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📢Ole Winther and colleagues present SpatialFormer, a transformer-based model for spatial transcriptomics to learn single-cell multimodal and multi-scale information in the niche context. www.nature.com/articles/s43... 🖥️ 🧬 🔓 rdcu.be/fw3dm

SpatialFormer: universal spatial representation learning from subcellular molecular to multicellular landscapes - Nature Computational ScienceSpatialFormer, a transformer-based model for spatial transcriptomics, learns cell–cell relationships to predict cell co-localization, annotate cell types and niches, and reveal cell communication gene...www.nature.com

📢A new study presents a method that uses multiple structure alignments to capture evolutionary rules and conservation patterns across RNA families, enabling diverse, structure-guided design of functional aptamers and ribozymes. www.nature.com/articles/s43... #RNASky 🔓 rdcu.be/fw25L

Structure-alignment-driven cross-graph modeling for functional RNA design - Nature Computational ScienceThis study presents AlignIF, which uses multiple structure alignments to capture evolutionary rules and conservation patterns across RNA families, enabling diverse, structure-guided designs of functio...www.nature.com

📢Zhen He and colleagues present MIRACLE, an online learning framework for continual integration of single-cell multimodal data. www.nature.com/articles/s43... 🖥️ 🧬

Continual integration of single-cell multimodal data with MIRACLE - Nature Computational ScienceMIRACLE is an online continual learning framework that efficiently integrates single-cell multimodal data across batches, modalities, tissues, and diseases.www.nature.com

📢In our latest Comment for the 5-year anniversary Series, Natnatee Dokmai argues that, while privacy-preserving GWAS has strong technical benchmarks, they should connect formal guarantees to trust, risk, and governance. www.nature.com/articles/s43... 🖥️ 🧬 🔓 rdcu.be/fvszn

🚨Our July issue is now live, including a model that predicts secondary metabolite chemical structures from biosynthetic gene clusters, a Review on organoid intelligence, and much more! Check it out: www.nature.com/natcomputsci... 📰Cover: www.nature.com/articles/s43...

📢New Article out today! Yueming Wang and colleagues introduce personalized models that decode human emotion states from intracranial brain recordings in real time. www.nature.com/articles/s43... #compneuro #CogSci 🔓 rdcu.be/fvaLp

Cross-task, explainable and real-time decoding of human emotion states by integrating gray and white matter intracranial neural activity - Nature Computational ScienceThis study reports personalized models that decode human emotion states from intracranial brain recordings in real time, work across different tasks and uncover key brain networks that could guide fut...www.nature.com

📢AlphaFold2 turns 5 today, and we discuss in our latest Editorial how it has advanced protein design and inspired the development of AI-driven infrastructures. www.nature.com/articles/s43... #alphafold

AlphaFold2 turns five - Nature Computational ScienceWe highlight how AlphaFold2 has advanced protein design and inspired the development of artificial intelligence-driven infrastructures for scientific discovery.www.nature.com

📢Out now! N. M. Anoop Krishnan and colleagues introduce an evaluation framework for assessing the generalization of universal machine learning force fields across the chemical space. www.nature.com/articles/s43... #chemsky 🔓 rdcu.be/ftLgX

UniFFBench: evaluating universal machine learning force fields against experimental measurements - Nature Computational ScienceUniversal machine learning force fields excel on computational benchmarks but consistently fail when tested against experimental measurements of real minerals, underscoring the need for evaluation fra...www.nature.com

📢Tie Jun Cui and colleagues present a generative model for designing information metamaterials, enabling beam steering, near-field focusing and holography, with more than a 1,000-fold acceleration in holographic design. www.nature.com/articles/s43... 🔓 rdcu.be/ftLeD

Generative model for information metamaterial design - Nature Computational ScienceA generative model designs information metamaterials from meta-atoms to programmable arrays, enabling beam steering, focusing and holography with experimental validation and more than 1,000-fold faste...www.nature.com

📢Out now! @chaohou.bsky.social, @yshen.bsky.social and colleagues show that PLMs predict fitness best when outputs align with evolutionary patterns in homologs, with the peak performance occurring at moderate predicted sequence likelihoods. www.nature.com/articles/s43... 🔓 rdcu.be/ftBgt

Understanding language model scaling for protein fitness prediction - Nature Computational ScienceLarger language models do not always perform better at fitness prediction. Hou et al. found that performance depends on whether model outputs match evolutionary patterns in homologs, which is best ach...www.nature.com

🚨Together with other journals from our family, Nature Computational Science invites contributions that advance the foundations and applications of high-fidelity digital twins in drug discovery. Deadline is 22 March, 2027! www.nature.com/collections/... 🖥️ 🧬 #DigitalTwin #ChemSky #DrugDiscovery

Next-Generation Digital Twins for Drug DiscoveryWith this Collection, the editors invite contributions that advance the foundations and applications of high-fidelity digital twins in drug discovery.www.nature.com

📢Out now! Weiluo Ren and colleagues develop a framework for improving the efficiency and scalability of NNQMC with local pseudopotentials. www.nature.com/articles/s43... #chemsky 🔓 rdcu.be/ftfbq

Empowering neural network-based quantum Monte Carlo with local pseudopotentials - Nature Computational ScienceThis study shows that local pseudopotentials boost the efficiency of neural network-based quantum Monte Carlo while preserving accuracy, enabling reliable simulations of large, challenging iron–sulfur...www.nature.com

📢Zexian Zeng and colleagues propose DISSECT, which integrates cytological imaging and spatial transcriptomics to improve cell segmentation and enable reconstruction of spatial single-cell transcriptomes. www.nature.com/articles/s43... 🖥️ 🧬 🔓 rdcu.be/fte6N

Integrating cytological images and spatial transcriptomics for cell segmentation with DISSECT - Nature Computational ScienceThe authors propose a framework that integrates cytological imaging and spatial transcriptomics to improve cell segmentation and enable reconstruction of spatial single-cell transcriptomes.www.nature.com

📢In a new study, Yatish Turakhia and colleagues introduce DIPPER, a GPU-accelerated tool for efficiently reconstructing evolutionary trees from tens of millions of genome sequences. www.nature.com/articles/s43... 🖥️ 🧬 #evosky 🔓 rdcu.be/fsPLo

Ultrafast and ultralarge distance-based phylogenetics using DIPPER - Nature Computational ScienceThis study introduces DIPPER, a GPU-accelerated tool that efficiently reconstructs evolutionary trees from tens of millions of genome sequences, extending scalability by one to two orders of magnitude...www.nature.com

📢A study from @shunda-chen.bsky.social and colleagues proposes NEP89, a foundation model for large-scale molecular dynamics across 89 elements with near-quantum accuracy. www.nature.com/articles/s43... #chemsky 🔓 rdcu.be/fsPw0

NEP89: universal neuroevolution potential for inorganic and organic materials across 89 elements - Nature Computational ScienceThe researchers developed NEP89, a foundation model for large-scale molecular dynamics across 89 elements with near-quantum-level accuracy and high efficiency. It can be rapidly adapted to address com...www.nature.com

📢Shyni Varghese and Paris Brown discuss the evolution of brain-inspired computing, highlighting the challenges of neuromorphic systems in replicating the flexibility, adaptability and efficiency of the human brain. www.nature.com/articles/s43... 🔓 rdcu.be/fsjXG

Computing inspired by the brain: a journey from algorithms to organoids - Nature Computational ScienceOrganoid intelligence represents a new frontier for computing inspired by the human brain. This Review discusses the evolution of brain-inspired computing along with potential challenges for future de...www.nature.com

📢Out now! A study from Gregory A. Voth and colleagues from @uchichemistry.bsky.social introduces HUMID, a coarse-grained framework for proton transport that enables simulations of reactive transport dynamics with improved efficiency. www.nature.com/articles/s43... #chemsky 🔓 rdcu.be/fru7H

Systematic bottom-up coarse-graining of hydrated excess proton transport across scales - Nature Computational ScienceHUMID is a bottom-up coarse-grained framework for proton transport that bridges the quantum and molecular scales, enabling simulations of reactive transport dynamics across diverse environments with o...www.nature.com

📢A new paper introduces RF-PHATE, a supervised visualization method that preserves data structure while revealing biological patterns. www.nature.com/articles/s43... 🔓 rdcu.be/frhdk

Gaining biological insights through supervised data visualization - Nature Computational ScienceThis study introduces RF-PHATE, a supervised visualization method that preserves data structure while revealing biological patterns, enabling insights into disease progression in multiple sclerosis, C...www.nature.com

📢In a new Comment for our 5-year Anniversary series, @profsanderlinden.bsky.social and @yarakyrychenko.bsky.social discuss the dangers and opportunities of social technology. www.nature.com/articles/s43... #cssky 🔓 rdcu.be/fq22F

📢In our latest Editorial, we discuss the large geographical disparities regarding the availability of GPU hardware, and how they impact scientific participation. www.nature.com/articles/s43...