Author

Tessel E. Galesloot

Radboud University Medical CenterORCID 0000-0002-2717-3679Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Assay:GWAS summary statistics· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:gene regulatory network inference· 1 Research Focus:GWAS / association mapping· 1 Assay:imaging· 1

Frequent Co-Authors

AH Ghamarian· 1 shared Alejandro Arias VásqueziD· 1 shared Alessandra ChesiiD· 1 shared Alessandro DelitalaiD· 1 shared Alexander DietliD· 1 shared Aliki‐Eleni FarmakiiD· 1 shared Alireza AniiD· 1 shared Amy L MooreiD· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

AH Ghamarian

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3 papers

Recent·Most cited

NeurosciencebioRxivPreprintMar 27, 2024

Sensory processing sensitivity is associated with neural synchrony and functional connectivity during threatening movies

Christienne G. Damatac, Judith Regina Homberg, Tessel E. Galesloot…·Corina U. Greven

This study examines how sensory processing sensitivity relates to neural synchrony and functional connectivity during threatening movie viewing.

1 citation

𝕏 PostBluesky

GeneticsbioRxivPreprintJan 7, 2022

A Saturated Map of Common Genetic Variants Associated with Human Height from 5.4 Million Individuals of Diverse Ancestries

Loïc Yengo, Sailaja Vedantam, Eirini Marouli…·Thomas Folkmann Hansen

This study identifies 12,111 SNPs associated with height from 5.4 million individuals, explaining most common SNP-based heritability and showing ancestry-specific prediction accuracy.

18 citations

humanGWAS summary statistics

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BioinformaticsbioRxivPreprintDec 15, 2020

Quantitative Genetic Scoring, or how to put a number on an arbitrary genetic region

Gido Schoenmacker, Priscilla Vlaming, Jonatan Pallesen…·Alejandro Arias Vásquez

This paper introduces quantitative genetic scoring (QGS) to create quantitative genetic variables from arbitrary regions, showing it can reduce genetic data by >98% while explaining phenotypic variance across different granularities.

1 citation

GWAS summary statisticsstatistical model

𝕏 PostBluesky