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Nature Computational Science, Volume 4
Volume 4, Number 1, 2024
- Cover runners-up of 2023. 1
- Alexis Palmer, Noah A. Smith, Arthur Spirling:
Using proprietary language models in academic research requires explicit justification. 2-3 - Fernando Chirigati:
Mining the chemical space for new antibiotics. 4 - Daniel T. O'Brien:
Disentangling truth from bias in naturally occurring data. 5-6 - A transformer method that predicts human lives from sequences of life events. 7-8
- Learning physical laws from observations of complex dynamics. 9-10
- Roger G. Melko, Juan Carrasquilla:
Language models for quantum simulation. 11-18 - Zachary Friedenberger, Richard Naud:
Dendritic excitability controls overdispersion. 19-28 - Junbo Shen, Qinze Yu, Shenyang Chen, Qingxiong Tan, Jingchen Li, Yu Li:
Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model. 29-42 - Germans Savcisens, Tina Eliassi-Rad, Lars Kai Hansen, Laust Hvas Mortensen, Lau Lilleholt, Anna Rogers, Ingo Zettler, Sune Lehmann:
Using sequences of life-events to predict human lives. 43-56 - Zhi Liu, Uma Bhandaram, Nikhil Garg:
Quantifying spatial under-reporting disparities in resident crowdsourcing. 57-65 - Xiaoli Chen, Beatrice W. Soh, Zi-En Ooi, Eléonore Vissol-Gaudin, Haijun Yu, Kostya S. Novoselov, Kedar Hippalgaonkar, Qianxiao Li:
Constructing custom thermodynamics using deep learning. 66-85
Volume 4, Number 2, 2024
- A look into our non-primary formats. 87-88
- Yang Cao, Alán Aspuru-Guzik:
Accelerating discovery in organic redox flow batteries. 89-91 - Joseph Bakarji:
Distilling data into code. 92-93 - Joshua Weinstein:
Refining the lens of DNA microscopy. 94-95 - Chloe Markey, Samuel Croset, Olivia Ruth Woolley, Can Martin Buldun, Christian Koch, Daniel Koller, Daniel Reker:
Characterizing emerging companies in computational drug development. 96-103 - Téo Lemane, Nolan Lezzoche, Julien Lecubin, Eric Pelletier, Magali Lescot, Rayan Chikhi, Pierre Peterlongo:
Indexing and real-time user-friendly queries in terabyte-sized complex genomic datasets with kmindex and ORA. 104-109 - Paul J. Blazek, Kesavan Venkatesh, Milo M. Lin:
Automated discovery of algorithms from data. 110-118 - Alexander M. Kloosterman, Igor Baars, Björn Högberg:
An error correction strategy for image reconstruction by DNA sequencing microscopy. 119-127 - Wenjie Sun, Meghan Perkins, Mathilde Huyghe, Marisa M. Faraldo, Silvia Fre, Leïla Perié, Anne-Marie Lyne:
Extracting, filtering and simulating cellular barcodes using CellBarcode tools. 128-143
Volume 4, Number 3, 2024
- The increasing potential and challenges of digital twins. 145-146
- Karen Willcox, Brittany Segundo:
The role of computational science in digital twins. 147-149 - Luís M. A. Bettencourt:
Recent achievements and conceptual challenges for urban digital twins. 150-153 - Peter Bauer, Torsten Hoefler, Bjorn Stevens, Wilco Hazeleger:
Digital twins of Earth and the computing challenge of human interaction. 154-157 - Jie Pan:
Materials informatics heralds a collaborative future. 158-160 - Gokay Avci, Kim E. Jelfs:
Enhancing discovery of host-guest binders. 161-162 - Andreas W. Hauser:
Pushing the limits of OFDFT with neural networks. 163-164 - Hod Dana:
Accelerating protein sensor optimization with machine learning. 165-166 - Enabling comparative gene regulatory network analysis on single-cell data with SCORPION. 167-168
- Fei Tao, He Zhang, Chenyuan Zhang:
Advancements and challenges of digital twins in industry. 169-177 - Alberto Ferrari, Karen Willcox:
Digital twins in mechanical and aerospace engineering. 178-183 - Reinhard C. Laubenbacher, Borna Mehrad, Ilya Shmulevich, Natalia A. Trayanova:
Digital twins in medicine. 184-191 - Michael Batty:
Digital twins in city planning. 192-199 - Juan Manuel Parrilla Gutierrez, Jaroslaw M. Granda, Jean-François Ayme, Michal D. Bajczyk, Liam Wilbraham, Leroy Cronin:
Electron density-based GPT for optimization and suggestion of host-guest binders. 200-209 - He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao:
Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning. 210-223 - Sarah J. Wait, Marc Expòsit, Sophia Lin, Michael Rappleye, Justin Daho Lee, Samuel A. Colby, Lily Torp, Anthony Asencio, Annette Smith, Michael Regnier, Farid Moussavi-Harami, David Baker, Christina K. Kim, Andre Berndt:
Machine learning-guided engineering of genetically encoded fluorescent calcium indicators. 224-236 - Daniel Osório, Anna Capasso, S. Gail Eckhardt, Uma Giri, Alexander Somma, Todd M. Pitts, Christopher H. Lieu, Wells A. Messersmith, Stacey M. Bagby, Harinder Singh, Jishnu Das, Nidhi Sahni, S. Stephen Yi, Marieke L. Kuijjer:
Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics data. 237-250
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