Author

Chiara Magliaro

University of PisaORCID 0000-0003-2520-4643Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Chiara Magliaro1 paper

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Assay:electronic health records· 1 Approach:genetic perturbation / CRISPR· 1

Frequent Co-Authors

Arti Devi AhluwaliaiD· 3 shared Alejandro Luis CallaraiD· 1 shared Ermes BotteiD· 1 shared Flavio Fontana· 1 shared Francesco PampaloniiD· 1 shared Nicola VanelloiD· 1 shared Piera ManciniiD· 1 shared Rachele FabbriiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 14 mutual co-author links

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3 shared papersBioengineering

Arti Devi AhluwaliaORCID

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3 papers

Recent·Most cited

BioengineeringJournal of Biological EngineeringPeer-reviewedFeb 27, 2026

Evolvoid: A genetic algorithm for shaping optimal cellular constructs

Piera Mancini, Flavio Fontana, Ermes Botte…·Arti Devi Ahluwalia

Evolvoid uses genetic algorithms to optimize cellular construct morphology by balancing cell viability and surface energy through a fitness function based on biophysical laws.

1 citation

deep learninggenetic perturbation / CRISPR

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NeurosciencebioRxivPreprintOct 30, 2023

Digitoids: a novel computational platform for mimicking oxygen-dependent firing dynamics in in vitro neuronal networks

Rachele Fabbri, Arti Devi Ahluwalia, Chiara Magliaro

The paper introduces a computational platform called Digitoids that mimics oxygen-dependent firing dynamics in in vitro neuronal networks and shows its output matches experimental data.

DOI 10.1101/2023.10.30.564673

electronic health recordsexperimental assay

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BioinformaticsFrontiers in NeuroinformaticsPeer-reviewedMar 17, 2020

A Smart Region-Growing algorithm for single-neuron segmentation from confocal and 2-photon datasets

Alejandro Luis Callara, Chiara Magliaro, Arti Devi Ahluwalia, Nicola Vanello

The paper introduces a Smart Region-Growing algorithm for single-neuron segmentation from 3D confocal datasets and validates it against manual segmentation by experts.

21 citations

imagingexperimental assay

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