifer A. Smith, Jerome I. Rotter, Matthew Moll, Myriam Fornage, Noah Simon, Peter Castaldi, Ramon Casanova, Ren-Hua Chung, Robert Kaplan, Ruth J. F. Loos, Sharon L. R. Kardia, Stephen S. Rich, Susan Redline, Tanika Kelly, Timothy O’Connor, Wei Zhao, Wonji Kim, Xiuqing Guo, Yii-Der Ida Chen, The Trans-Omics in Precision Medicine Consortium, Tamar Sofer
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of
Externí odkaz:
https://doaj.org/article/322241f378754ea881e603a18375361b
Autor:
Yi-Ting Tsai, Yana Hrytsenko, Michael Elgart, Usman A. Tahir, Zsu-Zsu Chen, James G. Wilson, Robert E. Gerszten, Tamar Sofer
Publikováno v:
HGG Advances, Vol 5, Iss 3, Pp 100304- (2024)
Summary: Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variab
Externí odkaz:
https://doaj.org/article/7493a82d16f842ec929d7929506e2863
Publikováno v:
Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics.
Background:Determining population structure helps us understand connections among different populations and how they evolve over time. This knowledge is important for studies ranging from evolutionary biology to large-scale variant-trait association
Background: Phylogenies enrich our understanding of how genes, genomes, and species evolve. Traditionally, alignment-based methods are used to construct phylogenies from genetic sequence data; however, this process can be time-consuming when analyzin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90013951cb54b03b292e0580c41d576b
https://doi.org/10.21203/rs.3.rs-1174825/v2
https://doi.org/10.21203/rs.3.rs-1174825/v2
Background: Phylogenies enrich our understanding of how genes, genomes, and species evolve. Traditionally, alignment-based methods are used to construct phylogenies from genetic sequence data; however, this process can be time-consuming when analyzin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f05b46c361dedb296aa78afdbfba2272
https://doi.org/10.21203/rs.3.rs-1174825/v1
https://doi.org/10.21203/rs.3.rs-1174825/v1
The position of some taxa on the Tree of Life remains controversial despite the increase in genomic data used to infer phylogenies. While analyzing large datasets alleviates stochastic errors, it does not prevent systematic errors in inference, cause
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::042f529ae7f8ff50dbe6d661eedf5b50
https://doi.org/10.1101/2021.11.18.469131
https://doi.org/10.1101/2021.11.18.469131
Publikováno v:
BCB
Clustering biological samples allows us to define populations within groups (for example of species or cells), which permits us to answer questions about the processes occuring in those groups. Distance calculations between DNA sequences have been us