Computational models articles within Nature Communications

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  • Article
    | Open Access

    Genome-scale models of microbial metabolism largely ignore reaction kinetics. Here, the authors develop a general mathematical framework for modeling cellular growth with explicit non-linear reaction kinetics and use it to glean insights into the principles of cellular resource allocation and growth.

    • Hugo Dourado
    •  & Martin J. Lercher

  • Article
    | Open Access

    Metabolic engineering is often hampered by non-linear kinetics and allosteric regulatory mechanisms. Here, the authors construct a quantitative model for the pentose degradation Weimberg pathway in Caulobacter crescentus and demonstrate its biotechnological applications in cell-free system and standard metabolic engineering.

    • Lu Shen
    • , Martha Kohlhaas
    •  & Bettina Siebers

  • Article
    | Open Access

    Quantifying somatic evolutionary processes in cancer and healthy tissue is a challenge. Here, the authors use single time point multi-region sampling of cancer and normal tissue, combined with evolutionary theory, to quantify in vivo mutation and cell survival rates per cell division.

    • Benjamin Werner
    • , Jack Case
    •  & Andrea Sottoriva

  • Article
    | Open Access

    Cell-surface proteins serve as phenotypic cell markers and in many cases are more indicative of cellular function than the transcriptome. Here, the authors introduce a transfer learning framework to impute surface protein abundances from scRNA-seq data.

    • Zilu Zhou
    • , Chengzhong Ye
    •  & Nancy R. Zhang

  • Article
    | Open Access

    Accounting for the effects of genetic expression in genome-scale metabolic models is challenging. Here, the authors introduce a model formulation that efficiently simulates thermodynamic-compliant fluxes, enzyme and mRNA concentration levels, allowing omics integration and broad analysis of in silico cellular physiology.

    • Pierre Salvy
    •  & Vassily Hatzimanikatis

  • Article
    | Open Access

    Low sample numbers often limit the robustness of analyses in biomedical research. Here, the authors introduce a method to generate realistic scRNA-seq data using GANs that learn gene expression dependencies from complex samples, and show that augmenting spare cell populations improves downstream analyses.

    • Mohamed Marouf
    • , Pierre Machart
    •  & Stefan Bonn

  • Article
    | Open Access

    Existing computational approaches to predict long-range regulatory interactions do not fully exploit high-resolution Hi-C datasets. Here the authors present a Random Forests regression-based approach to predict high-resolution Hi-C counts using one-dimensional regulatory genomic signals.

    • Shilu Zhang
    • , Deborah Chasman
    •  & Sushmita Roy

  • Article
    | Open Access

    Disease heritability and genetic correlations between traits depend on genetics, the environment and their interaction. Here, Jia et al. compute disease prevalence curves and disease embeddings from electronic health records and impute heritability for hundreds of diseases and genetic correlations for thousands of disease pairs.

    • Gengjie Jia
    • , Yu Li
    •  & Andrey Rzhetsky

  • Article
    | Open Access

    Haplotype information inferred by phasing is useful in genetic and genomic analysis. Here, the authors develop SHAPEIT4, a phasing method that exhibits sub-linear running time, provides accurate haplotypes and enables integration of external phasing information.

    • Olivier Delaneau
    • , Jean-François Zagury
    •  & Emmanouil T. Dermitzakis

  • Article
    | Open Access

    Whole genome sequencing (WGS) holds promise to solve a subset of Mendelian disease cases for which exome sequencing did not provide a genetic diagnosis. Here, Wells et al. report a supervised machine learning model trained on functional, mutational and structural features for rank-scoring and interpreting variants in non-coding regions from WGS.

    • Alex Wells
    • , David Heckerman
    •  & Julia di Iulio

  • Article
    | Open Access

    Allele-specific expression at single-cell resolution can reveal stochastic and dynamic features of gene expression in greater detail. The authors propose scBASE, a soft zero-and-one inflated model that improves estimation of cellular allelic proportions by pooling information across cells.

    • Kwangbom Choi
    • , Narayanan Raghupathy
    •  & Gary A. Churchill

  • Article
    | Open Access

    Flexizymes have been used to expand the scope of chemical substrates for ribosome-directed polymerization in vitro. Here the authors deduce design rules of Flexizyme-mediated tRNA acylation that more effectively predict the incorporation of new monomers into peptides.

    • Joongoo Lee
    • , Kenneth E. Schwieter
    •  & Michael C. Jewett

  • Article
    | Open Access

    During meiotic prophase chromosomes organise into a series of chromatin loops, but the mechanisms of assembly remain unclear. Here the authors use Saccharomyces cerevisiae to elucidate how this elaborate three-dimensional chromosome organisation is linked to genomic sequence, and demonstrate an essential role for cohesin during this process.

    • Stephanie A. Schalbetter
    • , Geoffrey Fudenberg
    •  & Matthew J. Neale

  • Article
    | Open Access

    Cellular systems have numerous mechanisms to control gene expression. Here the authors build a Tet-On system with conditional destablising elements to regulate gene expression and protein stability, allowing fine modulation of mESC signalling pathways.

    • Elisa Pedone
    • , Lorena Postiglione
    •  & Lucia Marucci

  • Article
    | Open Access

    Cardiomyocytes obtained from human induced pluripotent stem cells are increasingly used for drug testing, but they are not always predictive of the heart contractile responses. Here the authors develop a method to measure cytosolic calcium, action potentials and contraction simultaneously, to achieve higher sensitivity for drug screenings.

    • Berend J. van Meer
    • , Ana Krotenberg
    •  & Christine L. Mummery

  • Article
    | Open Access

    Non-additive genetic interactions are plastic and can complicate genetic prediction. Here, using deep mutagenesis of the lambda repressor, Li et al. reveal that changes in gene expression can alter the strength and direction of genetic interactions between mutations in many genes and develop mathematical models for predicting them.

    • Xianghua Li
    • , Jasna Lalić
    •  & Ben Lehner

  • Article
    | Open Access

    Gene activation requires an increase of successful initiation events. Here, by employing a genome-wide kinetic analysis of transcription, the authors showed that gene activation generally requires a decrease in RNA Polymerase II (Pol II) promoter-proximal pausing while transcription of enhancer elements is not limited by Pol II pausing.

    • Saskia Gressel
    • , Björn Schwalb
    •  & Patrick Cramer

  • Article
    | Open Access

    Compared to bulk data, cell-type-specific DNA methylation data provide higher resolution of epigenetic variation. Here, the authors introduce Tensor Composition Analysis, a novel computational approach for learning cell-type-specific DNA methylation from tissue-level bulk data, and show its application in epigenome-wide association studies.

    • Elior Rahmani
    • , Regev Schweiger
    •  & Eran Halperin

  • Article
    | Open Access

    Polymorphisms in the avian influenza A virus (IAV) polymerase restrict its host range during transmission from birds to mammals. Here, the authors investigate differences in the host chromatin regulator ANP32A regarding IAV polymerase adaptation, and profile ANP32A splicing to predict avian species associated with pre-adaptive human-signatures in the virus.

    • Patricia Domingues
    • , Davide Eletto
    •  & Benjamin G. Hale

  • Article
    | Open Access

    The fraction of protein-protein interactions (PPIs) that can be disrupted without fitness effect is unknown. Here, the authors model how disease-causing mutations and common mutations carried by healthy people perturb the interactome, and estimate that <20% of human PPIs are completely dispensable.

    • Mohamed Ghadie
    •  & Yu Xia

  • Article
    | Open Access

    Sequencing of newly synthesised RNA can reveal the transcriptional dynamics in a population of cells. Here the authors develop NASC-seq to bring this sensitivity and temporal resolution to single-cell analysis.

    • Gert-Jan Hendriks
    • , Lisa A. Jung
    •  & Rickard Sandberg

  • Comment
    | Open Access

    Infectious disease modeling has played a prominent role in recent outbreaks, yet integrating these analyses into public health decision-making has been challenging. We recommend establishing ‘outbreak science’ as an inter-disciplinary field to improve applied epidemic modeling.

    • Caitlin Rivers
    • , Jean-Paul Chretien
    •  & Simon Pollett

  • Article
    | Open Access

    The role of gene expression noise in the evolution of drug resistance in mammalian cells is unclear. Here, by uncoupling noise from mean expression of a drug resistance gene in CHO cells the authors show that noisy expression aids adaptation to high drug levels, but delays it at low drug levels.

    • Kevin S. Farquhar
    • , Daniel A. Charlebois
    •  & Gábor Balázsi

  • Article
    | Open Access

    Simulated single cell RNA sequencing data is useful for method development and comparison. Here, the authors developed SymSim, a simulator that explicitly models the main factors of variation in single cell data.

    • Xiuwei Zhang
    • , Chenling Xu
    •  & Nir Yosef

  • Article
    | Open Access

    Synergistic interactions may arise between regulators in complex molecular networks. Here, the authors develop OptiCon, a computational method for de novo identification of synergistic key regulators and investigate their potential roles as candidate targets for combination therapy.

    • Yuxuan Hu
    • , Chia-hui Chen
    •  & Kai Tan

  • Article
    | Open Access

    Here, using an integrative experimental and computational approach, Imle et al. show how cell motility and density affect HIV cell-associated transmission in a three-dimensional tissue-like culture system of CD4+ T cells and collagen, and how different collagen matrices restrict infection by cell-free virions.

    • Andrea Imle
    • , Peter Kumberger
    •  & Oliver T. Fackler

  • Article
    | Open Access

    Methodological advances have increased our understanding of chromatin structure through chromosome conformation capture techniques and high resolution imaging, but integration of these datasets is challenging. Here the authors propose GEM-FISH, a method for reconstructing the 3D models of chromosomes through systematically integrating both Hi-C and FISH data with the prior biophysical knowledge of a polymer model.

    • Ahmed Abbas
    • , Xuan He
    •  & Jianyang Zeng

  • Article
    | Open Access

    The drivers of coexistence between species with different growth rates are of interest in both ecology and applied microbial science. The authors show, via modelling, that species interactions moderated by consumption or degradation of chemicals can allow coexistence.

    • Lori Niehaus
    • , Ian Boland
    •  & Babak Momeni

  • Article
    | Open Access

    Phenotypically identical mammalian cells often display considerable variability in transcript levels of individual genes. Here the authors document how different genes propagate their expression levels in cell lineages and suggest a potential role of transcriptional memory for generating spatial patterns of gene expression.

    • Nicholas E. Phillips
    • , Aleksandra Mandic
    •  & David M. Suter

  • Article
    | Open Access

    In 2014 Guangzhou, China experienced its worse dengue epidemic on record. To determine the reasons for this the authors model historical data under combinations of four time-varying factors and find that past epidemics were limited by one or more unfavourable conditions, but the 2014 epidemic faced none of these restraints.

    • Rachel J. Oidtman
    • , Shengjie Lai
    •  & Hongjie Yu

  • Article
    | Open Access

    Model selection is a time-intensive step of molecular phylogenetic analysis. Here, Abadi, Azouri and colleagues show that all model selection criteria lead to similar inferences, and that for topology and ancestral sequence reconstruction, using the GTR+I+G model is as accurate.

    • Shiran Abadi
    • , Dana Azouri
    •  & Itay Mayrose

  • Article
    | Open Access

    Forecasting of infectious disease outbreaks can inform appropriate intervention measures, but whether fundamental limits to accurate prediction exist is unclear. Here, the authors use permutation entropy as a model independent measure of predictability to study limitations across a broad set of infectious diseases.

    • Samuel V. Scarpino
    •  & Giovanni Petri

  • Article
    | Open Access

    Integration of omics data remains a challenge. Here, the authors introduce iCell, a framework to integrate tissue-specific protein–protein interaction, co-expression and genetic interaction data, enabling identification of the most rewired genes in cancer, unidentifiable in individual data layers.

    • Noël Malod-Dognin
    • , Julia Petschnigg
    •  & Nataša Pržulj

  • Article
    | Open Access

    Seasonal malaria chemoprevention provides substantial benefit for young children, but resistance to used drugs will likely develop. Here, Chotsiri et al. evaluate the use of dihydroartemisinin-piperaquine as a regimen in 179 children, and population-based simulations suggest that small children would benefit from a higher and extended dosage.

    • Palang Chotsiri
    • , Issaka Zongo
    •  & Joel Tarning

  • Article
    | Open Access

    Single-cell RNA sequencing is a powerful method to study gene expression, but noise in the data can obstruct analysis. Here the authors develop a denoising method based on a deep count autoencoder network that scales linearly with the number of cells, and therefore is compatible with large data sets.

    • Gökcen Eraslan
    • , Lukas M. Simon
    •  & Fabian J. Theis

  • Article
    | Open Access

    Many organs develop through branching morphogenesis, but whether the underlying mechanisms are shared is unknown. Here, the authors show that a ligand-receptor based Turing mechanisms, similar to that observed in lung development, likely underlies branching morphogenesis of the kidney.

    • Denis Menshykau
    • , Odyssé Michos
    •  & Dagmar Iber

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