Machine learning can distinguish orphans that have resulted from sequence divergence beyond recognition

Authors

Anne Kupczok (ORCID: https://orcid.org/0000-0001-5237-1899)
Nikolaos Vakirlis (ORCID: https://orcid.org/0000-0001-7606-6987)
Christoforos Nikolaou
Emilios Tassios (ORCID: https://orcid.org/0000-0003-1360-9619)
Jori de Leuw

Institutions

University of Ioannina (GR)
Pasteur Hellenic Institute (GR)
Alexander Fleming Biomedical Sciences Research Center (GR)
Wageningen University & Research (NL)

Publication Details

Journal: Bioinformatics Advances
Published: 2025-12-25
DOI: https://doi.org/10.1093/bioadv/vbaf324
Primary Topic: Genomics and Rare Diseases
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Hellenic Foundation for Research and Innovation

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article

Machine learning can distinguish orphans that have resulted from sequence divergence beyond recognition

Anne Kupczok, Nikolaos Vakirlis, Christoforos Nikolaou, Emilios Tassios et al.

Dec 25, 2025

Bioinformatics Advances

Genomics and Rare Diseases

article

Machine learning can distinguish orphans that have resulted from sequence divergence beyond recognition

Anne Kupczok, Nikolaos Vakirlis, Christoforos Nikolaou, Emilios Tassios, Jori de Leuw

December 25, 2025article en

Abstract

No abstract available for this paper.

Bioinformatics AdvancesVol. 6(1)

University of Ioannina (GR), Pasteur Hellenic Institute (GR), Alexander Fleming Biomedical Sciences Research Center (GR), Wageningen University & Research (NL)

Hellenic Foundation for Research and Innovation

Openalex Percentile: Top 24%

Genomics and Rare Diseases

DOI Open Access PDF OpenAlex

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