Publication detail

Unlocking Genetic Prognostication: Cage App – Computer-Aided Approach for Genomics Prediction

SCHWARZEROVÁ, J. NOHEL, M. SITKOVA, R. SKARDA, J. CHMELÍK, J. PROVAZNÍK, V. WECKWERTH, W.

Original Title

Unlocking Genetic Prognostication: Cage App – Computer-Aided Approach for Genomics Prediction

Type

abstract

Language

English

Original Abstract

Advanced sequencing techniques have propelled molecular biology research into what is often termed the post-genomic era. Consequently, there's a heightened focus on unraveling the functional connections between individual genes and their ultimate phenotypic expression. This newly developed app, designed within Matlab2023b App Designer, holds signicant promise for opening new and optimal pathways in predictive genomics. We developed user-friendly app for uploading genomics (in form single nucleotide polymorphisms (SNPs)), metabolomics and phenotype data, their visualization and subsequently prediction analysis using different methods such as linear, non-linear and also deep learning for genomic prediction and calculated polygenic risk score and GWAS with visualization which is implemented in Matlab2022b.

Keywords

Post-Genomic Era, Genomic Prediction, Metabolomics, Matlab App Designer

Authors

SCHWARZEROVÁ, J.; NOHEL, M.; SITKOVA, R.; SKARDA, J.; CHMELÍK, J.; PROVAZNÍK, V.; WECKWERTH, W.

Released

5. 6. 2024

Location

Kladno, Czech Republik

Pages count

1

URL

https://ventilation.fbmi.cvut.cz/wp-content/uploads/2024/07/YBERC_2024_Book_of_abstracts.pdf

BibTex

@misc{BUT193462,
  author="Jana {Schwarzerová} and Michal {Nohel} and Radka {Sitkova} and Jozef {Skarda} and Jiří {Chmelík} and Valentine {Provazník} and Wolfram {Weckwerth}",
  title="Unlocking Genetic Prognostication: Cage App – Computer-Aided Approach for Genomics Prediction",
  year="2024",
  pages="1",
  address="Kladno, Czech Republik",
  url="https://ventilation.fbmi.cvut.cz/wp-content/uploads/2024/07/YBERC_2024_Book_of_abstracts.pdf",
  note="abstract"
}