default search action
Nature Computational Science, Volume 1
Volume 1, Number 1, 2021
- Celebrating today, inspiring tomorrow. 1
- Amanda Casari
, Katie McLaughlin
Open source ecosystems need equitable credit across contributions. 2 - Matthew K. Horton
Promises and perils of computational materials databases. 3-5 - Rosalind M. Eggo, Jeanette Dawa
The importance of local context in COVID-19 models. 6-8 - Moritz U. G. Kraemer, Samuel V. Scarpino, Vukosi Marivate
Data curation during a pandemic and lessons learned from COVID-19. 9-10 - Fernando Chirigati, Ananya Rastogi:
Connecting Black women in computational biology. 11-13 - Fernando Chirigati:
Computationally designing synthesizable molecules. 14 - Jie Pan
Characterizing true quantum computing power. 15 - Ananya Rastogi:
Parameter inference for systems biology models. 16 - Jie Pan
Modeling higher-order lattice anharmonicity. 17 - Gábor Balázsi
Discovering evolutionary hidden treasures. 18-19 - Fanjie Meng, Hoi Sung Chung
Kinetics of amyloid β from deep learning. 20-21 - Hanna Najgebauer, Umberto Perron
Redefining false discoveries in cancer data analyses. 22-23 - Tony Liu, Lyle H. Ungar, Konrad P. Kording
Quantifying causality in data science with quasi-experiments. 24-32 - Gihanna Galindez
Lessons from the COVID-19 pandemic for advancing computational drug repurposing strategies. 33-41 - Umberto Raucci
Voice-controlled quantum chemistry. 42-45 - Chi Chen, Yunxing Zuo, Weike Ye
Learning properties of ordered and disordered materials from multi-fidelity data. 46-53 - Rahul Singh, Aayush Sharma, Prashant Singh, Ganesh Balasubramanian, Duane D. Johnson:
Accelerating computational modeling and design of high-entropy alloys. 54-61 - Hiroyuki Kuwahara
Stable maintenance of hidden switches as a strategy to increase the gene expression stability. 62-70 - Thomas Löhr
A kinetic ensemble of the Alzheimer's Aβ peptide. 71-78 - Le Yang
An efficient and effective method to identify significantly perturbed subnetworks in cancer. 79-88
Volume 1, Number 2, 2021
- Hail, software! 89
- Annarita Giani:
Quantum computing opportunities in renewable energy. 90-91 - Lois Curfman McInnes
How community software ecosystems can unlock the potential of exascale computing. 92-94 - Jie Pan
Scaling up system size in materials simulation. 95 - Fernando Chirigati:
Predicting protein structure from cryo-EM data. 96 - Ananya Rastogi:
Inspecting treatment benefit in clinical drug trials. 97 - Kathy Leung
Quantifying the uncertainty of CovidSim. 98-99 - Stephane Bugeon
Towards a consistent neuron classification. 100-101 - Florian Klimm
Functional change along cellular trajectories. 102-103 - Peter Bauer
The digital revolution of Earth-system science. 104-113 - Aleksey K. Fedorov
Towards practical applications in quantum computational biology. 114-119 - Rohan Gala
Consistent cross-modal identification of cortical neurons with coupled autoencoders. 120-127 - Wouter Edeling, Hamid Arabnejad
The impact of uncertainty on predictions of the CovidSim epidemiological code. 128-135 - James C. Knight
Larger GPU-accelerated brain simulations with procedural connectivity. 136-142 - Brian B. Avants
Similarity-driven multi-view embeddings from high-dimensional biomedical data. 143-152 - Alexander G. B. Grønning
Enabling single-cell trajectory network enrichment. 153-163
Volume 1, Number 3, 2021
- Shining a light on the peer review process. 165
- Karen E. Willcox
The imperative of physics-based modeling and inverse theory in computational science. 166-168 - Rebecca Knowles
We need to talk about the lack of investment in digital research infrastructure. 169-171 - Fernando Chirigati:
Porting software without affecting scientific results. 172 - Ananya Rastogi:
Interpretable predictions of cellular behavior. 173 - Jie Pan
Simulating thermal physics on quantum computers. 174 - Fida K. Dankar
Data privacy through participant empowerment. 175-176 - Shulei Wang
Revisiting colocalization via optimal transport. 177-178 - Sokseiha Muy, Nicola Marzari
On the design of solid-state Li-ion batteries. 179-180 - Shiqiang Wang
Efficient deep learning. 181-182 - Michael Scherer
Machine learning for deciphering cell heterogeneity and gene regulation. 183-191 - Dennis Grishin
Citizen-centered, auditable and privacy-preserving population genomics. 192-198 - Carla Tameling, Stefan Stoldt
Colocalization for super-resolution microscopy via optimal transport. 199-211 - Michael W. Swift, James W. Swift, Yue Qi
Modeling the electrical double layer at solid-state electrochemical interfaces. 212-220 - Bin Li
Random sketch learning for deep neural networks in edge computing. 221-228 - Xian Yeow Lee
Fast inverse design of microstructures via generative invariance networks. 229-238 - Brian B. Avants
Publisher Correction: Similarity-driven multi-view embeddings from high-dimensional biomedical data. 239
Volume 1, Number 4, 2021
- To review or not to review. 241
- Kala M. Mehta
Designing a biomedical coding program focused on inclusivity and agency. 242-243 - Jie Pan
Can machines learn with hard constraints? 244 - Ananya Rastogi:
Comparing single-cell datasets. 245 - Jie Pan:
Computationally probing exciton dynamics. 246 - Dvir Aran
Extracting insights from heterogeneous tissues. 247-248 - Denise Syndercombe Court
Protecting against racial bias in DNA databasing. 249-250 - Jennifer E. Adair
A key toolbox for cellular barcoding analysis. 251-252 - Chong Jin
Cell-type-aware analysis of RNA-seq data. 253-261 - Marta Pelizzola
Multiple haplotype reconstruction from allele frequency data. 262-271 - Jacob A. Blindenbach, Karthik Anand Jagadeesh, Gill Bejerano
Avoiding genetic racial profiling in criminal DNA profile databases. 272-279 - Diego A. Espinoza
Interrogation of clonal tracking data using barcodetrackR. 280-289 - Phillip M. Maffettone
Crystallography companion agent for high-throughput materials discovery. 290-297
Volume 1, Number 5, 2021
- Theorists and experimentalists must join forces. 299
- Kazunori Akiyama
New views of black holes from computational imaging. 300-303 - Fernando Chirigati:
Inverse problem via a Bayesian approach. 304 - Ananya Rastogi:
Insights on protein condensate formation. 305 - Jie Pan
Large-scale transport simulation by deep learning. 306 - Omer San
The digital twin revolution. 307-308 - Jiao Zhao, Hao Xu
A dynamic metabolic map for diabetes. 309-310 - Wenhao Sun
AI tool makes phase identification crystal clear. 311-312 - Steven A. Niederer
Scaling digital twins from the artisanal to the industrial. 313-320 - Tamar Schlick
Biomolecular modeling thrives in the age of technology. 321-331 - Robert Vaser
Time- and memory-efficient genome assembly with Raven. 332-336 - Michael G. Kapteyn
A probabilistic graphical model foundation for enabling predictive digital twins at scale. 337-347 - Marouen Ben Guebila, Ines Thiele:
Dynamic flux balance analysis of whole-body metabolism for type 1 diabetes. 348-361 - Xingcheng Lin
Rapid assessment of T-cell receptor specificity of the immune repertoire. 362-373 - Shaoheng Liang
Single-cell manifold-preserving feature selection for detecting rare cell populations. 374-384
Volume 1, Number 6, 2021
- Networking in times of pandemic. 385
- Fernando Chirigati:
Accurate and efficient fluid flow analysis. 386 - Ananya Rastogi:
Data generation for training biomedical models. 387 - Jie Pan
Mathematically exploring wrinkle evolution. 388 - Patrick J. Coles
Seeking quantum advantage for neural networks. 389-390 - Mikel Hernaez
Towards scalable genomic data access. 391-392 - Eric R. Gamazon
Detecting context-dependent gene regulation. 393-394 - Sonia Tarazona, Angeles Arzalluz-Luque
Undisclosed, unmet and neglected challenges in multi-omics studies. 395-402 - Amira Abbas, David Sutter
The power of quantum neural networks. 403-409 - Carla Lupo
Maximally localized dynamical quantum embedding for solving many-body correlated systems. 410-420 - Elena Vigorito
Detection of quantitative trait loci from RNA-seq data with or without genotypes using BaseQTL. 421-432 - Yuanfang Guan
A survival model generalized to regression learning algorithms. 433-440 - Hao Hou, Brent S. Pedersen, Aaron R. Quinlan
Balancing efficient analysis and storage of quantitative genomics data with the D4 format and d4tools. 441-447 - Shaoheng Liang
Publisher Correction: Single-cell manifold-preserving feature selection for detecting rare cell populations. 448
Volume 1, Number 7, 2021
- But is the code (re)usable? 449
- Geoffrey Lovelace
Computational challenges in numerical relativity in the gravitational-wave era. 450-452 - Jie Pan
Improving chemical accuracy with neural networks. 453 - Fernando Chirigati:
Detection of war destruction from satellite images. 454 - Ananya Rastogi:
COVID-19 prognosis from a longitudinal dataset. 455 - Osama Abdin
Rapid protein model refinement by deep learning. 456-457 - Houlong Zhuang
From evidence to new high-entropy alloys. 458-459 - Jun Ding
A versatile model for single-cell data analysis. 460-461 - Xiaoyang Jing
Fast and effective protein model refinement using deep graph neural networks. 462-469 - Minh-Quyet Ha
Evidence-based recommender system for high-entropy alloys. 470-478 - Qiyuan Zhao
Simultaneously improving reaction coverage and computational cost in automated reaction prediction tasks. 479-490 - Hantao Shu
Modeling gene regulatory networks using neural network architectures. 491-501 - Carla Lupo
Publisher Correction: Maximally localized dynamical quantum embedding for solving many-body correlated systems. 502
Volume 1, Number 8, 2021
- Fostering multidisciplinary collaborations. 503
- Fernando Chirigati:
Fluid dynamic behavior of deep-sea sponges. 504 - Ananya Rastogi:
A pandemic's trajectory using PCR testing. 505 - Jie Pan
Simulating synthesis of 3D network polymers. 506 - Rachel Waymack, Zeba Wunderlich
Embryonic development across space and time. 507-508 - Zhiyong Li
Predicting bone regeneration from machine learning. 509-510 - Luca Massimino
The Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework. 511-515 - Sayantan Dutta
From complex datasets to predictive models of embryonic development. 516-520 - Josh C. D'aeth
Optimal national prioritization policies for hospital care during the SARS-CoV-2 pandemic. 521-531 - Chi Wu
A machine learning-based multiscale model to predict bone formation in scaffolds. 532-541 - Ugur Tegin
Scalable optical learning operator. 542-549 - Muhammad Haseeb
High performance computing framework for tera-scale database search of mass spectrometry data. 550-561
Volume 1, Number 9, 2021
- Meet the editors. 563
- Jie Pan
Deep learning boosts RNA prediction. 564 - Jie Pan
Reducing qubit budget in quantum machine learning. 565 - Ananya Rastogi:
Shining a light on mutational signatures. 566 - Nishant Kishore
Mobility data as a proxy for epidemic measures. 567-568 - Ariel Rokem
Detect-ing brain anomalies with autoencoders. 569-570 - Dezsö Módos, John P. Thomas, Tamás Korcsmáros
A handy meta-analysis tool for IBD research. 571-572 - Sudip Sharma
Fast and accurate bootstrap confidence limits on genome-scale phylogenies using little bootstraps. 573-577 - Cupjin Huang, Fang Zhang, Michael Newman, Xiaotong Ni, Dawei Ding
Efficient parallelization of tensor network contraction for simulating quantum computation. 578-587 - Roman Levin, Dennis L. Chao
Insights into population behavior during the COVID-19 pandemic from cell phone mobility data and manifold learning. 588-597 - Maxime Chamberland
Detecting microstructural deviations in individuals with deep diffusion MRI tractometry. 598-606 - Paul J. Blazek
Explainable neural networks that simulate reasoning. 607-618 - Aamir Faisal Ansari, Yugandhar B. S. Reddy, Janhavi Raut, Narendra M. Dixit
An efficient and scalable top-down method for predicting structures of microbial communities. 619-628
Volume 1, Number 10, 2021
- Moving towards reproducible machine learning. 629-630
- Fabio J. Cortes Rodriguez, Matteo Dal Peraro, Luciano A. Abriata
Democratizing interactive, immersive experiences for science education with WebXR. 631-632 - Fernando Chirigati:
Eva to the rescue. 633 - Kaitlin McCardle:
Computationally guided zeolite phase control. 634 - Jie Pan:
Physics-educated DL refines phase mapping. 635 - Ananya Rastogi:
High-performance modeling toolkit. 636 - Kaitlin McCardle:
Predicting reactivity with a push from theory. 637 - Jordi Tura
Boosting simulation of quantum computers. 638-639 - Boyang Ji
Microbial community dynamics revisited. 640-641 - Laura Alessandretti
A new computational model for human navigation. 642-643 - Evert P. L. van Nieuwenburg
To V or not to V. 644-645 - Yuan Ping
Computational design of quantum defects in two-dimensional materials. 646-654 - Alejandro Fontal
Climatic signatures in the different COVID-19 pandemic waves across both hemispheres. 655-665 - Xiang Zhang
Population-scale identification of differential adverse events before and during a pandemic. 666-677 - Christian Bongiorno, Yulun Zhou, Marta Kryven
Vector-based pedestrian navigation in cities. 678-685 - Junqi Yin
Neural network-based order parameter for phase transitions and its applications in high-entropy alloys. 686-693 - Gordon Lemmon
A Poisson binomial-based statistical testing framework for comorbidity discovery across electronic health record datasets. 694-702 - Luca Massimino
Author Correction: The Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework. 703
Volume 1, Number 11, 2021
- For the greatest benefit to humankind. 705-706
- Kaitlin McCardle:
Modeling historical impacts of fisheries on biomass. 707 - Jie Pan:
Coupling mechanics into membrane electrochemistry. 708 - Fernando Chirigati:
Accurate short-term precipitation prediction. 709 - Ananya Rastogi:
Accuracy and fairness go hand in hand. 710 - Dorit M. Hammerling
Advancing data compression via noise detection. 711-712 - Milan Klöwer
Compressing atmospheric data into its real information content. 713-724 - Liang Zeng
Modeling galvanostatic charge-discharge of nanoporous supercapacitors. 725-731 - Jerelle A. Joseph
Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy. 732-743 - Ehsan Kharazmi, Min Cai, Xiaoning Zheng
Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks. 744-753 - Phillip J. Brown, J. Edward F. Green
A rigid body framework for multicellular modeling. 754-766 - Tamar Schlick
Publisher Correction: Biomolecular modeling thrives in the age of technology. 767
Volume 1, Number 12, 2021
- Fighting COVID-19 with HPC. 769-770
- Neda Mohammadi
Thinking fast and slow in disaster decision-making with Smart City Digital Twins. 771-773 - Fernando Chirigati:
Learning to read. 774 - Ananya Rastogi:
Evolution through the lens of genetic codes. 775 - Jie Pan:
Analyzing noise for quantum advantage. 776 - Kaitlin McCardle:
Pushing the bounds of multiconfigurational methods. 777 - Pu Wang
Bridging human mobility and urban growth. 778-779 - Jianwei Sun
Application of wavefunction methods to metals. 780-781 - Ad Aertsen:
Insights into hippocampal network function. 782-783 - Hani Jieun Kim
Uncovering cell identity through differential stability with Cepo. 784-790 - Fengli Xu
Emergence of urban growth patterns from human mobility behavior. 791-800 - Tina N. Mihm
A shortcut to the thermodynamic limit for quantum many-body calculations of metals. 801-808 - Yuchi Qiu
Cluster learning-assisted directed evolution. 809-818 - Teeratorn Kadeethum
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. 819-829 - Segundo Jose Guzman
How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex-dentate gyrus-CA3 network. 830-842
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-12-29 01:16 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: