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464 results for “model structure”
Structural model of PORCN .cif and .pdb files
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Structural models of <em>Cheiracanthium</em> <em>punctorium</em> spider toxins with putative defensive function (CSTX-type and phospholipase A2)
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Hybridization selects for prime-numbered life cycles in Magicicada: an individual-based simulation model of a structured periodical cicada population
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Model and data for: Economical defense of resources structures territorial space use in a cooperative carnivore
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Arthropod food webs in the foreland of a retreating Greenland glacier: Integrating molecular gut content analysis with Structural Equation Modelling
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Data from: Characterizing morphological (co)variation using structural equation models: body size, allometric relationships and evolvability in a house sparrow metapopulation
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Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data
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Data from: Improving structured population models with more realistic representations of non-normal growth
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Data from: Structural and functional features of medium spiny neurons in the BACHDΔN17 mouse model of Huntington’s disease
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Computationally modelled structure of type IV pilus PilA of Aggregatibacter actinomycetemcomitans
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Structural modeling of ion channels using AlphaFold2, RoseTTAFold2, and ESMFold
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Urban Forest Effects Model (UFORE) to calculate forest structure and function from sample ground data. Two part set.
Within the City of Baltimore, 195 permanent 1/10 circular plots were established based on a stratified random sample among land uses in 1999. These plots were re-measured in 2004 and 2009 and will be re-measured again in 2014. On each plot, all trees (as defined as woody vegetation with a stem diameter at 4.5 ft (dbh) greater than one-inch) are recorded. For each tree, data are recorded on species, dbh, height, crown width, condition, crown competition, percent canopy missing and distance and direction to nearby residential buildings. These data are analyzed using the i-Tree model (www.itreetools.org) to assess ecosystem services and values. However, more importantly, these plots along with a comparable set of plots established in Syracuse, NY in 1999 are the first and most spatially comprehensive set of long-term urban forest monitoring data within cities globally. These data are being used to understand how urban forest structure and associated ecosystem services are changing through time in the City of Baltimore.
Modelling Avian Habitat Suitability in Boreal Forest using Structural and Spectral Remote Sensing Data
<p>Data used in research regarding avian habitat suitability models in Harry's River Watershed in Newfoundland, Canada</p>
Supplementary material 1 from: Grace JB (2020) A 'Weight of Evidence' approach to evaluating structural equation models. One Ecosystem 5: e50452. https://doi.org/10.3897/oneeco.5.e50452
This text file contains the R code used to develop the demonstrations included in Grace JB (2020) A 'weight of evidence' approach to evaluating structural equation models. One Ecosystem
Statistical model training data for "Continuous Structural Parameterization: A proposed method for representing different model parameterizations within one structure demonstrated for atmospheric convection"
<p>Gzipped CSV files containing convection scheme inputs and outputs used for training.</p> <p>Column format of each file:</p> <p>THETA_IN_1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,Q_IN_1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,DTHETA_1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,DQ_1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28</p> <p>where THETA_IN are input values of potential temperature [K], Q_IN are input values of specific humidity [kg/kg], DTHETA are changes in potential temperature due to convection [K], DQ are changes in specific humidity due to convection [kg/kg].</p> <p>Key:</p> <p>"llcs" are simulations with Lambert-Lewis.</p> <p>"gr" are simulations with Gregory-Rowntree.</p> <p>"4xco2" have 4 x pre-industrial atmospheric carbon dioxide concentration. (Others have 1 x pre-industrial atmospheric carbon dioxide concentration.)</p> <p>"rh0.7" and "rh0.9" have LLCS RHCRIT set to 70% and 90% respectively.</p> <p>All are 30 day simulations either for January "jan" or July "jul".</p> <p> </p>
Dataset: A structural topic model approach to scientific reorientation of economics and chemistry after German reunification
<p>Dataset to: A structural topic model approach to scientific reorientation of economics and chemistry after German reunification</p> <p> </p> <p>Please see readme.txt for details</p>
Frog tongue segmentation data for a realistic vascular structure in modelling
<p>In the last decade, numerical models have been an increasingly important tool in biological and medical science both for the fundamental understanding of physiology as well as the potential for novel diagnostics and treatments tools in clinical application. In this paper, a nonlinear multi-scale model framework is developed for blood flow distribution in the full vascular system of an organ. We couple a quasi 1D vascular graph model to represent blood flow in larger vessels and a porous media model to describe flow in smaller vessels and capillary bed. The vascular model is based on Poiseuille's law, with pressure correction by elasticity and pressure drop estimation at vessels junctions. The porous capillary bed is modelled as a two-compartment domain (artery and venous) using Darcy's law. The fluid exchange between the artery and venous capillary bed compartments are defined as blood perfusion. </p> <p>The numerical experiments show that the proposed model for blood circulation: 1) is closely dependent on the structure and parameters of both the vascular vessels and of the capillary bed, and 2) it provides a realistic blood circulation in the organ. The advantage of the proposed model is that it is complex enough to reliably capture the main underlying physiological function, yet highly flexible as it offers the possibility of incorporating various local effects. Furthermore, the numerical implementation of the model is straightforward and allows for simulations on a regular desktop computer. </p>
Structure of transmembrane domain of mouse NBCe1 by homology modeling
<p>The structure model of the transmembrane domain of mouse NBCe1 was generated by SWISS-MODEL with the cryo-EM structure of human NBCe1 (PDB ID: 6CAA) as the template. Residues 445–1007 of mouse NBCe1-B was aligned with the homologous region of human NBCe1 by using SWISS-MODEL. The sequence identity between the two sequences is 96.09%. Structural assessment shows that the simulated model of mouse NBCe1 had QMEAN value −6.86, Cβ −3.57, solvation value −1.80, torsion value −5.49, and scored 1.49 by MolProbity approach.</p>
Data from: New forms of structure in ecosystems revealed with the Kuramoto model
<p>This is the general Mathematica code for the article, "New forms of structure in ecosystems revealed with the Kuramoto model" by Vandermeer, Hajian-Forooshani, Medina and Perfecto. All results presented in the article can be obtained by running the code with appropriate parameter settings.</p>
Data from: An updated 18S rRNA phylogeny of tunicates based on mixture and secondary structure models
BACKGROUND: Tunicates have been recently revealed to be the closest living relatives of vertebrates. Yet, with more than 2500 described species, details of their evolutionary history are still obscure. From a molecular point of view, tunicate phylogenetic relationships have been mostly studied based on analyses of 18S rRNA sequences, which indicate several major clades at odds with the traditional class-level arrangements. Nonetheless, substantial uncertainty remains about the phylogenetic relationships and taxonomic status of key groups such as the Aplousobranchia, Appendicularia, and Thaliacea. RESULTS: Thirty new complete 18S rRNA sequences were acquired from previously unsampled tunicate species, with special focus on groups presenting high evolutionary rate. The updated 18S rRNA dataset has been aligned with respect to the constraint on homology imposed by the rRNA secondary structure. A probabilistic framework of phylogenetic reconstruction was adopted to accommodate the particular evolutionary dynamics of this ribosomal marker. Detailed Bayesian analyses were conducted under the non-parametric CAT mixture model accounting for site-specific heterogeneity of the evolutionary process, and under RNA-specific doublet models accommodating the occurrence of compensatory substitutions in stem regions. Our results support the division of tunicates into three major clades: 1) Phlebobranchia + Thaliacea + Aplousobranchia, 2) Appendicularia, and 3) Stolidobranchia, but the position of Appendicularia could not be firmly resolved. Our study additionally reveals that most Aplousobranchia evolve at extremely high rates involving changes in secondary structure of their 18S rRNA, with the exception of the family Clavelinidae, which appears to be slowly evolving. This extreme rate heterogeneity precluded resolving with certainty the exact phylogenetic placement of Aplousobranchia. Finally, the best fitting secondary-structure and CAT-mixture models suggest a sister-group relationship between Salpida and Pyrosomatida within Thaliacea. CONCLUSION: An updated phylogenetic framework for tunicates is provided based on phylogenetic analyses using the most realistic evolutionary models currently available for ribosomal molecules and an unprecedented taxonomic sampling. Detailed analyses of the 18S rRNA gene allowed a clear definition of the major tunicate groups and revealed contrasting evolutionary dynamics among major lineages. The resolving power of this gene nevertheless appears limited within the clades composed of Phlebobranchia + Thaliacea + Aplousobranchia and Pyuridae + Styelidae, which were delineated as spots of low resolution. These limitations underline the need to develop new nuclear markers in order to further resolve the phylogeny of this keystone group in chordate evolution.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.