Author

Fábio Fabris

University of KentORCID 0000-0001-7159-4668Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Organism:C. elegans· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Organism:Drosophila· 1

Frequent Co-Authors

Alex Alves FreitasiD· 3 shared Daniel H. PalmeriD· 2 shared João Pedro de MagalhãesiD· 2 shared Ahmet Süreyya RifaioğluiD· 1 shared Alan J. MedlariD· 1 shared Alberto PaccanaroiD· 1 shared Alessandro PetriniiD· 1 shared Alex W. CrockeriD· 1 shared

Activity by Year

2019-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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3 shared papersBioinformatics

Alex Alves FreitasORCID

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3 papers

Recent·Most cited

Ageing Transcriptome Meta-Analysis Reveals Similarities Between Key Mammalian Tissues

Daniel H. Palmer, Fábio Fabris, Aoife Doherty, Alex Alves Freitas, João Pedro de Magalhães

This study identifies common ageing transcriptomic signatures across mammalian tissues using meta-analysis and machine learning, revealing shared functional changes and network properties.

Aging · Feb 11, 2021Peer-reviewedBioinformatics

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Naihui Zhou, Yuxiang Jiang, Timothy R. Bergquist, Alexandra J. Lee, Balint Z Kacsoh, Alex W. Crocker, Kimberley A. Lewis, George P. Georghiou, Huy N. Nguyen, Md-Nafiz Hamid, Larry Davis, Tunca Doğan, Volkan Atalay, Ahmet Süreyya Rifaioğlu, Alperen Dalkıran, , Enrico Lavezzo

The paper reports results from the CAFA3 challenge, showing improved computational protein function prediction and new annotations for over 1000 genes through experimental screens in C. albicans, P. aureginosa, and Drosophila.

Genome biology · Nov 19, 2019Peer-reviewedBioinformatics

PICKER-HG: a web server using random forests for classifying human genes into categories

Fábio Fabris, Daniel H. Palmer, Zoya Farooq, João Pedro de Magalhães, Alex Alves Freitas

PICKER-HG is a web server that uses random forests to classify human genes into categories based on user-provided annotations and outputs classification rules.

bioRxiv · Jun 24, 2019 · PreprintBioinformatics