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PLoS Computational Biology

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https://read.qxmd.com/read/30779745/a-saturated-reaction-in-repressor-synthesis-creates-a-daytime-dead-zone-in-circadian-clocks
#1
Koichiro Uriu, Hajime Tei
Negative feedback loops (NFLs) for circadian clocks include light-responsive reactions that allow the clocks to shift their phase depending on the timing of light signals. Phase response curves (PRCs) for light signals in various organisms include a time interval called a dead zone where light signals cause no phase shift during daytime. Although the importance of the dead zone for robust light entrainment is known, how the dead zone arises from the biochemical reactions in an NFL underlying circadian gene expression rhythms remains unclear...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30779739/a-component-overlapping-attribute-clustering-coac-algorithm-for-single-cell-rna-sequencing-data-analysis-and-potential-pathobiological-implications
#2
He Peng, Xiangxiang Zeng, Yadi Zhou, Defu Zhang, Ruth Nussinov, Feixiong Cheng
Recent advances in next-generation sequencing and computational technologies have enabled routine analysis of large-scale single-cell ribonucleic acid sequencing (scRNA-seq) data. However, scRNA-seq technologies have suffered from several technical challenges, including low mean expression levels in most genes and higher frequencies of missing data than bulk population sequencing technologies. Identifying functional gene sets and their regulatory networks that link specific cell types to human diseases and therapeutics from scRNA-seq profiles are daunting tasks...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30779737/graph-peak-caller-calling-chip-seq-peaks-on-graph-based-reference-genomes
#3
Ivar Grytten, Knut D Rand, Alexander J Nederbragt, Geir O Storvik, Ingrid K Glad, Geir K Sandve
Graph-based representations are considered to be the future for reference genomes, as they allow integrated representation of the steadily increasing data on individual variation. Currently available tools allow de novo assembly of graph-based reference genomes, alignment of new read sets to the graph representation as well as certain analyses like variant calling and haplotyping. We here present a first method for calling ChIP-Seq peaks on read data aligned to a graph-based reference genome. The method is a graph generalization of the peak caller MACS2, and is implemented in an open source tool, Graph Peak Caller...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30779735/allosteric-mechanism-of-the-circadian-protein-vivid-resolved-through-markov-state-model-and-machine-learning-analysis
#4
Hongyu Zhou, Zheng Dong, Gennady Verkhivker, Brian D Zoltowski, Peng Tao
The fungal circadian clock photoreceptor Vivid (VVD) contains a photosensitive allosteric light, oxygen, voltage (LOV) domain that undergoes a large N-terminal conformational change. The mechanism by which a blue-light driven covalent bond formation leads to a global conformational change remains unclear, which hinders the further development of VVD as an optogenetic tool. We answered this question through a novel computational platform integrating Markov state models, machine learning methods, and newly developed community analysis algorithms...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30779734/multi-modality-in-gene-regulatory-networks-with-slow-promoter-kinetics
#5
Muhammad Ali Al-Radhawi, Domitilla Del Vecchio, Eduardo D Sontag
Phenotypical variability in the absence of genetic variation often reflects complex energetic landscapes associated with underlying gene regulatory networks (GRNs). In this view, different phenotypes are associated with alternative states of complex nonlinear systems: stable attractors in deterministic models or modes of stationary distributions in stochastic descriptions. We provide theoretical and practical characterizations of these landscapes, specifically focusing on stochastic Slow Promoter Kinetics (SPK), a time scale relevant when transcription factor binding and unbinding are affected by epigenetic processes like DNA methylation and chromatin remodeling...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30779733/multiscale-modeling-of-influenza-a-virus-replication-in-cell-cultures-predicts-infection-dynamics-for-highly-different-infection-conditions
#6
Daniel Rüdiger, Sascha Young Kupke, Tanja Laske, Pawel Zmora, Udo Reichl
Influenza A viruses (IAV) are commonly used to infect animal cell cultures for research purposes and vaccine production. Their replication is influenced strongly by the multiplicity of infection (MOI), which ranges over several orders of magnitude depending on the respective application. So far, mathematical models of IAV replication have paid little attention to the impact of the MOI on infection dynamics and virus yields. To address this issue, we extended an existing model of IAV replication in adherent MDCK cells with kinetics that explicitly consider the time point of cell infection...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30779730/a-numerical-approach-for-a-discrete-markov-model-for-progressing-drug-resistance-of-cancer
#7
Masayuki Maeda, Hideaki Yamashita
The presence of treatment-resistant cells is an important factor that limits the efficacy of cancer therapy, and the prospect of resistance is considered the major cause of the treatment strategy. Several recent studies have employed mathematical models to elucidate the dynamics of generating resistant cancer cells and attempted to predict the probability of emerging resistant cells. The purpose of this paper is to present numerical approach to compute the number of resistant cells and the emerging probability of resistance...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30779729/identifying-individual-risk-rare-variants-using-protein-structure-guided-local-tests-point
#8
Rachel Marceau West, Wenbin Lu, Daniel M Rotroff, Melaine A Kuenemann, Sheng-Mao Chang, Michael C Wu, Michael J Wagner, John B Buse, Alison A Motsinger-Reif, Denis Fourches, Jung-Ying Tzeng
Rare variants are of increasing interest to genetic association studies because of their etiological contributions to human complex diseases. Due to the rarity of the mutant events, rare variants are routinely analyzed on an aggregate level. While aggregation analyses improve the detection of global-level signal, they are not able to pinpoint causal variants within a variant set. To perform inference on a localized level, additional information, e.g., biological annotation, is often needed to boost the information content of a rare variant...
February 19, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30768597/verbalizing-phylogenomic-conflict-representation-of-node-congruence-across-competing-reconstructions-of-the-neoavian-explosion
#9
Nico M Franz, Lukas J Musher, Joseph W Brown, Shizhuo Yu, Bertram Ludäscher
Phylogenomic research is accelerating the publication of landmark studies that aim to resolve deep divergences of major organismal groups. Meanwhile, systems for identifying and integrating the products of phylogenomic inference-such as newly supported clade concepts-have not kept pace. However, the ability to verbalize node concept congruence and conflict across multiple, in effect simultaneously endorsed phylogenomic hypotheses, is a prerequisite for building synthetic data environments for biological systematics and other domains impacted by these conflicting inferences...
February 15, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30768590/efficient-neural-decoding-of-self-location-with-a-deep-recurrent-network
#10
Ardi Tampuu, Tambet Matiisen, H Freyja Ólafsdóttir, Caswell Barry, Raul Vicente
Place cells in the mammalian hippocampus signal self-location with sparse spatially stable firing fields. Based on observation of place cell activity it is possible to accurately decode an animal's location. The precision of this decoding sets a lower bound for the amount of information that the hippocampal population conveys about the location of the animal. In this work we use a novel recurrent neural network (RNN) decoder to infer the location of freely moving rats from single unit hippocampal recordings...
February 15, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30763315/iris-eda-an-integrated-rna-seq-interpretation-system-for-gene-expression-data-analysis
#11
Brandon Monier, Adam McDermaid, Cankun Wang, Jing Zhao, Allison Miller, Anne Fennell, Qin Ma
Next-Generation Sequencing has made available substantial amounts of large-scale Omics data, providing unprecedented opportunities to understand complex biological systems. Specifically, the value of RNA-Sequencing (RNA-Seq) data has been confirmed in inferring how gene regulatory systems will respond under various conditions (bulk data) or cell types (single-cell data). RNA-Seq can generate genome-scale gene expression profiles that can be further analyzed using correlation analysis, co-expression analysis, clustering, differential gene expression (DGE), among many other studies...
February 14, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30763309/identifying-the-mechanism-for-superdiffusivity-in-mouse-fibroblast-motility
#12
Giuseppe Passucci, Megan E Brasch, James H Henderson, Vasily Zaburdaev, M Lisa Manning
We seek to characterize the motility of mouse fibroblasts on 2D substrates. Utilizing automated tracking techniques, we find that cell trajectories are super-diffusive, where displacements scale faster than t1/2 in all directions. Two mechanisms have been proposed to explain such statistics in other cell types: run and tumble behavior with Lévy-distributed run times, and ensembles of cells with heterogeneous speed and rotational noise. We develop an automated toolkit that directly compares cell trajectories to the predictions of each model and demonstrate that ensemble-averaged quantities such as the mean-squared displacements and velocity autocorrelation functions are equally well-fit by either model...
February 14, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30759077/improving-the-reliability-of-model-based-decision-making-estimates-in-the-two-stage-decision-task-with-reaction-times-and-drift-diffusion-modeling
#13
Nitzan Shahar, Tobias U Hauser, Michael Moutoussis, Rani Moran, Mehdi Keramati, Raymond J Dolan
A well-established notion in cognitive neuroscience proposes that multiple brain systems contribute to choice behaviour. These include: (1) a model-free system that uses values cached from the outcome history of alternative actions, and (2) a model-based system that considers action outcomes and the transition structure of the environment. The widespread use of this distinction, across a range of applications, renders it important to index their distinct influences with high reliability. Here we consider the two-stage task, widely considered as a gold standard measure for the contribution of model-based and model-free systems to human choice...
February 13, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30753182/maps-of-variability-in-cell-lineage-trees
#14
Damien G Hicks, Terence P Speed, Mohammed Yassin, Sarah M Russell
New approaches to lineage tracking have allowed the study of differentiation in multicellular organisms over many generations of cells. Understanding the phenotypic variability observed in these lineage trees requires new statistical methods. Whereas an invariant cell lineage, such as that for the nematode Caenorhabditis elegans, can be described by a lineage map, defined as the pattern of phenotypes overlaid onto the binary tree, a traditional lineage map is static and does not describe the variability inherent in the cell lineages of higher organisms...
February 12, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30742612/cell-geometry-determines-symmetric-and-asymmetric-division-plane-selection-in-arabidopsis-early-embryos
#15
Moukhtar Julien, Alain Trubuil, Katia Belcram, David Legland, Zhor Khadir, Aurélie Urbain, Jean-Christophe Palauqui, Philippe Andrey
Plant tissue architecture and organ morphogenesis rely on the proper orientation of cell divisions. Previous attempts to predict division planes from cell geometry in plants mostly focused on 2D symmetric divisions. Using the stereotyped division patterns of Arabidopsis thaliana early embryogenesis, we investigated geometrical principles underlying plane selection in symmetric and in asymmetric divisions within complex 3D cell shapes. Introducing a 3D computational model of cell division, we show that area minimization constrained on passing through the cell centroid predicts observed divisions...
February 11, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30742610/how-good-are-pathogenicity-predictors-in-detecting-benign-variants
#16
Abhishek Niroula, Mauno Vihinen
Computational tools are widely used for interpreting variants detected in sequencing projects. The choice of these tools is critical for reliable variant impact interpretation for precision medicine and should be based on systematic performance assessment. The performance of the methods varies widely in different performance assessments, for example due to the contents and sizes of test datasets. To address this issue, we obtained 63,160 common amino acid substitutions (allele frequency ≥1% and <25%) from the Exome Aggregation Consortium (ExAC) database, which contains variants from 60,706 genomes or exomes...
February 11, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30742609/a-hierarchical-sparse-coding-model-predicts-acoustic-feature-encoding-in-both-auditory-midbrain-and-cortex
#17
Qingtian Zhang, Xiaolin Hu, Bo Hong, Bo Zhang
The auditory pathway consists of multiple stages, from the cochlear nucleus to the auditory cortex. Neurons acting at different stages have different functions and exhibit different response properties. It is unclear whether these stages share a common encoding mechanism. We trained an unsupervised deep learning model consisting of alternating sparse coding and max pooling layers on cochleogram-filtered human speech. Evaluation of the response properties revealed that computing units in lower layers exhibited spectro-temporal receptive fields (STRFs) similar to those of inferior colliculus neurons measured in physiological experiments, including properties such as sound onset and termination, checkerboard pattern, and spectral motion...
February 11, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30742608/assessing-the-performance-of-real-time-epidemic-forecasts-a-case-study-of-ebola-in-the-western-area-region-of-sierra-leone-2014-15
#18
Sebastian Funk, Anton Camacho, Adam J Kucharski, Rachel Lowe, Rosalind M Eggo, W John Edmunds
Real-time forecasts based on mathematical models can inform critical decision-making during infectious disease outbreaks. Yet, epidemic forecasts are rarely evaluated during or after the event, and there is little guidance on the best metrics for assessment. Here, we propose an evaluation approach that disentangles different components of forecasting ability using metrics that separately assess the calibration, sharpness and bias of forecasts. This makes it possible to assess not just how close a forecast was to reality but also how well uncertainty has been quantified...
February 11, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30742607/network-guided-prediction-of-aromatase-inhibitor-response-in-breast-cancer
#19
Matthew Ruffalo, Roby Thomas, Jian Chen, Adrian V Lee, Steffi Oesterreich, Ziv Bar-Joseph
Prediction of response to specific cancer treatments is complicated by significant heterogeneity between tumors in terms of mutational profiles, gene expression, and clinical measures. Here we focus on the response of Estrogen Receptor (ER)+ post-menopausal breast cancer tumors to aromatase inhibitors (AI). We use a network smoothing algorithm to learn novel features that integrate several types of high throughput data and new cell line experiments. These features greatly improve the ability to predict response to AI when compared to prior methods...
February 11, 2019: PLoS Computational Biology
https://read.qxmd.com/read/30742605/correlation-structure-in-micro-ecog-recordings-is-described-by-spatially-coherent-components
#20
Nicholas Rogers, John Hermiz, Mehran Ganji, Erik Kaestner, Kıvılcım Kılıç, Lorraine Hossain, Martin Thunemann, Daniel R Cleary, Bob S Carter, David Barba, Anna Devor, Eric Halgren, Shadi A Dayeh, Vikash Gilja
Electrocorticography (ECoG) is becoming more prevalent due to improvements in fabrication and recording technology as well as its ease of implantation compared to intracortical electrophysiology, larger cortical coverage, and potential advantages for use in long term chronic implantation. Given the flexibility in the design of ECoG grids, which is only increasing, it remains an open question what geometry of the electrodes is optimal for an application. Conductive polymer, PEDOT:PSS, coated microelectrodes have an advantage that they can be made very small without losing low impedance...
February 11, 2019: PLoS Computational Biology
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