Author

Marcin Magnus

Harvard UniversityORCID 0000-0002-5232-2234Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 5

Signature Assays, Organisms & Methods

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Research Focus:database / resource· 2 Approach:deep learning· 2 Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Research Focus:protein structure prediction· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Elena RivasiD· 4 shared Marcell SzikszaiiD· 3 shared Janusz Marek BujnickiiD· 2 shared Sachin KadyaniD· 2 shared Alex Bateman· 1 shared Andrew GreeniD· 1 shared Anton I. PetroviD· 1 shared Anton S. PetroviD· 1 shared

Activity by Year

2023-2025 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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4 shared papersBioinformatics

Elena RivasORCID

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

RNAcentral in 2026: Genes and literature integration

Andrew Green, Carlos Eduardo Ribas, Isaac Jandalala, Philippa Muston, Colman O’Cathail, Guy Cochrane, Christina Ernst, Lingyun Zhao, Pedro Madrigal, Helen L. Attrill, Steven J Marygold, Doron Lancet, Niv Dobzinski, Patricia P. Chan, Todd M. Lowe, , Blake Sweeney

RNAcentral integrates literature and gene-level data to enhance non-coding RNA sequence analysis and functional understanding.

Nucleic Acids Research · Dec 17, 2025Peer-reviewedBioinformatics

RNAhub - an automated pipeline to search and align RNA homologs with secondary structure assessment

Marcin Magnus, William N. D. Gao, Nivedita Dutta, Quentin Vicens, Elena Rivas

RNAhub generates RNA multiple sequence alignments and assesses conserved RNA structure using covariation analysis.

Nucleic Acids Research · Apr 17, 2025Peer-reviewedBioinformatics

On inputs to deep learning for RNA 3D structure prediction

Marcell Szikszai, Marcin Magnus, Sachin Kadyan, Elena Rivas

The paper identifies differences between protein and RNA structure and proposes RNA-specific methods to improve deep learning models for RNA 3D structure prediction.

bioRxiv · Feb 14, 2025 · PreprintBioinformatics

RNA3DB: a structurally-dissimilar dataset split for training and benchmarking deep learning models for RNA structure prediction

Marcell Szikszai, Marcin Magnus, Siddhant Sanghi, Sachin Kadyan, Nazim Bouatta, Elena Rivas

The paper introduces RNA3DB, a dataset of structured RNAs designed for training and benchmarking deep learning models, with non-redundant sequence and structure splits to improve generalization.

Journal of Molecular Biology · Mar 27, 2024Peer-reviewedBioinformatics

RNA fragment assembly with experimental restraints

Grzegorz Chojnowski, Rafał Zaborowski, Marcin Magnus, Sunandan Mukherjee, Janusz Marek Bujnicki

RNA Masonry assembles RNA fragments into geometrically plausible models using secondary structure constraints and SAXS data.

Bioinformatics · Aug 29, 2023Peer-reviewedBioinformatics