Computational models articles within Nature Communications

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  • Article
    | Open Access

    Spatial transcriptomics analyses can be affected by noise and spatial correlation across tissue locations. Here, the authors develop SpatialPCA, a spatially-aware dimensionality reduction method that explicitly models spatial correlation structures, and show its application to the analysis of healthy and tumour tissues.

    • Lulu Shang
    •  & Xiang Zhou

  • Article
    | Open Access

    Recovering dropout-affected gene expression values is a challenging problem in bioinformatics. Here, the authors propose a data-driven framework, that first learns the underlying data distribution and then recovers the expression values by imposing a self-consistency on the expression matrix.

    • Md Tauhidul Islam
    • , Jen-Yeu Wang
    •  & Lei Xing

  • Article
    | Open Access

    Spatially resolved transcriptomics is a relatively new technique that maps transcriptional information within a tissue. Here the authors present MIST, which detects molecular regions from spatially resolved transcriptomics and denoises the missing gene expression values by region-specific imputation.

    • Linhua Wang
    • , Mirjana Maletic-Savatic
    •  & Zhandong Liu

  • Article
    | Open Access

    Seasonal influenza vaccination is an important strategy to prevent serious disease in the elderly, but individual responsiveness to vaccination widely vary. Here authors establish, with an array of state-of-the art methods, the major immunological parameters that distinguish vaccine recipients developing robust antibody response and non-responders

    • Peggy Riese
    • , Stephanie Trittel
    •  & Carlos A. Guzmán

  • Article
    | Open Access

    The organisation of mammalian genomes plays a role in many biological processes. Here the authors report dcHiC, a tool which uses a multivariate distance measure to identify changes in compartmentalisation among multiple genome-wide chromatin contact maps, and apply this to different human and mouse datasets.

    • Abhijit Chakraborty
    • , Jeffrey G. Wang
    •  & Ferhat Ay

  • Article
    | Open Access

    Traditional bulk sequencing data lack information about cell-type-specific gene expression. Here, the authors develop a Tissue-AdaPtive autoEncoder (TAPE), a deep learning method connecting bulk RNA-seq and single-cell RNA-seq, and apply it to analyze the cell type fractions and cell-type-specific gene expression in clinical data.

    • Yanshuo Chen
    • , Yixuan Wang
    •  & Yu Li

  • Article
    | Open Access

    Studies on parent-of-origin effects have been limited in terms of sample size due to lack of parental genomes or known genealogies. Here, the authors develop a method to infer the parent-of-origin of an individual alleles in biobank-scale datasets, without requiring parental genomes or prior knowledge of genealogy, allowing discovery of parent-of-origin effects with an unprecedented sample size.

    • Robin J. Hofmeister
    • , Simone Rubinacci
    •  & Olivier Delaneau

  • Article
    | Open Access

    RNA velocity can detect the differentiation directionality by modelling sparse unspliced RNAs, but suffers from high estimation errors. Here, the authors develop a computational method called UniTVelo to reinforce the velocity estimation by introducing a unified time and a top-down model design.

    • Mingze Gao
    • , Chen Qiao
    •  & Yuanhua Huang

  • Article
    | Open Access

    Previous efforts to study the circadian clock using scRNA-seq have relied on time course designs that treat cell collection time as a proxy for circadian time. Here, the authors introduce a statistical method to infer circadian timing directly from expression, enabling researchers to study circadian phase heterogeneity.

    • Benjamin J. Auerbach
    • , Garret A. FitzGerald
    •  & Mingyao Li

  • Article
    | Open Access

    Biomarkers of age and frailty may aid in understanding the aging process, predicting lifespan or health span and in assessing the effects of anti-aging interventions. Here, the authors show that combining physics-based models and deep learning may enhance understanding of aging from big biomedical data, observe effects of anti-aging interventions in laboratory animals, and discover signatures of longevity.

    • Konstantin Avchaciov
    • , Marina P. Antoch
    •  & Peter O. Fedichev

  • Article
    | Open Access

    Renal fibrosis is a progressive process with complex etiopathology, causing organ failure. Here authors present a mathematical model, based on an in vitro system faithfully contemplating macrophage-fibroblast interaction and the metabolic-immunologic signals that are affecting kidney fibrosis, that is applicable to kidney transplant failure.

    • Elisa Setten
    • , Alessandra Castagna
    •  & Massimo Locati

  • Article
    | Open Access

    Mendelian randomization uses genetic variation to study the causal effect of exposure on outcome, but results can be biased by confounders, such as horizontal pleiotropy. Here, the authors present MR-CUE, a method to determine causal effects by accounting for correlated and uncorrelated horizontal pleiotropic effects.

    • Qing Cheng
    • , Xiao Zhang
    •  & Jin Liu

  • Article
    | Open Access

    Current methods to reanalyze bulk RNA-seq at spatially resolved single-cell resolution have limitations. Here, the authors develop Bulk2Space, a spatial deconvolution algorithm using single-cell and spatial transcriptomics as references, providing new insights into spatial heterogeneity within bulk tissue.

    • Jie Liao
    • , Jingyang Qian
    •  & Xiaohui Fan

  • Article
    | Open Access

    Proteomics can be used to refine cancer classification. Here, the authors characterise chronic lymphocytic leukaemia patients by proteogenomics, and identified a subtype of patients with poor prognosis associated with aberrant B cell receptor signalling.

    • Sophie A. Herbst
    • , Mattias Vesterlund
    •  & Sascha Dietrich

  • Article
    | Open Access

    Transplanting encapsulated insulin-producing cells may achieve a functional cure for type 1 diabetes, but efficacy is constrained by mass transfer limits. Here, the authors report a dynamic computational platform to investigate the therapeutic potency of such programmable bioartificial pancreas devices.

    • Alexander U. Ernst
    • , Long-Hai Wang
    •  & Minglin Ma

  • Article
    | Open Access

    Multi-view graph approaches could enhance the analysis of tissue heterogeneity in spatial transcriptomics. Here, the authors develop the Spatial Transcriptomics data analysis by Multiple View Collaborative-learning - stMVC - framework, and apply it to detect spatial domains and cell states in brain and tumor tissues.

    • Chunman Zuo
    • , Yijian Zhang
    •  & Luonan Chen

  • Article
    | Open Access

    In this work the authors propose a multiscale computational approach, integrating atomistic and coarse-grained models simulations, to study the thermodynamic and kinetic factors playing a major role in the liquid-to-solid transition of biomolecular condensates. It is revealed how the gradual accumulation of inter-protein β-sheets increases the viscosity of functional liquid-like condensates, transforming them into gel-like pathological aggregates, and it is also shown how high concentrations of RNA can decelerate such transition.

    • Andres R. Tejedor
    • , Ignacio Sanchez-Burgos
    •  & Jorge R. Espinosa

  • Article
    | Open Access

    Predicting treatment response in cancer remains a highly complex task. Here, the authors develop Precily, a deep neural network framework to predict treatment response in cancer by considering gene expression, pathway activity estimates and drug features, and test this method in multiple datasets and preclinical models.

    • Smriti Chawla
    • , Anja Rockstroh
    •  & Debarka Sengupta

  • Article
    | Open Access

    SARS-CoV-2 genome sequencing data can be used to infer epidemiological parameters, but the impact of the strategy used to select samples on these estimates is rarely considered. Here, the authors produce estimates using different sampling strategies and compare results to those based on case reporting data.

    • Rhys P. D. Inward
    • , Kris V. Parag
    •  & Nuno R. Faria

  • Article
    | Open Access

    Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. Here the authors develop a computational model, SELMA, to estimate and correct enzymatic cleavage biases in chromatin accessibility profiling data.

    • Shengen Shawn Hu
    • , Lin Liu
    •  & Chongzhi Zang

  • Article
    | Open Access

    Single-cell gene expression data with positional information is critical to dissect mechanisms and architectures of multicellular organisms, but the potential is limited by the scalability of current data analysis strategies. Here the authors develop a highly scalable method, scGCO, to identify genes whose expression values form spatial patterns from spatial transcriptomics data.

    • Ke Zhang
    • , Wanwan Feng
    •  & Peng Wang

  • Article
    | Open Access

    Water is an essential part of any biological system, yet many aspects of its role remain elusive. Here the authors show, in a paradigmatic ligand-protein system, that water modulates the ligand residence time in a complex and non-local way, with possible implications in drug design.

    • Narjes Ansari
    • , Valerio Rizzi
    •  & Michele Parrinello

  • Article
    | Open Access

    Cytoskeletal activity generates mechanical forces known to agitate and displace membrane-bound organelles in the cytoplasm. In oocytes, Al Jord et al. discover that these cytoplasmic forces functionally remodel nuclear RNA-processing condensates across scales for developmental success.

    • Adel Al Jord
    • , Gaëlle Letort
    •  & Marie-Hélène Verlhac

  • Article
    | Open Access

    The ’Roadmap’ for relaxation of COVID-19 restrictions in England in 2021 was informed by mathematical modelling. Here, the authors perform a retrospective assessment of the accuracy of modelling predictions and identify the main sources of uncertainty that led to observed values deviating from projections.

    • Matt J. Keeling
    • , Louise Dyson
    •  & Samuel Moore

  • Article
    | Open Access

    Utilizing viral test results to determine isolation length would minimize both the risk of prematurely ending isolation of infectious patients and the unnecessary individual burden of redundant isolation of noninfectious patients. Here, the authors develop a framework to compute the population-level risk of different isolation guidelines with rapid antigen tests.

    • Yong Dam Jeong
    • , Keisuke Ejima
    •  & Marco Ajelli

  • Article
    | Open Access

    Women generally mount a stronger immune response to infections than men do, resulting in a higher impact of autoimmune diseases. Here, the authors show that pathogen transmission from mother-to-child during pregnancy drives the co-evolution of a stout defence against harmless pathogens in women.

    • Evan Mitchell
    • , Andrea L. Graham
    •  & Geoff Wild

  • Article
    | Open Access

    How intrinsic cell properties such as stiffness contribute to cell-cell junction stabilization is not well described. Here they show that higher levels of intrinsic cell mechanics at the cortex, cytoskeleton and nucleus of neighboring cells promote junctional maturation.

    • K. Sri-Ranjan
    • , J. L. Sanchez-Alonso
    •  & Vania M. M. Braga

  • Article
    | Open Access

    Hematopoietic stem cells produce diverse cell lineages. Here, the authors apply single-cell RNA-seq, computational integration of non-perturbative approaches for fate-mapping, and mitotic tracking to chart lineage decisions in native hematopoiesis and identify megakaryocyte progenitors that directly link HSCs to megakaryocytes.

    • Mina N. F. Morcos
    • , Congxin Li
    •  & Alexander Gerbaulet

  • Article
    | Open Access

    Soil microbial carbon is central to soil functions and services, but its spatial-temporal dynamics are unclear. Here the authors show global trends in soil microbial carbon, which suggests a global decrease in soil microbial carbon, mostly driven by temperature increases in northern areas.

    • Guillaume Patoine
    • , Nico Eisenhauer
    •  & Carlos A. Guerra

  • Article
    | Open Access

    The authors provide a litmus test for the recognition mechanism of transiently binding proteins based on nuclear magnetic resonance and find a conformational selection binding mechanism through concentration-dependent kinetics of ubiquitin and SH3.

    • Kalyan S. Chakrabarti
    • , Simon Olsson
    •  & Christian Griesinger

  • Article
    | Open Access

    Genome-scale metabolic models have been widely used for quantitative exploration of the relation between genotype and phenotype. Here the authors present GECKO 2, an automated framework for continuous and version controlled update of enzyme-constrained models of metabolism, producing an interesting catalogue of high-quality models for diverse yeasts, bacteria and human metabolism, aiming to facilitate their use in basic science, metabolic engineering and synthetic biology purposes.

    • Iván Domenzain
    • , Benjamín Sánchez
    •  & Jens Nielsen

  • Article
    | Open Access

    Morphology of metabolosomes affects the encapsulated pathway performance. Here, the authors combine experimental characterizations with structural and kinetic modeling to reveal how the shell protein PduN changes the morphology of 1,2-propanediol utilization (Pdu) metabolosome and how this morphology shift impacts Pdu function.

    • Carolyn E. Mills
    • , Curt Waltmann
    •  & Danielle Tullman-Ercek

  • Article
    | Open Access

    Cellular contexts such as disease state, organismal life stage and tissue microenvironment, shape intercellular communication, and ultimately affect an organism’s phenotypes. Here, the authors present Tensor-cell2cell, an unsupervised method for deciphering context-driven intercellular communication.

    • Erick Armingol
    • , Hratch M. Baghdassarian
    •  & Nathan E. Lewis

  • Article
    | Open Access

    Here, the authors generated an artificial RNA molecule, or aptamer, specific for the Amyotrophic Lateral Sclerosis protein TDP-43. By interacting avidly with its target, the aptamer can be exploited to track TDP-43 phase transition in vitro and in cells.

    • Elsa Zacco
    • , Owen Kantelberg
    •  & Gian Gaetano Tartaglia

  • Article
    | Open Access

    The emergence of antibiotic resistance, even against last-line antibiotics such as colistin, is a serious public health threat. To guide treatment and drug development strategies, Marciano et al. apply evolutionary action (EA) analysis to identify driver mutations in a noisy mutational background in experimental evolution experiments and inform about de novo colistin resistance drivers.

    • David C. Marciano
    • , Chen Wang
    •  & Olivier Lichtarge

  • Article
    | Open Access

    Safely opening university campuses has been a major challenge during the COVID-19 pandemic. Here, the authors describe a program of public health measures employed at a university in the United States which, combined with other non-pharmaceutical interventions, allowed the university to stay open in fall 2020 with limited evidence of transmission.

    • Diana Rose E. Ranoa
    • , Robin L. Holland
    •  & Martin D. Burke

  • Article
    | Open Access

    Testing capacity continues to limit detection of COVID-19 infections and impacts reliability of mortality estimates. Here, the authors develop a statistical model to estimate COVID-19 attributable deaths using all-cause mortality data from Iran and estimate that around half of these deaths have been reported.

    • Mahan Ghafari
    • , Oliver J. Watson
    •  & Aris Katzourakis

  • Article
    | Open Access

    Computational approaches have been developed to estimate tumor microbial abundances from whole genomic and RNA-sequencing datasets. Here the authors report the predictive value of tumor microbial abundance, alone or in combination with gene expression data, for cancer prognosis and drug response.

    • Leandro C. Hermida
    • , E. Michael Gertz
    •  & Eytan Ruppin

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