Author

Jessica Chedid

The University of SydneyORCID 0000-0001-7985-5148Unclaimed 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:cell type annotation· 2 Organism:human· 2 Approach:experimental assay· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Adahir Labrador‐GarridoiD· 2 shared Carolyn M. SueiD· 2 shared Chiara PavaniD· 2 shared Clare L. ParishiD· 2 shared Dario StrbenaciD· 2 shared Deniz KirikiD· 2 shared Dmitry A. OvchinnikoviD· 2 shared Gautam WaliiD· 2 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersNeuroscience

Adahir Labrador‐GarridoORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintJan 29, 2026

Machine learning-based image analysis of Parkinson's disease iPS-derived neurons predicts genotype and reveals mitochondria-lysosome abnormalities

Yan Li, Maximilian Powell, Jessica Chedid…·Gautam Wali

The paper uses machine learning to analyze neuronal morphology in Parkinson's disease iPSC-derived neurons, identifying genotype-specific mitochondrial and lysosomal abnormalities.

DOI 10.64898/2026.01.28.702423

humanimaging

𝕏 PostBluesky

Neurosciencenpj Parkinson s DiseasePeer-reviewedJun 20, 2025

Dopamine and cortical iPSC-derived neurons with different Parkinsonian mutations show variation in lysosomal and mitochondrial dysfunction: implications for protein deposition versus selective cell loss

Jessica Chedid, Yan Li, Adahir Labrador‐Garrido…·Nicolas L. Dzamko

This study compares dopamine and cortical neurons with PD mutations to identify cellular dysfunctions linked to different pathological phenotypes.

8 citationstop 4%

humanexperimental assay

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