Author

Filip Ginter

University of TurkuORCID 0000-0002-5484-6103Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Research Focus:gene regulatory network inference· 2 Assay:protein sequence· 2 Approach:benchmark study· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Jari BjörneiD· 2 shared Suwisa KaewphaniD· 2 shared Aashish JainiD· 1 shared Adrian AltenhoffiD· 1 shared Alberto PaccanaroiD· 1 shared Alessandro PetriniiD· 1 shared Alfredo BensoiD· 1 shared Ali Ebrahimpour-BoroojenyiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 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 papersBioinformatics

Jari BjörneORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJun 12, 2026

On the state of protein function prediction: a report on the fourth CAFA challenge

Rashika Ramola, M. Clara De Paolis Kaluza, Damiano Piovesan…·Maarten J. M. F. Reijnders

This paper reports on the fourth CAFA challenge, showing improvements in Gene Ontology term prediction but highlighting challenges in new evaluation settings.

DOI 10.64898/2026.05.06.722942

protein sequencestatistical model

𝕏 PostBluesky

BioinformaticsIEEE Transactions on Computational Biology and BioinformaticsPeer-reviewedDec 11, 2020

Neural network and random forest models in protein function prediction

Kai Hakala, Suwisa Kaewphan, Jari Björne…·Filip Ginter

The paper develops an ensemble system combining random forest and neural network models to predict protein functions using sequence and taxonomic features, showing competitive performance in CAFA3 evaluations.

29 citations

protein sequencemachine learning (classical)

𝕏 PostBluesky