For undulatory swimming, fish form posteriorly traveling waves of body bending by activating their muscles sequentially along the body. However, experimental observations have shown that the muscle activation wave does not simply match the bending wave. Ming et al. use 3D computational fluid dynamics models to explain the muscle activation patterns by computing and analyzing the internal torque and power required for eel-like and mackerel-like swimming. They provide a mechanical picture in which the body shape, body movement, muscles, tendons, and body elasticity of a mackerel (or similar) orchestrate to make swimming efficient.
Image Credit: Bowen Jin, Beijing Computational Science Research Center (CSRC)
Editorial
Ten simple rules to create biological network figures for communication
PLOS Computational Biology: published September 26, 2019 | https://doi.org/10.1371/journal.pcbi.1007244
Education
Ten simple rules for helping newcomers become contributors to open projects
PLOS Computational Biology: published September 12, 2019 | https://doi.org/10.1371/journal.pcbi.1007296
Perspectives
Perspective: Dimensions of the scientific method
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Bioinformatics in Jordan: Status, challenges, and future directions
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Research Articles
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The FACTS model of speech motor control: Fusing state estimation and task-based control
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Benchmarking network propagation methods for disease gene identification
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Deconvolving multiplexed protease signatures with substrate reduction and activity clustering
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Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data
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Executable pathway analysis using ensemble discrete-state modeling for large-scale data
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Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction
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3D computational models explain muscle activation patterns and energetic functions of internal structures in fish swimming
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MHC binding affects the dynamics of different T-cell receptors in different ways
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Prepaid parameter estimation without likelihoods
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From Escherichia coli mutant 13C labeling data to a core kinetic model: A kinetic model parameterization pipeline
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Corrections
Correction: Minimal model of interictal and ictal discharges “Epileptor-2”
PLOS Computational Biology: published September 12, 2019 | https://doi.org/10.1371/journal.pcbi.1007359
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