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Research Papers

Bimodal masked language modeling for bulk RNA-seq and DNA methylation representation learning

Maxence Gélard | Hakim Benkirane | Thomas Pierrot | Guillaume Richard | Paul-Henry Cournède

ICML 2026 Jul 2026
Figure 1 shows MOJO pipeline. (a) Each modality is first tokenized using linear binning. (b) MOJO, whose core architecture is composed of a mix of convolution and attention operations, is firstly pre-trained through bimodal masked language modeling. (c) Embeddings are probed from MOJO to fine-tune a task-specific head tailored for cancer-type classification or survival analysis.
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InstaNovo-P: A de novo peptide sequencing model for phosphoproteomics

Jesper Lauridsen | Pathmanaban Ramasamy | Rachel Catze | Vahap Canbay | Amandla Mabona | Kevin Eloff | Paul Fullwood | Jennifer Ferguson | Annekatrine Kirketerp-Møller | Ida Sofie Goldschmidt | Tine Claeys | Sam van Puyenbroeck | Nicolas Lopez Carranza | Erwin M. Schoof | Lennart Martens | Jeroen Van Goey | Chiara Francavilla | Timothy Patrick Jenkins | Konstantinos Kalogeropoulos

Nature Communications (2026) Jul 2026
Figure 2. Benchmarking and evaluation of InstaNovo-P predictions. A) Comparison of Instanovo and InstaNovo-P peptide recall on the AC-PT (Proteome Tools I-III) and 21PTM dataset. B) Comparison of PrimeNovo and InstaNovo-P peptide recall on the 21PTM dataset. C) Peptide recall for each test dataset for all peptides, and peptides with different number of phosphorylated sites per peptide. D) Peptide recall for each test dataset split by type of phosphorylated residue. E) Peptide recall in each dataset for different FDR thresholds as calculated by database grounding. F) Peptide recall for different FDR thresholds, split by phosphorylated residue type in the FGFR2 dataset.
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Generalizable direct protein sequencing with InstaNexus

Marco Reverenna | Maike Wennekers Nielsen | Darian Stephan Wolff | Jemma Daniel | Elpida Lytra | Suthimon Thumtecho | Pasquale D. Colaianni | Anne Ljungars | Andreas H. Laustsen | Erwin M. Schoof | Jeroen Van Goey | Timothy P. Jenkins | Marie V. Lukassen | Alberto Santos | Konstantinos Kalogeropoulos

Molecular & Cellular Proteomics 2026 Mar 2026
The paper introduces InstaNexus, an optimized, end-to-end workflow for direct protein sequencing. It combines multi-protease sample preparation, AI-driven de novo peptide sequencing using InstaNovo, and a novel assembly pipeline to reconstruct contiguous protein sequences. InstaNexus demonstrates high accuracy and coverage across diverse proteins like nanobodies, antibodies, and de novo designed binders, offering promising applications in therapeutic discovery and immune profiling without relying on reference genomes.
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Protein sequence modelling with Bayesian flow networks

Timothy Atkinson | Thomas D. Barrett | Scott Cameron | Bora Guloglu | Matthew Greenig | Charlie B. Tan | Louis Robinson | Alex Graves | Liviu Copoiu | Alexandre Laterre

Nature Communications (2025) Feb 2026
Figure shows the application of a Bayesian Flow Network (BFN) to protein-sequence modelling
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Annotating the genome at single-nucleotide resolution with DNA foundation models

Bernardo P. de Almeida | Hugo Dalla-Torre | Guillaume Richard | Christopher Blum | Lorenz Hexemer | Maxence Gélard | Javier Mendoza-Revilla | Ziqi Tang | Frederikke I. Marin | David M. Emms | Priyanka Pandey | Stefan Laurent | Marie Lopez | Alexandre Laterre | Maren Lang | Uğur Şahin | Karim Beguir | Thomas Pierrot

Nature Methods (2025) Jan 2026
The SegmentNT neural network architecture consists of a pre-trained DNA encoder (here Nucleotide Transformer (NT) and a segmentation head (here a U-Net)
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GeoGraph: Geometric and Graph-based Ensemble Descriptors for Intrinsically Disordered Proteins

Eoin Quinn | Marco Carobene | Jean Quentin | Sebastien Boyer | Miguel Arbesú | Oliver Bent

NeurIPS 2025 Workshops Dec 2025
GeoGraph, a simulation-informed surrogate trained to predict ensembleaveraged statistics of residue–residue contact-map topology directly from sequence
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A foundational model for joint sequence-function multi-species modeling at scale for long-range genomic prediction

Sam Boshar | Benjamin Evans | Ziqi Tang | Armand Picard | Yanis Adel | Franziska K. Lorbeer | Chandana Rajesh | Tristan Karch | Shawn Sidbon | David Emms | Javier Mendoza-Revilla | Fatimah Al-Ani | Evan Seitz | Yair Schiff | Yohan Bornachot | Ariana Hernandez | Marie Lopez | Alexandre Laterre | Karim Beguir | Peter Koo | Volodymyr Kuleshov | Alexander Stark | Bernardo P. de Almeida | Thomas Pierrot

Dec 2025
NTv3 is InstaDeep’s new multi-species genomics foundation model, designed for 1 Mb, single-nucleotide-resolution prediction, and for bridging representation learning, sequence-to-function modelling, and generative regulatory design within a single framework.
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Bayes-PD: Exploring a Sequence to Binding Bayesian Neural Network model trained on Phage Display data

Ilann Amiaud-Plachy | Michael Blank | Oliver Bent | Sebastien Boyer

NeurIPS 2025 workshop Dec 2025
Figure 2 shows the phage display Poisson model.
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Assessing data size requirements for training generalizable sequence-based TCR specificity models via pan-allelic MHC-I point-mutation ligandome evaluation

Antoine Delaunay | Miles McGibbon | Bachir Djermani | Nikolai Gorbushin | Sergio Chaves García-Mascaraque | Isaac Rayment | Ilya Kizhvatov | Cécile Petit | Maren Lang | Karim Beguir | Ugur Sahin | Liviu Copoiu | Nicolas Lopez Carranza | AndreyTovchigrechko

Scientific Reports Dec 2025
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MEMENTO: Memory-Enhanced Neural Solvers for Routing Problems

Felix Chalumeau | Refiloe Shabe | Noah De Nicola | Arnu Pretorius | Thomas D. Barrett | Nathan Grinsztajn

NeurIPS 2025 (Spotlight) Nov 2025
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Breaking the Performance Ceiling in Reinforcement Learning requires Inference Strategies

Felix Chalumeau | Daniel Rajaonarivonivelomanantsoa | Ruan de Kock | Claude Formanek | Sasha Abramowitz | Oumayma Mahjoub | Wiem Khlifi | Simon Du Toit | Louay Ben Nessir | Refiloe Shabe | Arnol Fokam | Siddarth Singh | Ulrich Mbou Sob | Arnu Pretorius

NeurIPS 2025 (Oral) Nov 2025
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Oryx: a Scalable Sequence Model forMany-Agent Coordination in Offline MARL

Claude Formanek | Omayma Mahjoub | Louay Ben Nessir | Sasha Abramowitz | Ruan de Kock | Wiem Khlifi | Daniel Rajaonarivonivelomanantsoa | Simon Du Toit | Arnol Fokam | Siddarth Singh | Ulrich Mbou Sob | Felix Chalumeau | Arnu Pretorius

NeurIPS 2025 Nov 2025
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