Data mining articles within Nature Communications

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  • Article
    | Open Access

    How reproducible evolutionary processes are remains an important question in evolutionary biology. Here, the authors compile a compendium of more than 15,000 mutation events for Escherichia coli under 178 distinct environmental settings, and develop an ensemble of predictors to predict evolution at a gene level.

    • Xiaokang Wang
    • , Violeta Zorraquino
    •  & Ilias Tagkopoulos

  • Article
    | Open Access

    Technical noise in experiments is unavoidable, but it introduces inaccuracies into the biological networks we infer from the data. Here, the authors introduce a diffusion-based method for denoising undirected, weighted networks, and show that it improves the performances of downstream analyses.

    • Bo Wang
    • , Armin Pourshafeie
    •  & Jure Leskovec

  • Article
    | Open Access

    Community detection allows one to decompose a network into its building blocks. While communities can be identified with a variety of methods, their relative importance can’t be easily derived. Here the authors introduce an algorithm to identify modules which are most promising for further analysis.

    • Marinka Zitnik
    • , Rok Sosič
    •  & Jure Leskovec

  • Article
    | Open Access

    While breast cancer incidence in the Asia Pacific region is rising, the molecular basis remains poorly characterized. Here the authors perform genomic screening of 187 Korean breast cancer patients and find differences in molecular subtype distribution, mutation pattern and prevalence, and gene expression signature when compared to TCGA.

    • Zhengyan Kan
    • , Ying Ding
    •  & Yeon Hee Park

  • Article
    | Open Access

    Modules composed of groups of genes with similar expression profiles tend to be functionally related and co-regulated. Here, Saelens et al evaluate the performance of 42 computational methods and provide practical guidelines for module detection in gene expression data.

    • Wouter Saelens
    • , Robrecht Cannoodt
    •  & Yvan Saeys

  • Article
    | Open Access

    RNA levels in post-mortem tissue can differ greatly from those before death. Studying the effect of post-mortem interval on the transcriptome in 36 human tissues, Ferreira et al. find that the response to death is largely tissue-specific and develop a model to predict time since death based on RNA data.

    • Pedro G. Ferreira
    • , Manuel Muñoz-Aguirre
    •  & Roderic Guigó

  • Article
    | Open Access

    Resting cortical activity fluctuates, but it is unclear what underlies these variations in activity. Here, the authors show that large-scale fluctuations in fMRI cortical activity are associated with momentary decreases in cortical arousal and opposite activity changes in the basal forebrain and thalamus.

    • Xiao Liu
    • , Jacco A. de Zwart
    •  & Jeff H. Duyn

  • Article
    | Open Access

    Facioscapulohumeral muscular dystrophy is a myopathy linked to ectopic expression of the DUX4 transcription factor. The authors show that the suppression of targets genes of the myogenesis regulator PAX7 is a signature of FSHD, and might explain oxidative stress sensitivity and epigenetic changes.

    • Christopher R. S. Banerji
    • , Maryna Panamarova
    •  & Peter S. Zammit

  • Article
    | Open Access

    The authors use an integrative clustering approach to identify two laryngeal cancer clusters with distinct prognosis and show that mutations damaging the NSD1 and NSD2 methyltransferases segregate to the cluster with favorable prognosis, and independently predict longer survival in patients with laryngeal, but not other head and neck cancers.

    • Suraj Peri
    • , Evgeny Izumchenko
    •  & Erica A. Golemis

  • Article
    | Open Access

    Tumorigenesis is a complex process driven by numerous risk factors. Here, genomic analysis of liver cancer reveals the evolution of mutational signatures during tumor development, highlighting mutational and structural signatures linked to environmental exposures and endogenous cellular processes.

    • Eric Letouzé
    • , Jayendra Shinde
    •  & Jessica Zucman-Rossi

  • Article
    | Open Access

    As the experimental discovery of microRNAs (miRNAs) is cumbersome, computational tools have been developed for the prediction of pre-miRNAs. Here the authors develop a framework to assess the performance of existing and novel pre-miRNA prediction tools and provide guidelines for selecting an appropriate approach for a given data set.

    • Müşerref Duygu Saçar Demirci
    • , Jan Baumbach
    •  & Jens Allmer

  • Article
    | Open Access

    In single-cell RNA sequencing data of heterogeneous cell populations, cell cycle stage of individual cells would often be informative. Here, the authors introduce a computational model to reconstruct a pseudo-time series from single cell transcriptome data, identify the cell cycle stages, identify candidate cell cycle-regulated genes and recover the methylome changes during the cell cycle.

    • Zehua Liu
    • , Huazhe Lou
    •  & Ting Chen

  • Article
    | Open Access

    There are no robust methods for systematically identifying mutation-specific synthetic lethal (SL) partners in cancer. Here, the authors develop a computational algorithm that uses pan-cancer data to detect mutation-andcancer-specific SL partners and they validate a novel SL interaction between mutant IDH and loss of ACACA in leukaemia.

    • Subarna Sinha
    • , Daniel Thomas
    •  & David L. Dill

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