Author

Vinícius Alexandre Fiaia Costa

Universidade Federal de GoiásORCID 0000-0001-6479-5963Unclaimed 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:drug response / drug discovery· 2 Organism:Arabidopsis· 1 Research Focus:benchmarking· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Approach:graph neural network· 1

Frequent Co-Authors

Bruno Junior NevesiD· 2 shared Eugene N. MuratoviD· 2 shared Holli‐Joi MartiniD· 2 shared Rodolpho de Campos BragaiD· 2 shared Adriano Defini AndricopuloiD· 1 shared Alexandra Maria dos Santos CarvalhoiD· 1 shared Amanda Santana SilvaiD· 1 shared Bruna Cassimiro BatistaiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Bruno Junior NevesORCID

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2 papers

Recent·Most cited

BioinformaticsJournal of Chemical Information and ModelingPeer-reviewedOct 30, 2026

Instance-Wise Contrastive Graph Neural Network Enables the Discovery of Novel Aedes aegypti Larvicidal Compounds

Karine Santana Lúcio da Costa, Gustavo Henrique Garcia Caldeira, Vinícius Alexandre Fiaia Costa…·Bruno Junior Neves

This paper introduces a contrastive graph neural network to discover novel larvicidal compounds against Aedes aegypti, identifying LC-79 as a potent and selective candidate.

DOI 10.1021/acs.jcim.6c02558

Arabidopsiscontrastive learning

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BioinformaticsbioRxivPreprintNov 19, 2025

Semantic-Aware Graph Embedding Approach Uncovers LC-61, a Potent Anti-Leishmania infantum Compound

Vinícius Alexandre Fiaia Costa, Alexandra Maria dos Santos Carvalho, Rafael Consolin Chelucci…·Bruno Junior Neves

The paper introduces a semantic-aware graph neural network framework for drug discovery, identifying LC-61 as a potent antileishmanial compound with nanomolar activity.

1 citation

graph neural networkdeep learning

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