Mathematics and computing articles within Nature Communications

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  • Article
    | Open Access

    Most microbiome studies make conclusions based on changes in relative abundance of taxa, inferred from sequencing data. Here, the authors highlight common pitfalls in comparing relative abundance across samples, and identify solutions that reveal microbial changes without the need to estimate total microbial load.

    • James T. Morton
    • , Clarisse Marotz
    •  & Rob Knight

  • Article
    | Open Access

    Understanding local dynamical processes in materials is challenging due to the complexity of the local atomic environments. Here the authors propose a graph dynamical networks approach that is shown to learn the atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations.

    • Tian Xie
    • , Arthur France-Lanord
    •  & Jeffrey C. Grossman

  • Article
    | Open Access

    Deconfined quantum critical points separate two phases with different broken symmetries, which puts them beyond the standard Landau theory of phase transitions. Here the authors present a model with a monopole-free deconfined quantum critical point, making it more amenable to detailed numerical studies.

    • Yuhai Liu
    • , Zhenjiu Wang
    •  & Fakher F. Assaad

  • Perspective
    | Open Access

    Questions of causality are ubiquitous in Earth system sciences and beyond, yet correlation techniques still prevail. This Perspective provides an overview of causal inference methods, identifies promising applications and methodological challenges, and initiates a causality benchmark platform.

    • Jakob Runge
    • , Sebastian Bathiany
    •  & Jakob Zscheischler

  • Article
    | Open Access

    Social contagion cannot only be understood in terms of pairwise interactions among individuals. Here, the authors include higher-order social interactions, the effects of groups, in their model of social contagion, enabling insight into why critical masses are required to initiate social changes.

    • Iacopo Iacopini
    • , Giovanni Petri
    •  & Vito Latora

  • Article
    | Open Access

    Failure to account for heterogeneity in TB risk can mislead model-based evaluation of proposed interventions. Here, the authors introduce a metric to estimate the distribution of risk in populations from routinely collected data and find that variation in infection acquisition is the most impactful.

    • M. Gabriela M. Gomes
    • , Juliane F. Oliveira
    •  & Christian Lienhardt

  • Article
    | Open Access

    Pyroclastic density currents (PDCs) are a major threat during explosive volcanic eruptions, hence the possibility to forecast them would be a vital improvement for risk mitigation. Here the authors present a 3D flow model to quantify the thermal patterns leading to volcanic ash plume collapse conditions.

    • Matteo Trolese
    • , Matteo Cerminara
    •  & Guido Giordano

  • Article
    | Open Access

    For most actors sustained productivity defines success. Here the authors study the careers of actors and identify a "rich-get-richer" mechanism with respect to productivity, the emergence of hot streaks and the presence of gender bias, and are able to predict whether the most productive year of an actor is yet to come.

    • Oliver E. Williams
    • , Lucas Lacasa
    •  & Vito Latora

  • Article
    | Open Access

    Evaporation plays a key role in applications such as cooling and desalination. Here, the authors experimentally demonstrated a unifying relationship between dimensionless flux and driving potential for evaporation kinetics under different working conditions.

    • Zhengmao Lu
    • , Ikuya Kinefuchi
    •  & Evelyn N. Wang

  • Article
    | Open Access

    Cellular uptake of nanoparticles is highly variable between individual cells in a population. Here, the authors show that this heterogeneity is a result of varying numbers of nanoparticle-containing endosomes while the nanoparticle dose per endosome remains constant.

    • Paul Rees
    • , John W. Wills
    •  & Huw D. Summers

  • Article
    | Open Access

    Some next-generation computing may be based in physical systems that respond directly and reciprocally to environmental stimuli. Here, the authors describe a photoresponsive material that autonomously performs computations with incident beams of incoherent white light.

    • Alexander D. Hudson
    • , Matthew R. Ponte
    •  & Kalaichelvi Saravanamuttu

  • Comment
    | Open Access

    In research studies, the need for additional samples to obtain sufficient statistical power has often to be balanced with the experimental costs. One approach to this end is to sequentially collect data until you have sufficient measurements, e.g., when the p-value drops below 0.05. I outline that this approach is common, yet that unadjusted sequential sampling leads to severe statistical issues, such as an inflated rate of false positive findings. As a consequence, the results of such studies are untrustworthy. I identify the statistical methods that can be implemented in order to account for sequential sampling.

    • Casper Albers

  • Article
    | Open Access

    Hyperspectral imaging (HSI) enables recording both morphological and biochemical information, but image acquisition time and geometric distortions limit its clinical applicability. Here the authors overcome these challenges with an endoscope combining HSI and white light to correct for image distortion during freehand operation.

    • Jonghee Yoon
    • , James Joseph
    •  & Sarah E. Bohndiek

  • Article
    | Open Access

    Microfluidic multipoles use arrays of sources and sinks to confine fluids and reagents without the use of physical channels. Here the authors use conformal mappings to predict both convective and diffusive transport in these flows and 3D print multipoles to automate surface-based immunoassays.

    • Pierre-Alexandre Goyette
    • , Étienne Boulais
    •  & Thomas Gervais

  • Article
    | Open Access

    Polygenic risk scores (PRS) have the potential to predict complex diseases and traits from genetic data. Here, Ge et al. develop PRS-CS which uses a Bayesian regression framework, continuous shrinkage (CS) priors and an external LD reference panel for polygenic prediction of binary and quantitative traits from GWAS summary statistics.

    • Tian Ge
    • , Chia-Yen Chen
    •  & Jordan W. Smoller

  • Article
    | Open Access

    Recovering the properties of a network which has suffered adversarial intervention can find applications in uncovering targeted attacks on social networks. Here the authors propose a causal statistical inference framework for reconstructing a network which has suffered non-random, targeted attacks.

    • Yuankun Xue
    •  & Paul Bogdan

  • Article
    | Open Access

    The impacts of technological development on social sphere lack strong empirical foundation. Here the authors presented quantitative analysis of the phenomenon of social acceleration across a range of digital datasets and found that interest appears in bursts that dissipate on decreasing timescales and occur with increasing frequency.

    • Philipp Lorenz-Spreen
    • , Bjarke Mørch Mønsted
    •  & Sune Lehmann

  • Article
    | Open Access

    DNA as a high density storage medium is receiving increasing attention, but long term physical storage is an unsolved problem. Here the authors show that up to 1 TB of data stored as dehydrated DNA spots on a glass cartridge can be retrieved in a spot of water using digital microfluidics with minimal data loss and contamination.

    • Sharon Newman
    • , Ashley P. Stephenson
    •  & Luis Ceze

  • Article
    | Open Access

    Convolutional Neural Networks (CNNs) have reached human-level benchmarks in classifying images, but they can be “fooled” by adversarial examples that elicit bizarre misclassifications from machines. Here, the authors show how humans can anticipate which objects CNNs will see in adversarial images.

    • Zhenglong Zhou
    •  & Chaz Firestone

  • Article
    | Open Access

    Nonlinear machine learning methods have good predictive ability but the lack of transparency of the algorithms can limit their use. Here the authors investigate how these methods approach learning in order to assess the dependability of their decision making.

    • Sebastian Lapuschkin
    • , Stephan Wäldchen
    •  & Klaus-Robert Müller

  • Article
    | Open Access

    Resource sharing over peer-to-peer technological networks is emerging as economically important, yet little is known about how people choose to share in this context. Here, the authors introduce a new game to model sharing, and test how players form sharing strategies depending on technological constraints.

    • Hirokazu Shirado
    • , George Iosifidis
    •  & Nicholas A. Christakis

  • Article
    | Open Access

    Universal cluster states for quantum computing can be assembled without feed-forward by fusing n-photon clusters with linear optics if the fusion success probability is above a threshold p. The authors bound p in terms of n and provide protocols for n = 3 clusters requiring lower fusion probability than before.

    • Mihir Pant
    • , Don Towsley
    •  & Saikat Guha

  • Article
    | Open Access

    Disordered hyperuniformity implies a hidden order on length scales that can be found in various amorphous materials. Klatt et al. analyse the evolution of random point patterns using Llyod’s algorithm and show that they converge to an effectively hyperuniform state regardless of the initial conditions.

    • Michael A. Klatt
    • , Jakov Lovrić
    •  & Salvatore Torquato

  • Article
    | Open Access

    The resolution limitations when using the ubiquitous algorithms that process images obtained using modern techniques are not straightforward to define. Here, the authors examine the performance of localization algorithms and use spatial statistics to provide a metric for assessing the resolution limit of such algorithms.

    • Edward A. K. Cohen
    • , Anish V. Abraham
    •  & Raimund J. Ober

  • Article
    | Open Access

    The incomplete nature and undefined structure of the existing catalysis research data has prevented comprehensive knowledge extraction. Here, the authors report a novel meta-analysis method that identifies correlations between a catalyst’s physico-chemical properties and its performance in a particular reaction.

    • Roman Schmack
    • , Alexandra Friedrich
    •  & Ralph Kraehnert

  • Article
    | Open Access

    Percolation is a tool used to investigate a network’s response as random links are removed. Here the author presents a generic analytic theory to describe how percolation properties are affected in coloured networks, where the colour can represent a network feature such as multiplexity or the belonging to a community.

    • Ivan Kryven

  • Article
    | Open Access

    Designing mechanical metamaterials is challenging because of the large number of non-periodic constituent elements. Here, the authors develop an approach to design arbitrarily shaped metamaterials that is more computationally efficient by six orders of magnitude compared to other approaches.

    • Lucas A. Shaw
    • , Frederick Sun
    •  & Jonathan B. Hopkins

  • Article
    | Open Access

    Similarly to entropy, majorization allows to quantify deviation from uniformity in a wide range of fields. In this paper, the authors use its generalization to the quantum realm to derive a complete set of necessary and sufficient conditions for thermal transformations of quantum states.

    • Gilad Gour
    • , David Jennings
    •  & Iman Marvian

  • Article
    | Open Access

    Predicting plastic deformation in crystals remains challenging owing to the nonlinear nature of stochastic avalanches involved, which resemble the critical phenomena. Salmenjoki et al. use machine learning to predict plastic deformation and show that it works better for those under large strains.

    • Henri Salmenjoki
    • , Mikko J. Alava
    •  & Lasse Laurson

  • Article
    | Open Access

    The software Optimer has aided the programmable one-pot oligosaccharide synthesis with a library of 50 Building BLocks (BBLs). Here, the authors expanded Optimer's validated and virtual libraries of BBLs and developed Auto-CHO, a software which allows the one-pot programmable synthesis of more complex glycans.

    • Cheng-Wei Cheng
    • , Yixuan Zhou
    •  & Chi-Huey Wong

  • Article
    | Open Access

    Diversity is believed to raise effectiveness and performance but it contains many aspects. Here the authors studied the relationship between research impact and five classes of diversity and found that ethnic diversity had the strongest correlation with scientific impact.

    • Bedoor K. AlShebli
    • , Talal Rahwan
    •  & Wei Lee Woon

  • Article
    | Open Access

    Modern microscopes can generate high volumes of 3D images, driving difficulties in data handling and processing. Here, the authors present a content-adaptive image representation as an alternative to standard pixels that goes beyond data compression to overcome storage, memory, and processing bottlenecks.

    • Bevan L. Cheeseman
    • , Ulrik Günther
    •  & Ivo F. Sbalzarini

  • Article
    | Open Access

    It is now possible to predict what a chemical smells like based on its chemical structure, however to date, this has only been done for a small number of odor descriptors. Here, using natural-language semantic representations, the authors demonstrate prediction of a much wider range of descriptors.

    • E. Darío Gutiérrez
    • , Amit Dhurandhar
    •  & Guillermo A. Cecchi

  • Article
    | Open Access

    It is often advantageous to transform a strongly nonlinear system into a linear one in order to simplify its analysis for prediction and control. Here the authors combine dynamical systems with deep learning to identify these hard-to-find transformations.

    • Bethany Lusch
    • , J. Nathan Kutz
    •  & Steven L. Brunton

  • Article
    | Open Access

    Continuous-time computation paradigm could represent a viable alternative to the standard digital one when dealing with certain classes of problems. Here, the authors propose a generalised version of a continuous-time solver and simulate its performances in solving MaxSAT and two-colour Ramsey problems.

    • Botond Molnár
    • , Ferenc Molnár
    •  & Mária Ercsey-Ravasz

  • Article
    | Open Access

    HIV infected cells persist for decades in patients under ART, but the mechanisms responsible remain unclear. Here, Reeves et al. use modeling approaches adapted from ecology to show that cellular proliferation, rather than viral replication, generates a majority of infected cells during ART.

    • Daniel B. Reeves
    • , Elizabeth R. Duke
    •  & Joshua T. Schiffer

  • Article
    | Open Access

    Accurate and actionable biomarkers that integrate diverse molecular, functional and clinical information hold great promise in precision medicine. Here, the authors develop SIMMS, a method for pathway-based cross-disease biomarker discovery.

    • Syed Haider
    • , Cindy Q. Yao
    •  & Paul C. Boutros

  • Article
    | Open Access

    Complex networks can be a useful tool to investigate problems in social science. Here the authors use game theory to establish a network model and then use a machine learning approach to characterize the role of nodes within a social network.

    • Yuan Yuan
    • , Ahmad Alabdulkareem
    •  & Alex ‘Sandy’ Pentland

  • Article
    | Open Access

    Nanoparticle applications are limited by insufficient understanding of physiochemical properties on in vivo disposition. Here, the authors explore the influence of size, surface chemistry and administration on the biodisposition of mesoporous silica nanoparticles using image-based pharmacokinetics.

    • Prashant Dogra
    • , Natalie L. Adolphi
    •  & C. Jeffrey Brinker

  • Article
    | Open Access

    Solid-state nuclear magnetic resonance combined with quantum chemical shift predictions is limited by high computational cost. Here, the authors use machine learning based on local atomic environments to predict experimental chemical shifts in molecular solids with accuracy similar to density functional theory.

    • Federico M. Paruzzo
    • , Albert Hofstetter
    •  & Lyndon Emsley

  • Article
    | Open Access

    AI is used increasingly in medical diagnostics. Here, the authors present a deep learning model that masters medical knowledge, demonstrated by it having passed the written test of the 2017 National Medical Licensing Examination in China, and can provide help with clinical diagnosis based on electronic health care records.

    • Ji Wu
    • , Xien Liu
    •  & Ping Lv

  • Article
    | Open Access

    Dynamics in cold atomic ensembles involve complex many-body interactions that are hard to treat analytically. Here, the authors use machine learning to optimise the cooling and trapping of neutral atoms, showing an improvement in the resulting resonant optical depth compared to more traditional solutions.

    • A. D. Tranter
    • , H. J. Slatyer
    •  & G. T. Campbell

  • Article
    | Open Access

    Self-folding origami have applications for mechanical metamaterials but one of their pitfalls is that many undesirable folding modes exist. Here the authors propose an algorithm to determine which folding joints to make stiffer in order to ensure that the sheet is folded into the chosen state.

    • Menachem Stern
    • , Viraaj Jayaram
    •  & Arvind Murugan

  • Article
    | Open Access

    Progressive diseases tend to be heterogeneous in their underlying aetiology mechanism, disease manifestation, and disease time course. Here, Young and colleagues devise a computational method to account for both phenotypic heterogeneity and temporal heterogeneity, and demonstrate it using two neurodegenerative disease cohorts.

    • Alexandra L Young
    • , Razvan V Marinescu
    •  & Ansgar J Furst

  • Article
    | Open Access

    With the rapid development of quantum computers, quantum machine learning approaches are emerging as powerful tools to perform electronic structure calculations. Here, the authors develop a quantum machine learning algorithm, which demonstrates significant improvements in solving quantum many-body problems.

    • Rongxin Xia
    •  & Sabre Kais

  • Article
    | Open Access

    Materials databases currently neglect the temperature effect on compound thermodynamics. Here the authors introduce a Gibbs energy descriptor enabling the high-throughput prediction of temperature-dependent thermodynamics across a wide range of compositions and temperatures for inorganic solids.

    • Christopher J. Bartel
    • , Samantha L. Millican
    •  & Aaron M. Holder

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