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Nature Computational Science
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📢Out now! Zilin Li, Xihao Li, and colleagues present an all-in-one pipeline for computationally efficient meta-analysis of multiple biobank-scale whole-genome/whole-exome studies. www.nature.com/articles/s43... 🖥️ 🧬
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📢Our opinion piece for the May issue of our 5-year Anniversary series is now live! Jianyi Yang and colleagues discuss how protein language models can effectively decode evolution's grammar, making structure prediction and design scalable. www.nature.com/articles/s43... 🖥️ 🧬
📢A Resource introduces the Open Materials 2024 dataset (OMat24), with more than 110 million diverse DFT calculations. Models trained on OMat24 achieve high accuracy and can eliminate systematic biases across model architectures. www.nature.com/articles/s43...
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📢Yuan Gao and colleagues propose Helix, a deep-learning framework for modeling tissue- and context-specific RNA splicing and isoform usage. www.nature.com/articles/s43... #RNASky 🖥️ 🧬
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📢In our latest Editorial, we discuss the co-review initiative created for encouraging the involvement of early-career researchers in the peer review process, while ensuring proper recognition of their service. www.nature.com/articles/s43... #ResearchPublishing
An accompanying News & Views by Chengxuan Chen and Leng Han is also available for this paper! www.nature.com/articles/s43... #RNASky 🖥️ 🧬
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🚨Our May issue is now live, including a method to design dynamic unstructured proteins, a benchmark to evaluate spatial alignment methods for spatial transcriptomics, and much more! www.nature.com/natcomputsci...
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📢In a Perspective, researchers from @msftresearch.bsky.social explore the extent to which AI democratizes knowledge work, as well as highlight ongoing social and place-based divides. www.nature.com/articles/s43... #ArtificialIntelligence
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📢Out now! Julian Cremer and colleagues present FLOWR🌸, a structure-based flow-matching framework to generate and optimize 3D ligands. www.nature.com/articles/s43... #chemsky
Nature Computational Science
Nature Computational Science
Nature Computational Science
Nature Computational Science
Nature Computational Science
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Nature Computational Science
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Protein language models can effectively decode evolution’s grammar, making structure prediction and design scalable. This transformative capability is accelerating biological discovery and engineering...
This Resource introduces the Open Materials 2024 (OMat24) dataset, offering more than 110 million diverse density functional theory calculations. AI models trained on OMat24 achieve a high accuracy an...www.nature.com
The Open Materials 2024 dataset provides a large-scale, open-access collection of quantum-chemical atomistic simulations that encompasses diverse off-equilibrium crystal structures, thereby making mac...
MetaSTAARlite provides a scalable and resource-efficient summary statistics-based pipeline for powerful, functionally informed rare-variant meta-analysis of biobank-scale sequencing data.
HELIX is a deep learning framework for modeling tissue- and context-specific RNA splicing and isoform usage, prioritizing splicing-altering genetic variants and their functional effects from bulk and ...
FLOWR combines continuous and categorical flow matching with equivariant optimal transport and a separate protein pocket encoder to improve validity, pose accuracy and interaction recovery at substant...
Nature Computational Science now takes part in the co-review initiative in order to encourage the involvement of early-career researchers in the peer review process and to ensure proper recognition of...
A framework called HELIX provides a strategy for predicting full-length transcript isoform usage across diverse biological contexts by integrating sequence features with RNA-binding protein expression...
This Perspective explores the extent to which AI democratizes knowledge work and discusses potential intervention strategies for addressing social and place-based divides.
