@natcomputsci.nature.com
A @natureportfolio.nature.com journal on mathematical models and computational methods/tools that help advance science in multiple disciplines. https://www.nature.com/natcomputsci
@natcomputsci.nature.com📢Out now! Gisbert Schneider and colleagues pair active learning and geometric deep learning to predict the outcome and site selectivity of chemical reactions from scarce data, helping to accelerate the drug discovery process. www.nature.com/articles/s43... 🔓 #chemsky
@natcomputsci.nature.com📢Can Yang et al. present CellART, a DL framework that recovers individual cells from high-resolution spatial transcriptomics data, predicting cell boundaries and cell types together across different platforms and tissue types. www.nature.com/articles/s43... 🖥️ 🧬
@natcomputsci.nature.com📢Lu Fang and colleagues develop a physics-based in situ learning method that trains ANNs directly within the photonic integrated circuits, turning diverse optical circuits into efficient AI learning hardware. www.nature.com/articles/s43... ⚛️
@natcomputsci.nature.com📢 @boweiqin.bsky.social, @chaosfudan.bsky.social and colleagues present a framework that identifies modulation parameters based on desired spatiotemporal properties. www.nature.com/articles/s43... @iics-fudan.bsky.social #complexity ⚛️
@natcomputsci.nature.com🚨Our September issue is now live, including a single-cell multimodal data integration tool, a foundation model for pathology image segmentation, a study on self-rankings for peer review, and much more! Check it out! www.nature.com/natcomputsci...
📰Cover: www.nature.com/articles/s43...
@natcomputsci.nature.com📢In our latest 5-year Series Comment, Yifan Yang and Fan Xu discuss how the computational design of active materials can expand robotic capabilities in extreme environments, such as the human brain. www.nature.com/articles/s43... #MaterialsScience
@natcomputsci.nature.com📢In our latest Editorial, we discuss how LLMs have made reproducibility more challenging, as well as provide some recommendations on how to report LLM-based research results. www.nature.com/articles/s43... #ArtificialIntelligence #ResearchPublishing
@natcomputsci.nature.com📢 @homahm.bsky.social, @duncanjwatts.bsky.social and colleagues review the literature on the role of algorithmic recommendation and show that evidence linking algorithmic curation to problematic outcomes is inconclusive, calling for the need for more research. www.nature.com/articles/s43... #cssky
@natcomputsci.nature.com📢Out now! Nikita Karetnikov, Iyad Rahwan, and Davor Svetinovic discuss how LLMs are reshaping our understanding of human behavior by acting as proxies in various roles. www.nature.com/articles/s43... @wuvienna.bsky.social #cssky
@natcomputsci.nature.com📢Lisa Hamada and colleagues present TDiMS, a molecular descriptor that summarizes the enumerated pairwise topological distances between molecular substructures, capturing nonlocal interactions. www.nature.com/articles/s43... 🔓 #chemsky
@natcomputsci.nature.comAn accompanying News & Views by Wei Shen for this paper is also available! www.nature.com/articles/s43... #Bioimaging
@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
@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
@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... ⚛️
@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
@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
