Computational models articles within Nature Communications

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  • Article
    | Open Access

    Better understanding of a trade-off between the speed and accuracy of decision-making is relevant for mapping biological intelligence to machines. The authors introduce a brain-inspired learning algorithm to uncover dependencies in individual fMRI networks with features of neural activity and predict inter-individual differences in decision-making.

    • Michael Schirner
    • , Gustavo Deco
    •  & Petra Ritter

  • Article
    | Open Access

    Malaria elimination is defined by WHO as the absence of recent indigenous cases in an area. In this study, the authors develop a metapopulation model that identifies indigenous cases and use it to investigate the likelihood of malaria elimination in Zanzibar under different intervention scenarios.

    • Aatreyee M. Das
    • , Manuel W. Hetzel
    •  & Nakul Chitnis

  • Article
    | Open Access

    One of the main challenges hampering the development of kinetic models is the lack of kinetic parameters for many enzymatic reactions. Here, the authors introduce a framework to explore the catalytically optimal operating conditions of any complex enzyme mechanism from an evolutionary perspective.

    • Asli Sahin
    • , Daniel R. Weilandt
    •  & Vassily Hatzimanikatis

  • Article
    | Open Access

    Combining molecular dynamic simulations with in vivo functional assays, Gagelin et al. identified unique molecular features of the mitochondrial carrier uncoupling protein 1 that are crucial to its inhibition by nucleotides

    • Antoine Gagelin
    • , Corentin Largeau
    •  & Bruno Miroux

  • Article
    | Open Access

    Genetic modules are sensitive to changes in their context and to environmental perturbations. Here, the authors develop a genetic optimizer based on common synthetic biology parts to ensure optimal and robust cellular performance in diverse contexts.

    • Andras Gyorgy
    • , Amor Menezes
    •  & Murat Arcak

  • Article
    | Open Access

    Methods to reanalyze scRNA-seq data in a spatial perspective are vital but lacking. Here, the authors develop scSpace, an integrative method that uses ST data as spatial reference to reconstruct the pseudo-space of scRNA-seq data and identify spatially variable cell subpopulations, providing insights into spatial heterogeneity from scRNA-seq data.

    • Jingyang Qian
    • , Jie Liao
    •  & Xiaohui Fan

  • Article
    | Open Access

    The authors demonstrate efficient and direct correction of the DNA mutation causing Haemoglobin E β-thalassaemia with CRISPR Cas9 base editors. The work includes profiling of off-target effects using deep neural networks.

    • Mohsin Badat
    • , Ayesha Ejaz
    •  & James O. J. Davies

  • Article
    | Open Access

    SARS-CoV-2 seroprevalence surveys aim to estimate the proportion of the population that has been infected, but their accuracy depends on the characteristics of the test assay used. Here, the authors use statistical models to assess the impact of the use of different assays on estimates of seroprevalence in the United States.

    • Bernardo García-Carreras
    • , Matt D. T. Hitchings
    •  & Derek A. T. Cummings

  • Article
    | Open Access

    SARS-CoV-2 testing rates have varied during the pandemic but the drivers of changes in testing behaviour are unclear. Here, the authors link national testing data from England to indicators of epidemic trends to describe how testing varies according to level of virus transmission, disease susceptibility/severity, public health measures, and risk perception.

    • Younjung Kim
    • , Christl A. Donnelly
    •  & Pierre Nouvellet

  • Article
    | Open Access

    During somitogenesis, the dynamic oscillation of the molecular clock is converted into static spatial patterns. Here, the authors show that persistent suppression of Tbx6 expression triggered by periodical Ripply1/2 gene expression is a key to this conversion.

    • Taijiro Yabe
    • , Koichiro Uriu
    •  & Shinji Takada

  • Article
    | Open Access

    Here the authors report SBCG2 an update to the neural network based, Shape-Based Coarse Graining (SBCG) approach for creating coarse grained molecular topologies with atomistic detail. They show how SBCG2 can reduce the computational costs of simulating very large assemblies like the HIV-1 capsid allowing simulation on commodity hardware.

    • Alexander J. Bryer
    • , Juan S. Rey
    •  & Juan R. Perilla

  • Article
    | Open Access

    Oncogenic gene fusions are frequent in childhood cancers but remain poorly understood and untargeted. Here, the authors identify 272 oncogenic fusions in transcriptomics data from 5190 childhood cancer patients, revealing their possible etiologies, their links with tumor progression and evolution, and their potential as therapeutic targets.

    • Yanling Liu
    • , Jonathon Klein
    •  & Xiaotu Ma

  • Article
    | Open Access

    Accurately annotating cell types is a fundamental step in single-cell omics data analysis. Here, the authors develop a computational method called Cellcano based on a two-round supervised learning algorithm to identify cell types for scATAC-seq data and perform benchmarking to demonstrate its accuracy, robustness and computational efficiency.

    • Wenjing Ma
    • , Jiaying Lu
    •  & Hao Wu

  • Article
    | Open Access

    Disentangling how evolutionary history and environmental adaptation shape metabolic phenotypes is an open problem, especially for microbes whose phenotypes cannot be determined directly and are inferred from genomic information. Here, Ramon & Stelling propose sensitivity correlations to quantify similarity of predicted metabolic network responses to perturbations, and link genotype and environment to phenotype for 245 bacterial species.

    • Charlotte Ramon
    •  & Jörg Stelling

  • Article
    | Open Access

    High hyperdiploid acute lymphoblastic leukaemia (HeH ALL) is driven by nonrandom chromosomal gains, which have been suggested to arise early - even before birth. Here, the authors use single-cell whole genome sequencing and in silico modelling to show that HeH ALL aneuploidies could originate early and follow punctuated evolution.

    • Eleanor L. Woodward
    • , Minjun Yang
    •  & Kajsa Paulsson

  • Article
    | Open Access

    Accurately estimating the burden of tuberculosis is challenging due to incomplete registration systems and the relationship with HIV. Here, the authors develop a Bayesian modelling strategy accounting for these factors that estimates age- and country-specific annual risks of infection and the proportion resulting from recent infection.

    • Peter J. Dodd
    • , Debebe Shaweno
    •  & Helen Ayles

  • Article
    | Open Access

    In this study, the authors perform a meta-analysis of COVID-19 vaccine effectiveness studies and compare observed protection against severe disease with model-based estimates of neutralising antibody titres. Their results show that SARS-CoV-2 antibody titres are predictive of protection against severe COVID-19 disease.

    • Deborah Cromer
    • , Megan Steain
    •  & Miles P. Davenport

  • Article
    | Open Access

    It is challenging to approach protein structures in living cells. Here the authors investigate Interleukin-4 receptor alpha, which has a noncanonical amino acid incorporated at different locations, and see that evaluating click efficiency with calibrated imaging gives information on structure-related properties.

    • Frederik Steiert
    • , Peter Schultz
    •  & Thomas Weidemann

  • Article
    | Open Access

    The construction of protein-constrained genome-scale metabolic models depends on the integration of organism-specific enzyme turnover numbers. Here, the authors show that correction of turnover numbers by simultaneous consideration of proteomics and physiological data leads to improved predictions of condition-specific growth rates.

    • Philipp Wendering
    • , Marius Arend
    •  & Zoran Nikoloski

  • Article
    | Open Access

    Antimicrobial peptides emerge as compounds that can alleviate the global health hazard of antimicrobial resistance. Here, the authors propose HydrAMP, an extended conditional variational autoencoder. HydrAMP generated antimicrobial peptides with high activity against bacteria, including multidrug-resistant species.

    • Paulina Szymczak
    • , Marcin Możejko
    •  & Ewa Szczurek

  • Article
    | Open Access

    There is interest in measuring the influence of spatial cellular organization on pathophysiology, which is being accomplished through spatial transcriptomics. There the authors present UniCell Deconvolve, a pre-trained deep learning model that predicts cell identity and deconvolves cell type fractions using a 28 M cell database.

    • Daniel Charytonowicz
    • , Rachel Brody
    •  & Robert Sebra

  • Article
    | Open Access

    Advances in spatial transcriptomics technologies have enabled the gene expression profiling of tissues while retaining spatial context. Here the authors present GraphST, a graph self-supervised contrastive learning method that learns informative and discriminative spot representations from spatial transcriptomics data.

    • Yahui Long
    • , Kok Siong Ang
    •  & Jinmiao Chen

  • Article
    | Open Access

    The NHS COVID-19 digital contact tracing app was designed to notify people of potential exposure to SARS-CoV-2. Here, the authors summarise the uptake and engagement with the app in its first year, and estimate its epidemiological impact in terms of numbers of cases, hospitalisations, and deaths averted.

    • Michelle Kendall
    • , Daphne Tsallis
    •  & Christophe Fraser

  • Article
    | Open Access

    Single-cell multi-omics and deep learning could lead to the inference of biological networks across specific cell types. Here, the authors develop DeepMAPS, a deep learning, graph-based approach for cell-type specific network inference from single-cell multi-omics data that is tested on healthy and tumour tissue datasets.

    • Anjun Ma
    • , Xiaoying Wang
    •  & Qin Ma

  • Article
    | Open Access

    Delineating the cellular composition of tumour boundaries in spatial transcriptomics (ST) data is challenging. Here, the authors develop Cottrazm to integrate ST with histological imaging and single-cell data, identify the malignant and non-malignant tissue boundaries, deconvolute cell-type composition, and reconstruct cell type-specific gene expression profiles.

    • Zhenzhen Xun
    • , Xinyu Ding
    •  & Youqiong Ye

  • Article
    | Open Access

    Vaccination against invasive pneumococcal disease is recommended for older adults but the optimal age group to target has not been determined and may vary by epidemiological setting. Here, the authors use statistical modelling to estimate the optimal ages for vaccination in Brazil, England, Malawi, and South Africa.

    • Deus Thindwa
    • , Samuel Clifford
    •  & Stefan Flasche

  • Article
    | Open Access

    Here the authors show that H2A.Z histone variant incorporation reduces the nucleosomal barrier for transcription. Furthermore their simulations reveal that H2A.Z facilitates spontaneous DNA unwrapping from the histone octamer and enhances nucleosome gaping.

    • Shuxiang Li
    • , Tiejun Wei
    •  & Anna R. Panchenko

  • Article
    | Open Access

    Existing genomic data analysis methods tend to not take full advantage of underlying biological characteristics. Here, the authors leverage the inherent interactions of scRNA-seq data and develop a cartography strategy to contrive the data into a spatially configured genomap for accurate deep pattern discovery.

    • Md Tauhidul Islam
    •  & Lei Xing

  • Article
    | Open Access

    Long lasting insecticide treated mosquito nets (LLINs) provide protection from malaria through both direct effects to the user and indirect community-level effects. Here, the authors use mathematical modelling to assess the relative contributions of these effects under different insecticide resistance and LLIN usage scenarios.

    • H. Juliette T. Unwin
    • , Ellie Sherrard-Smith
    •  & Azra C. Ghani

  • Article
    | Open Access

    Cell type deconvolution in tumor spatial transcriptomics (ST) data remains challenging. Here, the authors develop Spatial Cellular Estimator for Tumors (SpaCET) to infer cell types and intercellular interactions from ST data in cancer across different platforms, with improved performance over similar methods.

    • Beibei Ru
    • , Jinlin Huang
    •  & Peng Jiang

  • Article
    | Open Access

    A major challenge in analyzing scRNA-seq data arises from challenges related to dimensionality and the prevalence of dropout events. Here the authors develop a deep graph learning method called scMGCA based on a graph-embedding autoencoder that simultaneously learns cell-cell topology representation and cluster assignments, outperforming other state-of-the-art models across multiple platforms.

    • Zhuohan Yu
    • , Yanchi Su
    •  & Xiangtao Li

  • Article
    | Open Access

    Trial data have shown that post-discharge malaria chemoprevention (PDMC) reduces the risk of readmission and death in children previously hospitalised with severe malarial anaemia. Here, the authors use mathematical modelling to estimate the potential epidemiological impacts of PDMC in malaria-endemic countries in Africa.

    • Lucy C. Okell
    • , Titus K. Kwambai
    •  & Amani Thomas Mori

  • Article
    | Open Access

    Many methods for single cell data integration have been developed, though mosaic integration remains challenging. Here the authors present scMoMaT, a mosaic integration method for single cell multi-modality data from multiple batches, that jointly learns cell representations and marker features across modalities for different cell clusters, to interpret the cell clusters from different modalities.

    • Ziqi Zhang
    • , Haoran Sun
    •  & Xiuwei Zhang

  • Article
    | Open Access

    A key player in the formation of endoplasmic reticulum sheets is CLIMP-63, but mechanistic details remained elusive. Here authors combined cellular experiments and mathematical modelling to show that S-acylation of CLIMP-63 regulates its function by mediating its oligomerisation, turnover, and localisation.

    • Patrick A. Sandoz
    • , Robin A. Denhardt-Eriksson
    •  & F. Gisou van der Goot

  • Article
    | Open Access

    GPCRs are integral membrane proteins that serve as attractive drug targets. Here, authors delineate the conformational landscapes of 45 GPCRs using a statistical model, highlighting their malleable native ensembles and providing functional insights.

    • Sathvik Anantakrishnan
    •  & Athi N. Naganathan

  • Article
    | Open Access

    Single-cell multimodal sequencing technologies are developed to simultaneously profile different modalities of data in the same cell. Here the authors develops a multimodal deep clustering method for the analysis of single-cell multi-omics data that supports clustering different types of multi-omics data and multi-batch data, as well as downstream differential expression analysis.

    • Xiang Lin
    • , Tian Tian
    •  & Hakon Hakonarson

  • Article
    | Open Access

    Identifying the designers of engineered biological sequences would help promote biotechnological innovation while holding designers accountable. Here the authors present the winners of a 2020 data-science competition which improved on previous attempts to attribute plasmid sequences.

    • Oliver M. Crook
    • , Kelsey Lane Warmbrod
    •  & William J. Bradshaw

  • Article
    | Open Access

    Methods that analyse heterogeneity and compare tissue microenvironments using spatial omics data are challenging to develop. Here, the authors present SOTIP, a method that can perform spatial heterogeneity, spatial domain, and differential microenvironment analyses across multiple spatial omics modalities.

    • Zhiyuan Yuan
    • , Yisi Li
    •  & Michael Q. Zhang

  • Article
    | Open Access

    Modelling how endogenous mutations accumulate in tissues is valuable to understand how cancers develop and evolve. Here, the authors establish a mathematical model that can predict the number of endogenous somatic mutations in the lifetime of tissues and approximate the time to cancer development.

    • Sophie Pénisson
    • , Amaury Lambert
    •  & Cristian Tomasetti

  • Article
    | Open Access

    Division of labour, where members of a group specialise on different tasks, is a central feature of many social organisms. Using a theoretical model, the authors demonstrate that division of labour can emerge spontaneously within a group of entirely identical individuals.

    • Jan J. Kreider
    • , Thijs Janzen
    •  & Franz J. Weissing

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