Author

MY Pikulina

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1

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Research Focus:benchmarking· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

AH Ghamarian· 1 shared Alejandro Arias VásqueziD· 1 shared Anders Dupont BørglumiD· 1 shared Barbara FrankeiD· 1 shared Ditte DemontisiD· 1 shared Geert PoelmansiD· 1 shared Gido SchoenmackeriD· 1 shared Jan K. BuitelaariD· 1 shared

Activity by Year

2020-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

AH Ghamarian

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1 paper

Recent·Most cited

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

Gido Schoenmacker, Priscilla Vlaming, Jonatan Pallesen, MY Pikulina, AH Ghamarian, Ditte Demontis, Anders Dupont Børglum, Tessel E. Galesloot, Geert Poelmans, Barbara Franke, Tom Claassen, Tom Heskes, Jan K. Buitelaar, 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.

bioRxiv · Dec 15, 2020 · PreprintBioinformatics