Author

Alkistis Skalkidou

Uppsala UniversityORCID 0000-0002-4935-7532Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:differential expression· 3 Organism:human· 3 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Birgit DerntliD· 2 shared Tobias KaufmanniD· 2 shared Andrey ShternshisiD· 1 shared Bangzhuo TongiD· 1 shared Carolina WählbyiD· 1 shared Dave ZachariahiD· 1 shared Gloria Matte BoniD· 1 shared Jonas L. FischeriD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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2 shared papersNeuroscience

Birgit DerntlORCID

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3 papers

Recent·Most cited

Brain anatomy in major hormonal transition phases: Longitudinal and cross-sectional volume associations with menarche and menopause

Melanie Freund, Gloria Matte Bon, Alkistis Skalkidou, Birgit Derntl, Tobias Kaufmann

The paper examines brain volume changes associated with menarche and menopause using MRI data, finding overlapping but opposing effects in specific brain regions across both phases.

bioRxiv · Apr 2, 2026 · PreprintNeuroscience

Traces of parenthood but not pregnancy loss in UK Biobank structural brain MRI data

Jonas L. Fischer, Alkistis Skalkidou, Birgit Derntl, Tobias Kaufmann

The paper examines structural brain MRI data from UK Biobank to determine if neuroanatomical changes reflect parenthood or pregnancy loss, finding that parenthood, not pregnancy loss, is associated with volumetric differences.

Human Brain Mapping · Apr 1, 2026Peer-reviewedNeuroscience

Predicting allergy and postpartum depression from incomplete compositional microbiome

Andrey Shternshis, Bangzhuo Tong, Alkistis Skalkidou, Carolina Wählby, Dave Zachariah, Luisa Warchavchik Hugerth, Prashant Singh

The paper predicts food allergies and postpartum depression using microbiome time series data with imputation and logarithmic transformation, achieving balanced accuracies of 0.72 and 0.62 respectively.

BMC Genomics · Dec 6, 2025Peer-reviewedBioinformatics