Bioinformatics

Syntactic and semantic conventions 1. Taxa are models, concepts are mimics. We typically refrain from using the terms “taxon”, “taxa”, or “clade(s)”. We take taxa to constitute evolutionary, causally sustained entities whose members are manifested in the natural realm. The task for systematics is to successively approximate the identities and limits of these entities. Thus,
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Abstract 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
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The analysis of single-cell RNA sequencing (scRNAseq) data plays an important role in understanding the intrinsic and extrinsic cellular processes in biological and biomedical research. One significant effort in this area is the detection of differentially expressed (DE) genes. scRNAseq data, however, are highly heterogeneous and have a large number of zero counts, which introduces
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Like going from a pinhole camera to a Polaroid, a significant mathematical update to the formula for a popular bioinformatics data visualization method will allow researchers to develop snapshots of single-cell gene expression not only several times faster but also at much higher-resolution. Published in Nature Methods, this innovation by Yale mathematicians will reduce the
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Preparing HMEC-1 cells for fluorescence imaging HMEC-1 cells were fixed using 1.7% (w/v) paraformaldehyde (Electron Microscopy Sciences) at room temperature and permeabilized by incubation with 0.02% (w/v) saponin in phosphate-buffered saline (PBS) for 10 min at room temperature. Cells were then preblocked with 3% bovine serum albumin (BSA) in PBS, incubated with anti-Clathrin primary antibody (mouse
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Three-dimensional structure of Mtb-SecBTA in complex with ChAD In contrast with the classical export chaperone SecB, which binds and wraps unfolded presecretory protein substrates and maintains them in an unfolded conformation compatible with translocation through membrane6, previous work revealed that the Mtb-SecBTA chaperone of TAC is capable of binding to its aggregation-prone Mtb-HigA1 antitoxin substrate
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Our methodological pipeline (Fig. 2) is comprised of several steps: (1) numerically represent the genomic contigs using a nucleotide mapping (Table 1). (2) MLBP is used to extract features from these numerical representations. If available, cross-sample coverage information (mean and standard deviation) is extracted separately using Bowtie 233 and can be considered as extra information to be
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Chemicals Paracetamol and paracetamol-D4 internal standard were purchased from Sigma (Sigma-Aldrich Chemie B.V., Zwijndrecht, The Netherlands). UPLC/MS grade MeOH was purchased from Biosolve (Biosolve B.V., Valkenswaard, The Netherlands). Purified water (H2O) was retrieved from PURELAB (Veolia Water Technologies B.V., Ede, The Netherlands). Zebrafish husbandry All experiments were planned and executed in compliance with European regulation6.
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Conversion of 8-mer architecture into 24-mer nanocage As a standard structural component among protein nanocages, ferritin exists ubiquitously in both prokaryotes and eukaryotes. It is a nearly spherical 24-subunits protein with an exterior diameter of about 12 nm and a hollow cavity of 8 nm30,31. Owing to its cage-like morphology and highly symmetrical structure, ferritin has been
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1. Niforou K, Cheimonidou C, Trougakos IP. Molecular chaperones and proteostasis regulation during redox imbalance. Redox Biol. 2014;2:323–32. 2. Powers ET, Balch WE. Diversity in the origins of proteostasis networks–a driver for protein function in evolution. Nat Rev Mol Cell Biol. 2013;14:237–48. 3. Bayer TA. Proteinopathies, a core concept for understanding and ultimately treating degenerative
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The advent of massively parallel sequencing (MPS) technologies in the past decade has revolutionized the field of genomics, enabling fast and cost-effective generation of a large amount of sequence data. This technological innovation leads to the accumulation of vast quantities of genomic data, posing a tremendous challenge to scientists for effective mining of data to
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Identifying and counting individual cells from cell cultures form the basis of numerous biological and biomedical research applications [1, 2]. Determining numbers of cells reflecting the growth, survival, and death of cell populations form the foundations of e.g. basic cancer research and early drug development. Currently, the most commonly used methods for counting cells in
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The analytical approach presented above was implemented using R-shiny. The typical analysis is performed by three interaction steps: i) input of gene lists and modifications, ii) graphical visualization of enriched terms and iii) interactive navigation of the results. A step-by-step user manual is available in Additional file 1. In the first step, the application provides a
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The analytical approach presented above was implemented using R-shiny. The typical analysis is performed by three interaction steps: i) input of gene lists and modifications, ii) graphical visualization of enriched terms and iii) interactive navigation of the results. A step-by-step user manual is available in Additional file 1. In the first step, the application provides a
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1. Hoglinger, GU, G Respondek and GG Kovacs. New classification of tauopathies. Rev Neurol (Paris) 2018. https://doi.org/10.1016/j.neurol.2018.07.001. 2. Lebouvier T, Pasquier F, Buee L. Update on tauopathies. Curr Opin Neurol. 2017;30:589–98. 3. Morris M, Maeda S, Vossel K, Mucke L. The many faces of tau. Neuron. 2011;70:410–26. 4. Höglinger GU, Melhem NM, Dickson DW, et
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Abstract The dynamic nature of technological developments invites us to rethink the learning spaces. In this context, science education can be enriched by the contribution of new computational resources, making the educational process more up-to-date, challenging, and attractive. Bioinformatics is a key interdisciplinary field, contributing to the understanding of biological processes that is often underrated
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Abstract The dynamic nature of technological developments invites us to rethink the learning spaces. In this context, science education can be enriched by the contribution of new computational resources, making the educational process more up-to-date, challenging, and attractive. Bioinformatics is a key interdisciplinary field, contributing to the understanding of biological processes that is often underrated
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Abstract 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
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Abstract 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
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Abstract 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
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Like going from a pinhole camera to a Polaroid, a significant mathematical update to the formula for a popular bioinformatics data visualization method will allow researchers to develop snapshots of single-cell gene expression not only several times faster but also at much higher-resolution. Published in Nature Methods, this innovation by Yale mathematicians will reduce the rendering
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Posted by: RNA-Seq Blog in Information 21 hours ago 173 Views Sometimes, analyzing our DNA sequences isn’t quite enough. RNA-seq is a next-generation sequencing (NGS)-based technique that looks at the RNA transcripts produced from our DNA, allowing us to look into how our genes are expressed. RNA-seq has shown its worth across many fields, and
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Dissecting the model to predict how landmark learning is achieved Using this model, we can dissect different elements of learning, analyse what information is learnt, and how effective is this information. Initially, we examined whether our model could simulate experimental spatial learning. Rats were simulated in a water maze using 4 trials/day for 10 days.
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This study involved a deep computational investigation of the MOG-antibody complex in aqueous solution. For a significant nanoscale description, available data on MOG structure and its specific antibody6,21 were taken into account together with considerations from the experimental-theoretical interface background of our research group. This study presented the following highlights: (1) Fab portion fluctuation of
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In the past decade, next generation sequencing (NGS) technology has made great progress and personal genome sequencing has also been widely used in human disease research, clinical treatment and new drug research [1]. In the genome analysis process, variant calling is significant step to discover and obtain variants relative to reference genome, which is also
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In the past decade, next generation sequencing (NGS) technology has made great progress and personal genome sequencing has also been widely used in human disease research, clinical treatment and new drug research [1]. In the genome analysis process, variant calling is significant step to discover and obtain variants relative to reference genome, which is also
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Genetic sequence database searching is a foundational tool in bioinformatics commonly used to make new discoveries, guide annotation, and direct downstream analysis, among many other tasks. Therefore, the performance of database searching tools is crucial to high quality results in many biomedical applications. Benchmarking such tools provides a systematic comparison to aid developers and researchers
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Genetic sequence database searching is a foundational tool in bioinformatics commonly used to make new discoveries, guide annotation, and direct downstream analysis, among many other tasks. Therefore, the performance of database searching tools is crucial to high quality results in many biomedical applications. Benchmarking such tools provides a systematic comparison to aid developers and researchers
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Abstract 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,
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Abstract 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,
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Abstract An important goal of systems medicine is to study disease in the context of genetic and environmental perturbations to the human interactome network. For diseases with both genetic and infectious contributors, a key postulate is that similar perturbations of the human interactome by either disease mutations or pathogens can have similar disease consequences. This
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Abstract An important goal of systems medicine is to study disease in the context of genetic and environmental perturbations to the human interactome network. For diseases with both genetic and infectious contributors, a key postulate is that similar perturbations of the human interactome by either disease mutations or pathogens can have similar disease consequences. This
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Ethics statement All experiments using mice were performed in accordance with the Animal Experimentation Ethics Committee of the Peter MacCallum Cancer Centre (Approval E427) and mice were sacrificed by anaesthetic overdose. Lineage data Data from 3 types of lineages are analyzed in this paper. Experimental data from T cells provide an example of a lineage
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Ethics statement All experiments using mice were performed in accordance with the Animal Experimentation Ethics Committee of the Peter MacCallum Cancer Centre (Approval E427) and mice were sacrificed by anaesthetic overdose. Lineage data Data from 3 types of lineages are analyzed in this paper. Experimental data from T cells provide an example of a lineage
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A team of scientists led by researchers at the University of Georgia Center for Food Safety in Griffin has developed a machine-learning approach that could lead to quicker identification of the animal source of certain Salmonella outbreaks. In the research, published in the January 2019 issue of Emerging Infectious Diseases, Xiangyu Deng and his colleagues
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Citation: Zhang Q, Hu X, Hong B, Zhang B (2019) A hierarchical sparse coding model predicts acoustic feature encoding in both auditory midbrain and cortex. PLoS Comput Biol 15(2): e1006766. https://doi.org/10.1371/journal.pcbi.1006766 Editor: Frédéric E. Theunissen, University of California at Berkeley, UNITED STATES Received: April 29, 2018; Accepted: December 21, 2018; Published: February 11, 2019 Copyright:
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Citation: Zhang Q, Hu X, Hong B, Zhang B (2019) A hierarchical sparse coding model predicts acoustic feature encoding in both auditory midbrain and cortex. PLoS Comput Biol 15(2): e1006766. https://doi.org/10.1371/journal.pcbi.1006766 Editor: Frédéric E. Theunissen, University of California at Berkeley, UNITED STATES Received: April 29, 2018; Accepted: December 21, 2018; Published: February 11, 2019 Copyright:
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Abstract 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
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Abstract 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
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Abstract 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
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Abstract 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
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