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ORCIDNature Computational Science, Volume 3
Volume 3, Number 1, 2023
- Cover runners-up of 2022. 1
- Fernando Chirigati:
Leveraging the power of crowds. 2 - Ananya Rastogi:
Deep learning to estimate brain age. 3 - Kaitlin McCardle
:
Uncovering contaminants via machine learning. 4 - Jie Pan:
Large language model for molecular chemistry. 5 - Stefan Vuckovic:
Using AI to navigate through the DFA zoo. 6-7 - Yang Yang, Zewen K. Tuong, Di Yu:
Dimensionality reduction under scrutiny. 8-9 - Towards a purely physics-based computational binding affinity estimation. 10-11
- Mingjian Wen, Evan Walter Clark Spotte-Smith, Samuel M. Blau, Matthew J. McDermott, Aditi S. Krishnapriyan, Kristin A. Persson:
Chemical reaction networks and opportunities for machine learning. 12-24 - Alexander Miessen, Pauline J. Ollitrault, Francesco Tacchino, Ivano Tavernelli:
Quantum algorithms for quantum dynamics. 25-37 - Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J. Kulik:
A transferable recommender approach for selecting the best density functional approximations in chemical discovery. 38-47 - Yiwei Liu, Cheng Zhang, Zhonghua Liu, Donald G. Truhlar, Ying Wang, Xiao He:
Supervised learning of a chemistry functional with damped dispersion. 48-58 - Vivek Govind Kumar, Adithya Polasa, Shilpi Agrawal, Thallapuranam K. Suresh Kumar, Mahmoud Moradi:
Binding affinity estimation from restrained umbrella sampling simulations. 59-70 - Tze Hui Koh, William E. Bishop, Takashi Kawashima, Brian B. Jeon, Ranjani Srinivasan, Yu Mu, Ziqiang Wei, Sandra J. Kuhlman, Misha B. Ahrens, Steven M. Chase, Byron M. Yu:
Dimensionality reduction of calcium-imaged neuronal population activity. 71-85 - Eric D. Sun, Rong Ma, James Zou:
Dynamic visualization of high-dimensional data. 86-100 - R. Patrick Xian, Vincent Stimper, Marios Zacharias, Maciej Dendzik, Shuo Dong, Samuel Beaulieu, Bernhard Schölkopf, Martin Wolf, Laurenz Rettig, Christian Carbogno, Stefan Bauer, Ralph Ernstorfer:
A machine learning route between band mapping and band structure. 101-114
Volume 3, Number 2, 2023
- Why can't we predict earthquakes? 115
- Fernando Chirigati:
Advancing the science of synthesis. 116-117 - Fernando Chirigati:
A successful few drive urban scaling. 118 - Kaitlin McCardle:
Advancing organic reaction discovery. 119 - Jie Pan:
Effective phase analyzer learned from stock images. 120 - Ananya Rastogi:
When and where the climate threshold will be reached. 121 - Yang Jiao:
Evolving wave networks for materials design. 122-123 - Yunan Luo:
Sensing the shape of functional proteins with topology. 124-125 - Sandeep Choubey:
Gene regulation meets Bayesian non-parametrics. 126-127 - Sunkyu Yu:
Evolving scattering networks for engineering disorder. 128-138 - Julia Westermayr, Joe Gilkes, Rhyan Barrett, Reinhard Johann Maurer:
High-throughput property-driven generative design of functional organic molecules. 139-148 - Yuchi Qiu, Guo-Wei Wei:
Persistent spectral theory-guided protein engineering. 149-163 - Tal Einav, Adrian Creanga, Sarah F. Andrews, Adrian B. McDermott, Masaru Kanekiyo:
Harnessing low dimensionality to visualize the antibody-virus landscape for influenza. 164-173 - Zeliha Kilic, Max Schweiger, Camille Moyer, Douglas Shepherd, Steve Pressé:
Gene expression model inference from snapshot RNA data using Bayesian non-parametrics. 174-183
Volume 3, Number 3, 2023
- Guiding element mixing. 185-186
- Kaitlin McCardle:
Understanding cancer drivers and passengers. 187-188 - Kaitlin McCardle:
Accounting for quantum effects in catalysis. 189 - Simon L. Batzner:
Biasing energy surfaces towards the unknown. 190-191 - Revealing trajectories of the mind via non-linear manifolds of brain activity. 192-193
- Oscillations and avalanches coexist in brain networks close to criticality. 194-195
- A single-cell-resolution mathematical model of the CA1 human hippocampus. 196-197
- Dierk Raabe, Jaber Rezaei Mianroodi, Jörg Neugebauer:
Accelerating the design of compositionally complex materials via physics-informed artificial intelligence. 198-209 - Xie Zhang, Jun Kang, Suhuai Wei:
Defect modeling and control in structurally and compositionally complex materials. 210-220 - Alberto Ferrari, Fritz Körmann, Mark Asta, Jörg Neugebauer:
Simulating short-range order in compositionally complex materials. 221-229 - Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, Ying Wai Li, Richard A. Messerly, Sergei Tretiak, Justin S. Smith, Benjamin T. Nebgen:
Uncertainty-driven dynamics for active learning of interatomic potentials. 230-239 - Erica L. Busch, Jessie Huang, Andrew Benz, Tom Wallenstein, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy, Nicholas B. Turk-Browne:
Multi-view manifold learning of human brain-state trajectories. 240-253 - Fabrizio Lombardi, Selver Pepic, Oren Shriki, Gasper Tkacik, Daniele De Martino:
Statistical modeling of adaptive neural networks explains co-existence of avalanches and oscillations in resting human brain. 254-263 - Daniela Gandolfi, Jonathan Mapelli, Sergio M. G. Solinas, Paul Triebkorn, Egidio D'Angelo, Viktor K. Jirsa, Michele Migliore:
Full-scale scaffold model of the human hippocampus CA1 area. 264-276
Volume 3, Number 4, 2023
- Computationally probing moiré magnets. 277-278
- Fernando Chirigati:
Moving toward safer driverless vehicles. 279 - Jie Pan:
Transfer learning for metal-organic frameworks. 280 - Kaitlin McCardle:
Learning properties of metal complexes. 281 - David Soriano:
Uncovering magnetic interactions in moiré magnets. 282-284 - Ali Rahnavard:
Omics correlation for efficient network construction. 285-286 - A deep-learning method for studying magnetic superstructures. 287-288
- A machine learning algorithm for studying how molecules self-assemble and function. 289-290
- Sharon Hammes-Schiffer:
Exploring proton-coupled electron transfer at multiple scales. 291-300 - Maalavika Pillai, Emilia Hojel, Mohit Kumar Jolly, Yogesh Goyal:
Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools. 301-313 - Baishun Yang, Yang Li, Hongjun Xiang, Haiqing Lin, Bing Huang:
Moiré magnetic exchange interactions in twisted magnets. 314-320 - He Li, Zechen Tang, Xiaoxun Gong, Nianlong Zou, Wenhui Duan, Yong Xu:
Deep-learning electronic-structure calculation of magnetic superstructures. 321-327 - Alec F. White, Chenghan Li, Xing Zhang, Garnet Kin-Lic Chan:
Quantum harmonic free energies for biomolecules and nanomaterials. 328-333 - Hendrik Jung, Roberto Covino, A. Arjun, Christian Leitold, Christoph Dellago, Peter G. Bolhuis, Gerhard Hummer:
Machine-guided path sampling to discover mechanisms of molecular self-organization. 334-345 - Martin Becker, Huda Nassar, Camilo Espinosa, Ina A. Stelzer, Dorien Feyaerts, Eloïse Berson, Neda Hajiakhoond Bidoki, Alan L. Chang, Geetha Saarunya, Anthony Culos, Davide De Francesco, Ramin Fallahzadeh, Qun Liu, Yeasul Kim, Ivana Maric, Samson Mataraso, Seyedeh Neelufar Payrovnaziri, Thanaphong Phongpreecha, Neal G. Ravindra, Natalie Stanley, Sayane Shome, Yuqi Tan, Melan Thuraiappah, Maria Xenochristou, Lei Xue, Gary M. Shaw, David K. Stevenson, Martin S. Angst, Brice Gaudilliere, Nima Aghaeepour:
Large-scale correlation network construction for unraveling the coordination of complex biological systems. 346-359
Volume 3, Number 5, 2023
- Experimental validation, anyone? 361
- Nicholas David, Wenhao Sun, Connor W. Coley:
The promise and pitfalls of AI for molecular and materials synthesis. 362-364 - Ananya Rastogi:
Exploring robust pattern formation. 365 - Ava P. Amini, Kevin K. Yang:
From noise to protein with image models. 366-367 - Alberto Corigliano:
Discovering kirigami patterns. 368-369 - A machine learning-based model for the quantification of mental conflict. 370-371
- A graph neural network for predicting the adsorption energy of molecules on metal surfaces. 372-373
- Guido Caldarelli, Elsa Arcaute, Marc Barthelemy, Michael Batty, Carlos Gershenson, Dirk Helbing, Stefano Mancuso, Yamir Moreno, José J. Ramasco, Céline Rozenblat, Ángel Sánchez, José Luis Fernández-Villacañas:
The role of complexity for digital twins of cities. 374-381 - Jin Sub Lee, Jisun Kim, Philip M. Kim:
Score-based generative modeling for de novo protein design. 382-392 - Jacob Saldinger, Matt Raymond, Paolo Elvati, Angela Violi:
Domain-agnostic predictions of nanoscale interactions in proteins and nanoparticles. 393-402 - Gengjie Jia, Yu Li, Xue Zhong, Kanix Wang, Milton Pividori, Rabab Alomairy, Aniello Esposito, Hatem Ltaief, Chikashi Terao, Masato Akiyama, Koichi Matsuda, David E. Keyes, Hae Kyung Im, Takashi Gojobori, Yoichiro Kamatani, Michiaki Kubo, Nancy J. Cox, James A. Evans, Xin Gao, Andrey Rzhetsky:
The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci. 403-417 - Yuki Konaka, Honda Naoki:
Decoding reward-curiosity conflict in decision-making from irrational behaviors. 418-432 - Sergio Pablo-García, Santiago Morandi, Rodrigo A. Vargas-Hernández, Kjell Jorner, Zarko Ivkovic, Núria López, Alán Aspuru-Guzik:
Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks. 433-442 - Levi H. Dudte, Gary P. T. Choi, Kaitlyn P. Becker, L. Mahadevan:
An additive framework for kirigami design. 443-454
Volume 3, Number 6, 2023
- A computational quest for a sustainable world. 455-456
- Sophia Chen:
Are quantum computers really energy efficient? 457-460 - Edmundo Molina-Perez:
Harnessing the power of decision-support tools to trigger climate action. 461-463 - Kaitlin McCardle:
Collaborations drive energy storage research. 464-466 - Kaitlin McCardle:
People, places, and the planet. 467-469 - Kaitlin McCardle:
Little by little, a bird builds its nest. 470-472 - Jie Pan:
Towards a welcoming climate for LGBTQ people. 473-475 - Ananya Rastogi:
Particle picking in tomograms. 476 - Fernando Chirigati:
Experts go deeper. 477 - Kaitlin McCardle:
Building molecules across the periodic table. 478 - Jie Pan:
Treating quantum states as human faces. 479 - Marco Bernardi:
Computing electron dynamics in momentum space. 480-481 - A single-cell transcriptomic meta-analysis platform for inflammatory bowel disease. 482-483
- Why bigger quantum neural networks do better. 484-485
- Matthew MacLeod, Prado Domercq, Sam Harrison, Antonia Praetorius:
Computational models to confront the complex pollution footprint of plastic in the environment. 486-494 - Jakub Kubecka, Yosef Knattrup, Morten Engsvang, Andreas Buchgraitz Jensen, Daniel Ayoubi, Haide Wu, Ove Christiansen, Jonas Elm:
Current and future machine learning approaches for modeling atmospheric cluster formation. 495-503 - Ke R. Yang, Gregory W. Kyro, Victor S. Batista:
The landscape of computational approaches for artificial photosynthesis. 504-513 - Loïc Lannelongue, Hans-Erik G. Aronson, Alex Bateman, Ewan Birney, Talia Caplan, Martin Juckes, Johanna R. McEntyre, Andrew D. Morris, Gerry Reilly, Michael Inouye:
GREENER principles for environmentally sustainable computational science. 514-521 - Hu Nie, Peilu Lin, Yu Zhang, Yihong Wan, Jiesheng Li, Chengqian Yin, Lei Zhang:
Single-cell meta-analysis of inflammatory bowel disease with scIBD. 522-531 - Zhenfa Zheng, Yongliang Shi, Jin-Jian Zhou, Oleg V. Prezhdo, Qijing Zheng, Jin Zhao:
Ab initio real-time quantum dynamics of charge carriers in momentum space. 532-541 - Martin Larocca, Nathan Ju, Diego García-Martín, Patrick J. Coles, Marco Cerezo:
Theory of overparametrization in quantum neural networks. 542-551 - Luca Cappelletti, Tommaso Fontana, Elena Casiraghi, Vida Ravanmehr, Tiffany J. Callahan, Carlos Cano, Marcin P. Joachimiak, Christopher J. Mungall, Peter N. Robinson, Justin T. Reese, Giorgio Valentini:
GRAPE for fast and scalable graph processing and random-walk-based embedding. 552-568 - He Li, Zechen Tang, Xiaoxun Gong, Nianlong Zou, Wenhui Duan, Yong Xu:
Author Correction: Deep-learning electronic-structure calculation of magnetic superstructures. 569
Volume 3, Number 7, 2023
- Of data and transparency. 571
- Da Yan, Adam D. Smith, Cheng-Chien Chen:
Structure prediction and materials design with generative neural networks. 572-574 - Jie Pan:
Physics-inspired model for online content dynamics. 575 - Fernando Chirigati:
A language model for medical predictive tasks. 576 - Kaitlin McCardle:
Shedding light on microbiome-drug interactions. 577 - James P. Bagrow:
Using fast and slow data to unfold city dynamics. 578-579 - Chris C. R. Smith:
Machine learning speeds up genetic structure analysis. 580-581 - Zheyang Zhang, Jialiang Huang:
Cellular deconvolution with continuous transitions. 582-583 - Pawel F. Przytycki:
Uncovering the genetic circuits that drive diseases. 584-585 - A software resource for large graph processing and analysis. 586-587
- Luca Pappalardo, Ed Manley, Vedran Sekara, Laura Alessandretti:
Future directions in human mobility science. 588-600 - Alex Chohlas-Wood, Madison Coots, Sharad Goel, Julian Nyarko:
Designing equitable algorithms. 601-610 - Yanyan Xu, Luis E. Olmos, David Mateo, Alberto Hernando, Xiaokang Yang, Marta C. González:
Urban dynamics through the lens of human mobility. 611-620 - Albert Dominguez Mantes, Daniel Mas Montserrat, Carlos D. Bustamante, Xavier Giró-i-Nieto, Alexander G. Ioannidis:
Neural ADMIXTURE for rapid genomic clustering. 621-629 - Liyang Song, Xiwei Sun, Ting Qi, Jian Yang:
Mixed model-based deconvolution of cell-state abundances (MeDuSA) along a one-dimensional trajectory. 630-643 - Xi Chen, Yuan Wang, Antonio Cappuccio, Wan-Sze Cheng, Frederique Ruf Zamojski, Venugopalan D. Nair, Clare M. Miller, Aliza B. Rubenstein, German Nudelman, Alicja Tadych, Chandra L. Theesfeld, Alexandria Vornholt, Mary-Catherine George, Felicia Ruffin, Michael Dagher, Daniel G. Chawla, Alessandra Soares-Schanoski, Rachel R. Spurbeck, Lishomwa C. Ndhlovu, Robert P. Sebra, Steven H. Kleinstein, Andrew G. Letizia, Irene Ramos, Vance G. Fowler, Christopher W. Woods, Elena Zaslavsky, Olga G. Troyanskaya, Stuart C. Sealfon:
Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data. 644-657 - Gengjie Jia, Yu Li, Xue Zhong, Kanix Wang, Milton Pividori, Rabab Alomairy, Aniello Esposito, Hatem Ltaief, Chikashi Terao, Masato Akiyama, Koichi Matsuda, David E. Keyes, Hae Kyung Im, Takashi Gojobori, Yoichiro Kamatani, Michiaki Kubo, Nancy J. Cox, James A. Evans, Xin Gao, Andrey Rzhetsky:
Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci. 658
Volume 3, Number 8, 2023
- The carbon footprint of computational research. 659
- Michelle N. Meyer, John Basl, David R. Choffnes, Christo Wilson, David M. J. Lazer:
Enhancing the ethics of user-sourced online data collection and sharing. 660-664 - Jie Pan:
Optimal crystal structure solutions. 665 - Ananya Rastogi:
Estimating cell growth rate. 666 - Liguo Wang:
Reference-guided search for open reading frames. 667-668 - Luer Zhong, Rhonda Bacher:
Leveraging remeasured samples in biomedical studies. 669-670 - Energy materials screening with defect graph neural networks. 671-672
- An imaging-based approach to measure atmospheric turbulence. 673-674
- Matthew D. Witman, Anuj Goyal, Tadashi Ogitsu, Anthony H. McDaniel, Stephan Lany:
Defect graph neural networks for materials discovery in high-temperature clean-energy applications. 675-686 - Yadong Wang, Darui Jin, Junzhang Chen, Xiangzhi Bai:
Revelation of hidden 2D atmospheric turbulence strength fields from turbulence effects in infrared imaging. 687-699 - Ales Varabyou, Beril Erdogdu, Steven L. Salzberg, Mihaela Pertea:
Investigating open reading frames in known and novel transcripts using ORFanage. 700-708 - Hanxuan Ye, Xianyang Zhang, Chen Wang, Ellen L. Goode, Jun Chen:
Batch-effect correction with sample remeasurement in highly confounded case-control studies. 709-719