Author

Avelino Javer

Primary ORCID profile (0000-0003-4100-6807 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Avelino JaveriD1 paper · MRC London Institute of Medical Sciences

Biology Disciplines

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Animal Behavior & Cognition· 3 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:C. elegans· 3 Research Focus:cell type annotation· 3 Approach:deep learning· 3 Assay:imaging· 3 Research Focus:clustering· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Research Focus:cell-cell communication· 1

Frequent Co-Authors

André E.X. Brown· 2 shared Agnieszka Dobrowolska· 1 shared Alice Del Vecchio· 1 shared Andre E.X. BrowniD· 1 shared Andrew AnighoroiD· 1 shared Cameron Field· 1 shared Chantriolnt-Andreas KapouraniiD· 1 shared Cristian RegepiD· 1 shared

Activity by Year

2017-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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2 shared papersAnimal Behavior & Cognition

André E.X. Brown

Author profile →

4 papers

Recent·Most cited

A DNA foundation model predicts osteoporosis risk genes without proximity bias

Cristian Regep, Chantriolnt-Andreas Kapourani, Emre Sofyalı, Agnieszka Dobrowolska, Giannis Loukas, Andrew Anighoro, Eleonora Canale, Torsten Gross, Marco P. Licciardello, Revant Gupta, Sorina Maciuca, Tariq Desai, Alice Del Vecchio, Cameron Field, Karl Gemayel, , Lindsay Edwards

Rosalind, a DNA foundation model, predicts variant-gene regulatory relationships without proximity bias, identifying distal genes as more impactful in osteoporosis.

bioRxiv · Mar 12, 2026 · PreprintGenetics

Identification of C elegans strains using a fully convolutional neural network on behavioural dynamics

Avelino Javer, André E.X. Brown, Iasonas Kokkinos, Jens Rittscher

This paper develops a deep learning model to classify C. elegans strains using behavioural dynamics and shows it outperforms hand-crafted features.

bioRxiv · Oct 3, 2018 · PreprintAnimal Behavior & Cognition

Powerful and interpretable behavioural features for quantitative phenotyping of C. elegans

Avelino Javer, Lidia Ripoll-Sanchez, André E.X. Brown

The paper introduces interpretable handcrafted features for quantifying C. elegans behavior, showing improved performance in classifying mutant strains and detecting behavioral changes in optogenetic experiments.

bioRxiv · Aug 9, 2018 · PreprintAnimal Behavior & Cognition

Recurrent Neural Networks with Interpretable Cells Predict and Classify Worm Behaviour

Kezhi Li, Avelino Javer, Eric E. Keaveny, Andre E.X. Brown

This paper uses a multilayer RNN to generate and classify C. elegans behaviour, finding that interpretable neurons correlate with observable features and improve strain classification.

bioRxiv · Nov 20, 2017 · PreprintAnimal Behavior & Cognition