Author

Fariza Tahi

Université Paris-SaclayORCID 0000-0002-3975-5668Unclaimed 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:benchmarking· 6 Assay:protein structure· 5 Approach:benchmark study· 3 Approach:deep learning· 2 Research Focus:protein structure prediction· 2 Approach:statistical model· 2 Research Focus:clustering· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Guillaume PosticiD· 6 shared Clément BernardiD· 5 shared Sahar GhannayiD· 5 shared Éric AngeliD· 2 shared François RadvanyiiD· 2 shared Constance CreuxiD· 1 shared Farida ZehraouiiD· 1 shared Loïc OmnesiD· 1 shared

Activity by Year

2024-2025 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 15 mutual co-author links

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6 shared papersBioinformatics

Guillaume PosticORCID

Mutual co-authors in cluster

Author profile →

8 papers

Recent·Most cited

RNAdvisor 2: A unified platform for RNA 3D model quality assessment using metrics, scoring functions, and meta-metrics

Clément Bernard, Guillaume Postic, Sahar Ghannay, Fariza Tahi

RNAdvisor 2 improves RNA 3D structure quality assessment by introducing meta-metrics, new scoring functions, and a web server, while enhancing the command-line tool's stability and extensibility.

Scientific Reports · Nov 23, 2025Peer-reviewedBioinformatics

A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: focus on pseudoknots identification

Loïc Omnes, Éric Angel, Pierre Bartet, François Radvanyi, Fariza Tahi

This paper introduces DivideFold, a deep learning method for predicting RNA secondary structures including pseudoknots in long sequences, showing improved performance over existing methods.

PLoS ONE · Apr 25, 2025Peer-reviewedBioinformatics

Has AlphaFold 3 reached its success for RNAs?

Clément Bernard, Guillaume Postic, Sahar Ghannay, Fariza Tahi

This paper evaluates AlphaFold 3's performance in predicting RNA 3D structures using multiple test sets and compares it to other methods.

Acta Crystallographica Section D Structural Biology · Jan 23, 2025Peer-reviewedBioinformatics

Semi-supervised segmentation of RNA 3D structuresusing density-based clustering

Quoc Khang Le, Éric Angel, Fariza Tahi, Guillaume Postic

This paper introduces RNA3DClust, a density-based clustering method for segmenting RNA 3D structures into functional domains, showing consistency with biological function and evolution.

Computational and Structural Biotechnology Journal · Jan 1, 2025Peer-reviewedBioinformatics

RNA-TorsionBERT: leveraging language models for RNA 3D torsion angles prediction

Clément Bernard, Guillaume Postic, Sahar Ghannay, Fariza Tahi

This work introduces RNA-TorsionBERT, a language model for predicting RNA torsion angles from sequence data, showing improved accuracy over existing methods.

Bioinformatics · Dec 26, 2024Peer-reviewedBioinformatics

Comparison and benchmark of deep learning methods for non-coding RNA classification

Constance Creux, Farida Zehraoui, François Radvanyi, Fariza Tahi

This paper benchmarks deep learning methods for non-coding RNA classification, comparing their performance, robustness, and efficiency across datasets.

PLoS Computational Biology · Sep 12, 2024Peer-reviewedBioinformatics

State-of-the-RNArt: benchmarking current methods for RNA 3D structure prediction

Clément Bernard, Guillaume Postic, Sahar Ghannay, Fariza Tahi

This paper benchmarks nine RNA 3D structure prediction methods using the RNA-Puzzles dataset and provides an online dashboard for their predictions.

NAR Genomics and Bioinformatics · Apr 4, 2024Peer-reviewedBioinformatics

RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality

Clément Bernard, Guillaume Postic, Sahar Ghannay, Fariza Tahi

RNAdvisor benchmarks RNA structural model quality by integrating metrics and scoring functions to evaluate 3D structure predictions.

Briefings in Bioinformatics · Jan 22, 2024Peer-reviewedBioinformatics