Fungi produce complex networks of filamentous structures that allow them to colonize different environments. The filamentous nature makes quantitative analyses of fungal growth dynamics and morphology challenging. Vidal-Diez de Ulzurrun et al. have developed a new method for capturing images of live fungi and a tool, Fungal Feature Tracker, to extract different morphological features from fungal images. FFT can quantitatively characterize fungal morphology, cell number and measure filamentous growth allowing objective and precise characterization of phenotypes which will advance our understanding of fungal growth and biology.
Image Credit: Guillermo Vidal-Diez de Ulzurrun, Institute of Molecular Biology, Academia Sinica, Taiwan
Editorials
Ten simple rules for providing optimal administrative support to research teams
PLOS Computational Biology: published October 3, 2019 | https://doi.org/10.1371/journal.pcbi.1007292
Ten simple rules to aid in achieving a vision
PLOS Computational Biology: published October 17, 2019 | https://doi.org/10.1371/journal.pcbi.1007395
Education
Ten quick tips for delivering programming lessons
PLOS Computational Biology: published October 31, 2019 | https://doi.org/10.1371/journal.pcbi.1007433
Perspective
Patient Dossier: Healthcare queries over distributed resources
PLOS Computational Biology: published October 17, 2019 | https://doi.org/10.1371/journal.pcbi.1007291
Research Articles
Estimating influenza incidence using search query deceptiveness and generalized ridge regression
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A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data
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Competition-driven evolution of organismal complexity
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Constrained inference in sparse coding reproduces contextual effects and predicts laminar neural dynamics
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A simulation of the random and directed motion of dendritic cells in chemokine fields
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Large-scale, dynamin-like motions of the human guanylate binding protein 1 revealed by multi-resolution simulations
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Predicting gait adaptations due to ankle plantarflexor muscle weakness and contracture using physics-based musculoskeletal simulations
PLOS Computational Biology: published October 7, 2019 | https://doi.org/10.1371/journal.pcbi.1006993
Dimensional reduction in networks of non-Markovian spiking neurons: Equivalence of synaptic filtering and heterogeneous propagation delays
PLOS Computational Biology: published October 8, 2019 | https://doi.org/10.1371/journal.pcbi.1007404
miRWoods: Enhanced precursor detection and stacked random forests for the sensitive detection of microRNAs
PLOS Computational Biology: published October 9, 2019 | https://doi.org/10.1371/journal.pcbi.1007309
A computational account of threat-related attentional bias
PLOS Computational Biology: published October 10, 2019 | https://doi.org/10.1371/journal.pcbi.1007341
Consensus and uncertainty in the geographic range of Aedes aegypti and Aedes albopictus in the contiguous United States: Multi-model assessment and synthesis
PLOS Computational Biology: published October 10, 2019 | https://doi.org/10.1371/journal.pcbi.1007369
Evaluation of linear and non-linear activation dynamics models for insect muscle
PLOS Computational Biology: published October 14, 2019 | https://doi.org/10.1371/journal.pcbi.1007437
Categorical encoding of decision variables in orbitofrontal cortex
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Combinations of low-level and high-level neural processes account for distinct patterns of context-dependent choice
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Phylogenetic correlations can suffice to infer protein partners from sequences
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Key residues in TLR4-MD2 tetramer formation identified by free energy simulations
PLOS Computational Biology: published October 14, 2019 | https://doi.org/10.1371/journal.pcbi.1007228
Transitions in information processing dynamics at the whole-brain network level are driven by alterations in neural gain
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TAPES: A tool for assessment and prioritisation in exome studies
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A Kuramoto model of self-other integration across interpersonal synchronization strategies
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Computational design and interpretation of single-RNA translation experiments
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Detecting distant-homology protein structures by aligning deep neural-network based contact maps
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Surfactant delivery in rat lungs: Comparing 3D geometrical simulation model with experimental instillation
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Action potential propagation and synchronisation in myelinated axons
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Color improves edge classification in human vision
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Spectral tuning of adaptation supports coding of sensory context in auditory cortex
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Sequence specificity despite intrinsic disorder: How a disease-associated Val/Met polymorphism rearranges tertiary interactions in a long disordered protein
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A multi-scale coevolutionary approach to predict interactions between protein domains
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LASSI: A lattice model for simulating phase transitions of multivalent proteins
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Hypergraph-based connectivity measures for signaling pathway topologies
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SourceSet: A graphical model approach to identify primary genes in perturbed biological pathways
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From space to time: Spatial inhomogeneities lead to the emergence of spatiotemporal sequences in spiking neuronal networks
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Matrigel patterning reflects multicellular contractility
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Uncovering and characterizing splice variants associated with survival in lung cancer patients
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Matrix feedback enables diverse higher-order patterning of the extracellular matrix
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Prediction of off-target specificity and cell-specific fitness of CRISPR-Cas System using attention boosted deep learning and network-based gene feature
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Seasonal influenza: Modelling approaches to capture immunity propagation
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Model-driven discovery of calcium-related protein-phosphatase inhibition in plant guard cell signaling
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EAGLE: An algorithm that utilizes a small number of genomic features to predict tissue/cell type-specific enhancer-gene interactions
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Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals
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Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach
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Fungal feature tracker (FFT): A tool for quantitatively characterizing the morphology and growth of filamentous fungi
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Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers
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Bayesian inference of neuronal assemblies
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