Author

G. Castellani

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Biophysics· 2 Bioengineering· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Research Focus:clustering· 2 Approach:deep learning· 2 Assay:DNA methylation· 2 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:biophysical modeling· 1

Frequent Co-Authors

C. Sala· 2 shared E. Giampieri· 2 shared A. Beleon· 1 shared A. Carbonaro· 1 shared A. Merlotti· 1 shared A. T. Turki· 1 shared A. Tesei· 1 shared C. Arienti· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersCancer Biology

C. Sala

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Covering Hierarchical Dirichlet Mixture Models on binary data to enhance genomic stratifications in Onco-Hematology

D. Dall'Olio, E. Sträng, A. T. Turki, J. M. Tettero, M. Barbus, R. Schulze-Rath, J. M. Elicegui, T. Matteuzzi, A. Merlotti, L. Carota, C. Sala, M. G. Della Porta, E. Giampieri, J. M. Hernandez-Rivas, L. Bullinger, G. Castellani

This paper applies Hierarchical Dirichlet Mixture Models to binary genomic data in AML to improve patient stratification and clustering through statistical refinements.

bioRxiv · Jun 26, 2023Cancer Biology

CometAnalyser: a user-friendly, open-source deep-learning microscopy tool for quantitative comet assay analysis.

A. Beleon, S. Pignatta, C. Arienti, A. Carbonaro, P. Horvath, G. Martinelli, G. Castellani, A. Tesei, F. Piccinini

CometAnalyser is an open-source deep-learning tool for automated comet assay analysis of fluorescent and silver-stained microscopy images, extracting quantitative features for DNA damage assessment.

bioRxiv · Jul 4, 2022Bioengineering

Discovering footprints of evolutionary chromatin response to transposons activity: merging biophysics with bioinformatics

S. Vitali, E. Giampieri, C. Sala, I. Do Valle, S. Criscione, N. Neretti, G. Castellani

The paper models LINEs activity as an ecosystem to infer evolutionary chromatin responses in mammals and primates, finding contrasting patterns in murine and primate lineages.

bioRxiv · Feb 22, 2021 · PreprintBiophysics

Prediction of vascular ageing based on smartphone acquired PPG signals

L. Dall'Olio, N. Curti, D. Remondini, Y. S. Harb, F. W. Asselbergs, G. Castellani, H.-W. Uh

This study uses machine learning and deep learning to predict vascular aging from smartphone-acquired PPG signals, achieving high accuracy with both approaches.

bioRxiv · May 26, 2020Biophysics