Author

Dietmar Fernández‐Orth

Barcelona Institute of Science and TechnologyORCID 0000-0002-1237-3192Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Claudia GiambartolomeiiD· 1 shared Eleftherios G. Samaras· 1 shared Fotis AisoposiD· 1 shared George PaliourasiD· 1 shared Gian Gaetano TartagliaiD· 1 shared Giorgio Bini· 1 shared Ivo Glynne GutiD· 1 shared Jordi RamblaiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Claudia GiambartolomeiORCID

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2 papers

Recent·Most cited

BioinformaticsBioinformatics AdvancesPeer-reviewedJan 1, 2026

CBIcall: a configuration-driven framework for variant calling in large sequencing cohorts

Manuel Rueda, Dietmar Fernández‐Orth, Ivo Glynne Gut

CBIcall provides a configuration-driven framework for standardized variant calling across large sequencing cohorts, ensuring reproducibility and consistency in pipeline execution.

DOI 10.1093/bioadv/vbag232

whole-exome sequencingwhole-genome sequencing

Genetic & Genomic MedicineAlzheimer s & Dementia Diagnosis Assessment & Disease MonitoringPeer-reviewedJan 1, 2022

Machine learning methods applied to genotyping data capture interactions between single nucleotide variants in late onset Alzheimer's disease

Magdalena Arnal, Giorgio Bini, Dietmar Fernández‐Orth…·Gian Gaetano Tartaglia

The paper uses machine learning to analyze genotyping data and identifies interactions between SNVs in late onset Alzheimer's disease, highlighting specific genomic profiles and interactions involving APOE and other genes.

9 citations

humanGWAS summary statistics