Author

Petya Kindalova

University of OxfordORCID 0000-0002-5202-1335Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Assay:imaging· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:CRISPR screen· 1

Frequent Co-Authors

Thomas E. NicholsiD· 4 shared Ioannis KosmidisiD· 3 shared Michele VeldsmaniD· 2 shared Alastair D. ReithiD· 1 shared Alice RockliffeiD· 1 shared Benedetta Carbone· 1 shared Cuong Nguyen· 1 shared Fernanda Martins Lopes· 1 shared

Activity by Year

2018-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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4 shared papersNeuroscience

Thomas E. NicholsORCID

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Author profile →

5 papers

Recent·Most cited

A CRISPR-CAS9 high throughput machine-learning platform for modulation of genes involved in Parkinson's disease-associated PINK1-mitophagy in iPSC-derived dopaminergic neurons

Marc P. M. Soutar, Benedetta Carbone, Petya Kindalova, Rahil Mehrizi, Fernanda Martins Lopes, Nathaniel Lam, Alice Rockliffe, Toni Braybrook, Matthew D. Taylor, Cuong Nguyen, Fiona Ducotterd, Alastair D. Reith, Lisa Mohamet, Hélène Plun‐Favreau

The paper develops a CRISPR-CAS9 platform with machine learning to study PINK1-mitophagy in Parkinson's disease using iPSC-derived neurons, identifying key genes and validating their roles.

bioRxiv · Jun 10, 2025 · PreprintNeuroscience

Penalized generalized estimating equations for relative risk regression with applications to brain lesion data

Petya Kindalova, Michele Veldsman, Thomas E. Nichols, Ioannis Kosmidis

The paper introduces penalized generalized estimating equations for relative risk regression to address instability in modeling brain lesion data, showing improved convergence and interpretation.

bioRxiv · Nov 1, 2021 · PreprintNeuroscience

Voxel-wise and spatial modelling of binary lesion masks: Comparison of methods with a realistic simulation framework

Petya Kindalova, Ioannis Kosmidis, Thomas E. Nichols

The paper compares voxel-wise and spatial modelling approaches for binary lesion masks using a simulation framework and finds bias-reduced voxel-wise GLMs are accurate and efficient.

NeuroImage · Apr 22, 2021Peer-reviewedNeuroscience

Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities

Michele Veldsman, Petya Kindalova, Masud Husain B, Ioannis Kosmidis, Thomas E. Nichols

This study investigates the spatial distribution of white matter hyperintensities (WMHs) related to cerebrovascular risk factors and their impact on cognitive function in a large cohort.

NeuroImage Clinical · Jan 1, 2020Peer-reviewedNeuroscience

Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference

Vaanathi Sundaresan, Ludovica Griffanti, Petya Kindalova, Fidel Alfaro‐Almagro, Giovanna Zamboni, Peter Malcolm Rothwell, Thomas E. Nichols, Mark Jenkinson

This paper develops a Bayesian spline method to model the spatio-temporal distribution of white matter hyperintensities with respect to age and validates it on simulated and real datasets.

NeuroImage · Oct 22, 2018Peer-reviewedNeuroscience