Nature Computational Science
LightNews LightNews
banner
natcomputsci.nature.com
Nature Computational Science
@natcomputsci.nature.com
4.6K followers 180 following 310 posts
A @natureportfolio.nature.com journal on mathematical models and computational methods/tools that help advance science in multiple disciplines. https://www.nature.com/natcomputsci
Posts Replies Media Videos
Pinned
natcomputsci.nature.com
Nature Computational Science @natcomputsci.nature.com · 27d
🚨Our August issue is now live, including quantum solvers for an NP-complete problem, a generative model for information metamaterial design, a method for designing functional RNAs, and much more! Check it out! www.nature.com/natcomputsci...

📰Cover: www.nature.com/articles/s43...
Glowing nodes and flowing light paths between the nodes.
natcomputsci.nature.com
📢A new Resource introduces PathSegmentor, a foundation model for segmenting structures across different anatomical regions and spatial scales. www.nature.com/articles/s43... #Bioimaging

🔓 rdcu.be/ttPkGmX7yy6a
Segment anything in pathology images with natural language - Nature Computational Science
This Resource introduces PathSegmentor—a foundation model that segments 160 pathological categories via natural language prompts, generalizes across datasets and clinical cohorts, and enables scalable...
www.nature.com
September 10, 2026 at 2:04 PM
natcomputsci.nature.com
📢Out now! @mutexazjy.bsky.social and colleagues present MutexaGPT, a multi-agent platform for enzyme engineering that translates intuition into physics-based simulations and thus variant designs. www.nature.com/articles/s43... 🔓 #chemsky
MutexaGPT: an intuition-to-design translator for physics-based enzyme engineering - Nature Computational Science
MutexaGPT turns plain-language enzyme-engineering intuitions into lead mutation designs through AI agent-orchestrated high-throughput molecular modeling, yielding experimentally validated improvements...
www.nature.com
September 10, 2026 at 1:55 PM
natcomputsci.nature.com
📢New work from Zhiping Xu and colleagues reports a physics-transfer learning framework that enables accurate prediction of brain morphogenesis from limited data. www.nature.com/articles/s43... ⚛️

🔓 rdcu.be/z1pnN7nqNiia
Predicting brain morphogenesis via physics-transfer learning - Nature Computational Science
The authors develop a physics-transfer learning framework that learns cortical folding physics from simple geometries and transfers it to complex brain structures, enabling accurate prediction of brai...
www.nature.com
September 9, 2026 at 3:57 PM
natcomputsci.nature.com
📢In a recent Correspondence, George Breckenridge and Feng Li argue that, while testing is an important component of AI safety governance, it should not be treated as a substitute. www.nature.com/articles/s43... #ArtificialIntelligence

🔓 rdcu.be/XFaZdAqXvzWa
AI testing is not AI safety - Nature Computational Science
Nature Computational Science - AI testing is not AI safety
www.nature.com
August 28, 2026 at 1:28 PM
natcomputsci.nature.com
📢Bedoor AlShebli discusses recent work by @wjsu.bsky.social, @kyunghyuncho.bsky.social et al. that finds that authors' rankings of their own AI conference papers predict later citations better than peer-review scores. www.nature.com/articles/s43... #ArtificialIntelligence

🔓 rdcu.be/kFj3SufmJCXa
When authors are the best judges of their work - Nature Computational Science
A large-scale experiment at a major machine learning conference shows that when researchers privately rank their own submissions, those rankings forecast future citations more reliably than peer-revie...
www.nature.com
August 28, 2026 at 1:24 PM
natcomputsci.nature.com
📢Mingda Li and colleagues develop CrysVCD, a valence-constrained approach for efficient crystal generation. @mitchemistry.bsky.social @mitcheme.bsky.social www.nature.com/articles/s43... #chemsky

🔓 rdcu.be/fCeRM
Enhancing materials discovery with valence-constrained design in generative modeling - Nature Computational Science
This work presents an efficient and modular framework called CrysVCD, which integrates chemical rules directly into the generative process for valence-constrained design.
www.nature.com
August 26, 2026 at 1:53 PM
natcomputsci.nature.com
📢Kang Zhang and colleagues introduce PULSE, an AI framework that uses patients' longitudinal EHRs to accurately generate within and cross-modal data from routine clinical laboratory tests. www.nature.com/articles/s43... 🔓 🖥️ 🧬
Longitudinal alignments and syntheses of multimodal clinical data for personalized medicine with the PULSE framework - Nature Computational Science
PULSE is an AI framework that uses patients’ longitudinal electronic health records to accurately generate within- and cross-modal data from routine clinical laboratory tests, enabling cost-effective precision medicine across diverse biomedical settings.
https://www.nature.com/articles/s43588-026-01026-5?utm_source=bluesky&utm_medium=social&utm_campaign=natcomputsci🔓
August 26, 2026 at 1:45 PM
natcomputsci.nature.com
📢 @wjsu.bsky.social, @kyunghyuncho.bsky.social et al. find that authors' rankings of their own AI papers predict later citations better than peer-review scores, suggesting that self-rankings could complement peer review. www.nature.com/articles/s43... 🔓 #SciencePublishing #ArtificialIntelligence
Self-rankings as a predictor of scientific impact beyond peer review - Nature Computational Science
The study finds that authors’ rankings of their own AI conference papers predict later citations better than peer-review scores, suggesting that self-rankings could provide a simple complement to peer...
www.nature.com
August 24, 2026 at 2:09 PM
natcomputsci.nature.com
📢In our latest Editorial, we discuss our policies regarding the appropriate and responsible use of AI. www.nature.com/articles/s43... #SciencePublishing #ResearchPublishing #AcademicPublishing
Responsible and transparent use of AI in scientific publishing - Nature Computational Science
As AI becomes increasingly embedded in research and scientific publishing, transparency, accountability, and human oversight remain essential to safeguarding research integrity.
www.nature.com
August 20, 2026 at 4:13 PM
natcomputsci.nature.com
🚨Our August issue is now live, including quantum solvers for an NP-complete problem, a generative model for information metamaterial design, a method for designing functional RNAs, and much more! Check it out! www.nature.com/natcomputsci...

📰Cover: www.nature.com/articles/s43...
Glowing nodes and flowing light paths between the nodes.
August 20, 2026 at 4:10 PM
natcomputsci.nature.com
📢In the latest Comment for our five-year anniversary series,
@gabegomes.bsky.social and colleagues argue that what grounds trust in autonomous science is not a view inside the model — it's provenance. www.nature.com/articles/s43... #chemsky
Provenance grounds trust in autonomous science - Nature Computational Science
As large language models begin to plan and run experiments on their own, the reflex is to demand that they be interpretable before they are trusted. We argue that what grounds trust in autonomous scie...
www.nature.com
August 20, 2026 at 4:04 PM
natcomputsci.nature.com
📢Out now! @kulikgroup.bsky.social and colleagues introduce targeted benchmarks to probe chemical and structural novelty in generated transition state prediction. www.nature.com/articles/s43... #chemsky

🔓 rdcu.be/fzJeu
Robust generative transition-state models for unseen chemistry - Nature Computational Science
Addressing generalization limits in machine learning models for chemical reactions, this work introduces a pretraining scheme that enables accurate predictions for unseen chemistry and expands computa...
www.nature.com
August 13, 2026 at 2:42 PM
natcomputsci.nature.com
📢New work from @pschwllr.bsky.social and colleagues introduces a model capable of generalizing to unseen Buchwald–Hartwig chemical space, reducing reaction scouting from weeks to minutes. www.nature.com/articles/s43... #chemsky
Robust out-of-distribution prediction of Buchwald–Hartwig reactions - Nature Computational Science
A predictive model capable of generalizing to previously unseen Buchwald–Hartwig chemical space is built to enable rapid, in silico optimization, reducing reaction scouting time from weeks to minutes.
www.nature.com
August 10, 2026 at 2:32 PM
natcomputsci.nature.com
📢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 Science
SpatialFormer, 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
July 31, 2026 at 11:19 AM
natcomputsci.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 Science
This 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
July 31, 2026 at 11:15 AM
natcomputsci.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 Science
MIRACLE is an online continual learning framework that efficiently integrates single-cell multimodal data across batches, modalities, tissues, and diseases.
www.nature.com
July 31, 2026 at 11:06 AM
natcomputsci.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
Rethinking privacy-preserving GWAS benchmarks for governance - Nature Computational Science
Privacy, utility, and efficiency benchmarks have advanced privacy-preserving genome-wide association studies (GWAS) but often fall short of supporting organizational decisions about responsible data s...
www.nature.com
July 23, 2026 at 3:02 PM
natcomputsci.nature.com
🚨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...
Hand-drawn watercolor illustration of a coral reef ecosystem mixed with colorful virus cells and pathogens among sea waves. Image credit: Dusan Stankovic / DigitalVision Vectors / Getty Images
July 23, 2026 at 2:58 PM
Reposted by Nature Computational Science
natrevcomputing.nature.com
Our first Collection brings together Reviews, Perspectives and Comments from foundational computer science, applied computing, and intersections with society, highlighting the global, dynamic, and multifaceted nature of the field, and with it the wide range of our scope: go.nature.com/4gFklc4
July 21, 2026 at 11:10 AM
natcomputsci.nature.com
📢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 Science
This 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
July 22, 2026 at 1:55 PM
natcomputsci.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 Science
We highlight how AlphaFold2 has advanced protein design and inspired the development of artificial intelligence-driven infrastructures for scientific discovery.
www.nature.com
July 15, 2026 at 1:03 PM
natcomputsci.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 Science
Universal 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
July 14, 2026 at 2:15 PM
natcomputsci.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 Science
A 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
July 14, 2026 at 2:10 PM
natcomputsci.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 Science
Larger 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
July 13, 2026 at 4:10 PM
natcomputsci.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 Discovery
With this Collection, the editors invite contributions that advance the foundations and applications of high-fidelity digital twins in drug discovery.
www.nature.com
July 13, 2026 at 2:49 PM