Browse our latest Computational and Systems Biology articles

Page 66 of 125
    1. Computational and Systems Biology
    2. Microbiology and Infectious Disease

    Microbial genetic and transcriptional contributions to oxalate degradation by the gut microbiota in health and disease

    Menghan Liu, Joseph C Devlin ... Lama Nazzal
    A novel multi-omics framework revealed the taxonomic contribution to microbiota oxalate, demontrated O. formigenes as the dominating taxon transcriptionally, and identified specific IBD cohort at risk for oxalte toxicity.
    1. Chromosomes and Gene Expression
    2. Computational and Systems Biology

    Tissue-specific modulation of gene expression in response to lowered insulin signalling in Drosophila

    Luke Stephen Tain, Robert Sehlke ... Linda Partridge
    Multi-omic profiling of gene expression in response to reduced insulin/IGF-like-signalling reveals tissue-specific regulation of DNA damage and lysosomal mannosidase regulation of tissue homeostasis as pro-longevity responses.
    1. Computational and Systems Biology
    2. Neuroscience

    Visuomotor learning from postdictive motor error

    Jana Masselink, Markus Lappe
    Visual, motor, and forward model gains learn from a postdictive update of space to keep perception and saccadic motor function aligned.
    1. Computational and Systems Biology
    2. Ecology

    Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments

    Sylvie Estrela, Alicia Sanchez-Gorostiaga ... Alvaro Sanchez
    There are regularities in how specific nutrients combine together to shape the taxonomic composition of self-assembled communities, with some types of nutrients dominating other types.
    1. Computational and Systems Biology

    Mouse aging cell atlas analysis reveals global and cell type-specific aging signatures

    Martin Jinye Zhang, Angela Oliveira Pisco ... James Zou
    Comprehensive single-cell transcriptome analysis reveals global and tissue-specific aging markers and characterizes the heterogeneous aging status of different cell types and tissues in mouse.
    1. Computational and Systems Biology
    2. Neuroscience

    Action detection using a neural network elucidates the genetics of mouse grooming behavior

    Brian Q Geuther, Asaf Peer ... Vivek Kumar
    A machine learning method for action detection is developed and applied toward mouse grooming behavior.
    1. Computational and Systems Biology
    2. Neuroscience

    Graphical-model framework for automated annotation of cell identities in dense cellular images

    Shivesh Chaudhary, Sol Ah Lee ... Hang Lu
    Unbiased and automatic annotation using structured prediction framework with efficiently built data-driven atlases is more accurate than registration-based methods for cell identifications in dense images and enables fast whole-brain analysis.
    1. Cell Biology
    2. Computational and Systems Biology

    CEM500K, a large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning

    Ryan Conrad, Kedar Narayan
    'Cellular Electron Microscopy 500,000 images' (CEM500K) is a highly heterogeneous, information-rich, non-redundant, unlabeled EM dataset curated to pre-train DL algorithms for better model generalization on EM segmentation tasks.
    1. Computational and Systems Biology
    2. Neuroscience

    Uncovering the computational mechanisms underlying many-alternative choice

    Armin W Thomas, Felix Molter, Ian Krajbich
    A comparison of different computational models reveals that looking behavior, during value-based choices from 9, 16, 25, or 36 snack foods, actively influences the subjective values of the available alternatives.
    1. Computational and Systems Biology
    2. Medicine

    Identification of human glucocorticoid response markers using integrated multi-omic analysis from a randomized crossover trial

    Dimitrios Chantzichristos, Per-Arne Svensson ... Gudmundur Johannsson
    A human experimental model for physiological glucocorticoid exposure and glucocorticoid withdrawal identifies a multi-omic cluster, including microRNA miR-122-5p and metabolites, associated with glucocorticoid-responsive genes.