Author

Jessica L. Mester

ORCID 0000-0001-9374-3185Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 3 Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 5 Research Focus:variant effect prediction· 4 Assay:GWAS summary statistics· 2 Organism:human· 2 Research Focus:variant calling· 2 Assay:whole-exome sequencing· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1

Frequent Co-Authors

Sharon E. PloniD· 4 shared Heidi L. RehmiD· 3 shared Jonathan S. BergiD· 3 shared Steven M. HarrisoniD· 3 shared Tina F. PesaraniD· 3 shared Ahmad N. Abou TayouniD· 2 shared Alicia B. ByrneiD· 2 shared Anne O’Donnell‐LuriaiD· 2 shared

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2020-2025 · peak 2/yr

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10 top collaborators · 45 mutual co-author links

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4 shared papersBioinformatics

Sharon E. PlonORCID

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5 papers

Recent·Most cited

BioinformaticsGenetics in MedicinePeer-reviewedMar 10, 2025

Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria

Timothy R. Bergquist, Sarah L. Stenton, Emily A.W. Nadeau…·Tina F. Pesaran

The paper calibrates three new computational tools for clinical variant classification, finding they provide evidence strength comparable to previously recommended tools.

86 citationstop 1%

GWAS summary statisticsstatistical model

𝕏 PostBluesky

Genetic & Genomic MedicinemedRxivPreprintOct 31, 2024

Loss of DOT1L disrupts neuronal transcription, behavior, and leads to a neurodevelopmental disorder

Marissa J. Maroni, Melissa Barton, Katherine Lynch…·Erica Korb

This study shows that partial loss of DOT1L causes transcriptional, morphological, and behavioral defects in neurons across multiple models.

3 citations

zebrafishmouse

𝕏 PostBluesky

BioinformaticsThe American Journal of Human GeneticsPeer-reviewedNov 21, 2022

Evidence-based calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for clinical use of PP3/BP4 criteria

Vikas Rao Pejaver, Alicia B. Byrne, Bing Feng…·Scott Topper

The paper calibrates computational tools for missense variant pathogenicity classification and provides evidence-based revisions to PP3/BP4 ACMG/AMP criteria.

589 citationstop 1%

GWAS summary statisticsstatistical model

𝕏 PostBluesky

Genetic & Genomic MedicineGenome MedicinePeer-reviewedJan 17, 2022

ClinGen Variant Curation Interface: A Variant Classification Platform for the Application of Evidence Criteria from ACMG/AMP Guidelines

Christine G. Preston, Matt W. Wright, Rao Madhavrao…·Helio A. Costa

The paper introduces the ClinGen Variant Curation Interface, a platform for applying ACMG/AMP guidelines to classify genetic variants, enabling collaboration and standardization in clinical variant interpretation.

81 citationstop 1%

humanwhole-exome sequencing

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Genetic & Genomic MedicineHuman MutationPeer-reviewedDec 10, 2020

Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants

Cristina Fortuño, Kristy Lee, Magali Olivier…·the ClinGen TP53 Variant Curation Expert Panel

The paper specifies TP53-specific ACMG/AMP variant classification guidelines, reducing variants of uncertain significance from 28% to 12%.

170 citationstop 1%

humanwhole-exome sequencing

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