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464 results for “model structure”
Transformed crane data from: Balancing structural complexity with ecological insight in spatio-temporal species distribution models
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National forest inventory data for a size-structured forest population model
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Data from: Dinosaurian survivorship schedules revisited: new insights from an age-structured population model
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Site-specific structure and stability constrained substitution models improve phylogenetic inference
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Structural modeling of hERG channel: Drug interactions using Rosetta
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Structural equation modeling reveals determinants of fitness in a cooperatively breeding bird
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UltraScan Solution Modeler (US-SOMO) hydrodynamic parameter, structural small angle scattering and SESCA circular dichroism (CD) calculations on AlphaFold predicted structures
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FAPM: Functional annotation of proteins using multi-modal models beyond structural modeling
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Know what you don't know: Embracing state uncertainty in disease-structured multistate models
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Inferring the evolutionary model of community-structuring traits with convolutional kitchen sinks: Code and data
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Model data created by MANDIFORE using ED2 simulating structure and biomass under harvest legacies and climate change as the Morton Arboretum, IL, USA, 2007-2099"
The data in this archive was used to investigate the long-term impacts of harvest-based management strategies on structure and resistance to climate-induced biomass loss using a process-based ecosystem model and an ensemble of climate change drivers in a midwestern USA hardwood forest. The model used was a modified version of the Ecosystem Demography model version 2.1 (ED2) where trees could be grouped based on plant functional type and size allowing for different management regimes to be simulated. The simulation site was an actively managed mid-continental North American temperate deciduous forest at The Morton Arboretum (TMA) near Chicago, USA. The initial conditions (composition and structure) of the forest simulated were initialized using field survey data from 487, 8.92-m radius plots collected in 2018. Different levels of tree removal based on traditional forestry management techniques for temperate deciduous forests were simulated and evaluated for their effects on forest structure and resistance to drought induced mortality for the period of 2006 to 2100. Model initialization and spin up occurred from 2006-2020 at which point management was simulated for the period of 2020-2024 before running without management for 2024 to 2100. Fourteen CMIP5 GCMs were used for meteorological drivers for 2006 to 2100 for both RCP4.5 and RCP 8.5 warming scenarios. CO2 concentration was held constant at 380 ppm over the simulation period. Four management regimes were simulated for each of these GCM-RCP pairings leading to a total of 112 distinct model runs. The four management regimes were group selection, shelterwood, understory thinning and an additional no management scenario served as a control. Data in this archived is separated into the 112 distinct model runs.
3D Cortical Bone and Trabecular Bone Structure [synthetic data, simple, capsule shell model]
<p>Trabecular bone patterns are mimicked by generating and arranging "capsule shells" in a three-dimensional voxel by following probability distribution. Ground truth (gt) contains 4 labels (Background: 0, Cortical Bone: 11, Trabecular Bone: 21, Cavity: 31).</p>
RosettaAntibody generated models for a dataset of 49 antibody-Fv structures
<p><strong>Structures of antibody-Fv domains computationally generated by RosettaAntibody based on the protocol of </strong><a href="https://www.nature.com/articles/nprot.2016.180?proof=true&draft=marketing">Weitzner, Jeliazkov, Lyskov et al.</a><strong> (Nature Protocols 12, 401–416, 2017). There are 49 antibody targets, with about 2800 decoy structures provided per antibody. A table is also provided with the H3-loop rmsd of each structure from the experimental crystal structure.</strong></p> <p><strong>These structures can be used to evaluate whether a score function can identify the near-native structures from the pool of decoys. These structures can also be used for comparison with other sets of structures generated by other antibody structure prediction programs.</strong></p> <p><strong>The research study on this set is unpublished and a manuscript is under preparation. Please cite Jeliazkov, Frick, Zhou & Gray, “Robustification of RosettaAntibody and Rosetta SnugDock,” in preparation, 2020.</strong></p> <p><strong>The homology modeling stage of RosettaAntibody was run with stringent homolog exclusion settings, excluding CDR templates of over 95% identity and FR templates of over 90% identity. The H3 modeling stage was run as described by <a href="https://www.nature.com/articles/nprot.2016.180">Weitzner, Jeliazkov, Lyskov et al.</a> (Nature Protocols 12, 401–416, 2017). </strong></p> <p><strong>The set of 49 antibody-Fv domains was originally compiled by <a href="https://academic.oup.com/peds/article/29/10/409/2462315">Marze et al. </a>(Protein Eng. Des. Sel. 29(10), 409-418, 2016). The dataset was first used to evaluate CDR-H3 loop rmsds in <a href="https://www.jimmunol.org/content/early/2016/11/18/jimmunol.1601137">Weitzner and Gray </a>(J. Immunology 198(1):505-515, 2017).</strong></p> <p><strong>The dataset can be extracted on a linux interface using: </strong></p> <p><strong> tar -xvzf <a href="https://www.zenodo.org/api/files/c2ba9da2-0d46-4aba-adbf-8ddd39b52b29/decoys_rosettaantibody_20200323.tar.gz?versionId=df264fc5-c79c-47b4-82bf-d1cda1e025e2">decoys_rosettaantibody_20200323.tar.gz</a> </strong></p> <p><strong>When extracted the output comprises RosettaAntibody generated models for 49 antibodies in the format:</strong></p> <p><strong><Antibody pdb id> / model-<id 1>.relaxed_<id 2>.pdb.gz</strong></p> <p><strong>The Rosetta "ref2015" scores (ref2015_score) and rmsd of the H3 loop (h3_rmsd) for every model (model) is provided in model_scores_and_rmsds.txt . RMSDs are calculated with respect to the corresponding crystal structure (pdb id) over all heavy atoms in the h3 loop (93–102 in Chothia numbering) after superposition of the framework residues. ID 1 comes from the homology model source (lower is better). ID 2 indicates the loop model.</strong></p> <p><strong>The decoy PDB files contain additional metrics following the ATOM records such as VH–VL relative orientation metrics (from Marze et al.) and per-residue Rosetta scores. Caveat: the “RMS” values reported within the decoy files were calculated against the input homology model and not the crystal structures (whereas the model_rmsds.txt file contains the H3 rmsds w.r.t. crystal).</strong></p>
Multi-species occupancy modeling provides novel insights into amphibian metacommunity structure and wetland restoration
<p>A fundamental goal of community ecology is to understand species-habitat relationships and how they shape metacommunity structure. Recent advances in occupancy modeling enable habitat relationships to be assessed for both common and rare species within metacommunities using multi-species occupancy models (MSOM). These models account for imperfect species detection and offer considerable advantages over other analytical tools commonly used for community analyses under the elements of metacommunity structure (EMS) framework. Here, we demonstrate that MSOM can be used to infer habitat relationships and test metacommunity theory, using amphibians. Repeated frog surveys were undertaken at 55 wetland sites in eastern Australia. We detected 11 frog species from three families (Limnodynastidae, Myobatrachidae and Pelodryadidae). The rarest species was detected at only one site whereas the most common species was detected at 42 sites (naïve occupancy rate: 0.02 – 0.76). Two models were assessed representing two competing hypotheses; the best-supported model included the covariates distance to the nearest site (connectivity), wetland area, presence of the non-native eastern mosquitofish (<i>Gambusia holbrooki</i>), proportion cover of emergent vegetation, an interaction term between Gambusia and emergent vegetation cover, and the proportion canopy cover over a site. Hydroperiod played no detectable role in metacommunity structure. We found species-habitat relationships that fit with current metacommunity theory – occupancy increased with wetland area and connectivity. There was a strong negative relationship between occupancy and the presence of predatory Gambusia, and a positive interaction between Gambusia and emergent vegetation. The presence of canopy cover strongly increased occupancy for several tree frog species, highlighting the importance of terrestrial habitat for amphibian community structure. We demonstrated how responses by amphibians to environmental covariates at the species level can be linked to occupancy patterns at the metacommunity scale. Our results have clear management implications – wetland restoration projects for amphibians and likely other taxa should maximize wetland area and connectivity, establish partial canopy cover, and eradicate Gambusia or provide aquatic vegetation to mitigate the impact of this non-native fish. We strongly advocate the use of MSOM to elucidate the habitat drivers behind animal occupancy patterns and to derive unbiased occupancy estimates for monitoring programmes.</p>
Dataset accompanying paper submission for "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"
<p>This data set accompanies code archived at DOI: <a href="https://doi.org/10.5281/zenodo.3833186">10.5281/zenodo.3833186</a>, which was used in the experiments for the paper submission "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"</p>
Data from: Characterizing morphological (co)variation using structural equation models: body size, allometric relationships and evolvability in a house sparrow metapopulation
Body size plays a key role in the ecology and evolution of all organisms. Therefore, quantifying the sources of morphological (co)variation, dependent and independent of body size, is of key importance when trying to understand and predict responses to selection. We combine structural equation modeling with quantitative genetics analyses to study morphological (co)variation in a meta-population of house sparrows (Passer domesticus). As expected, we found evidence of a latent variable 'body size', causing genetic and environmental covariation between morphological traits. Estimates of conditional evolvability show that allometric relationships constrain the independent evolution of house sparrow morphology. We also found spatial differences in general body size and its allometric relationships. On islands where birds are more dispersive and mobile, individuals were smaller and had proportionally longer wings for their body size. While in islands where sparrows are more sedentary and nest in dense colonies, individuals were larger and had proportionally longer tarsi for their body size. We corroborated these results using simulations and show that our analyses produce unbiased allometric slope estimates. This study highlights that in the short term allometric relationships may constrain phenotypic evolution, but that in the long term selection pressures can also shape allometric relationships.
Developing hierarchical density-structured models to study the national-scale dynamics of an arable weed
<p class="BodyText1">Population dynamics can be highly variable in the face of environmental heterogeneity, and understanding this variation is central in the study of ecology. Robust management decisions require that we understand how populations respond to management at a range of scales, and under a broad suite of conditions. Population models are potentially valuable tools in addressing this challenge. However, without adequate data, models can fail to produce useful results. Populations of arable weeds are particularly problematic in this respect, as they are widespread and their dynamics are extremely variable. Owing to the inherent cost of collecting data, most studies of weed population dynamics are derived from localized experiments under a small range of environmental conditions, limiting the extent to which variance in population dynamics can be measured. Density-structured models provide a route to rapid, large-scale analysis of population dynamics, and can expand the scale of ecological models that are directly tied to data. Here we extend previous density-structured models to include environmental heterogeneity, variation in management, and to account for inter-population variation. We develop, parameterize and test hierarchical density-structured models for a common agricultural weed, black-grass (<i>Alopecurus myosuroides</i>). We model the dynamics of this species in response to crop management, using survey data gathered over 4 years from 364 fields across a network of 45 UK farms. We show that hierarchical density-structured models provide a substantial improvement over their non-hierarchical counterparts. Using these models, we demonstrate that several alternative crop-rotations are effective in reducing weed densities. Rotations with high wheat prevalence exhibit the most severe infestations, and diverse rotations generally have lower weed densities. However, a key outcome is that in many cases the effect of crop rotation is small compared to the high variability arising from spatio-temporal heterogeneity. This result highlights the need to monitor and model population dynamics across large spatial and temporal scales in order to account for variation in the drivers of plant dynamics. Our framework for data collection and modelling provides a means to achieve this.</p>
Supporting data: Structure-based Markov random field model for representing evolutionary constraints on functional sites
<p>Supporting data for the paper:</p> <p>Chan-Seok Jeong, Dongsup Kim. Structure-based Markov random field model for representing evolutionary constraints on functional sites. Submitted. (2015)</p> <p>See 'README' for a description of the contents.</p>
Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. Part I: Adaptive local approximate models
<p>The global search stage of Crystal Structure Prediction (CSP) methods requires a fine balance between accuracy and computational cost, particularly for the study of large flexible molecules. A major improvement in the accuracy and cost of the intramolecular energy function used in the CrystalPredictor II (Habgood, M., Sugden, I. J., Kazantsev, A. V., Adjiman, C. S. & Pantelides, C. C. (2015).<em> J Chem Theory Comput</em> <strong>11</strong>, 1957-1969) program is presented, where the most efficient use of computational effort is ensured via the use of adaptive Local Approximate Model (LAM) placement. The entire search space of relevant molecule’s conformations is initially evaluated using a coarse, low accuracy grid. Additional LAM points are then placed at appropriate points determined via an automated process, aiming to minimise the computational effort expended in high energy regions whilst maximising the accuracy in low energy regions. As the size, complexity, and flexibility of molecules increase, the reduction in computational cost becomes marked. This improvement is illustrated with energy calculations for benzoic acid and the ROY molecule, and a CSP study of molecule XXVI from the sixth blind test (Reilly <em>et al.</em>, (2016).<em> Acta Cryst. B, accepted</em>.), which is challenging due its size and flexibility. Its known experimental form is successfully predicted as the global minimum. The computational cost of the study is tractable without the need to make unphysical simplifying assumptions. </p>
A voltage-dependent fluorescent indicator for optogenetic applications, archaerhodopsin-3: Structure and optical properties from in silico modeling
<p>seq.fasta and P96787_1UAZ.fasta are the input files for I-TASSER suite.</p> <p>The command of running I-TASSER suite:<br> path-to-I-TASSER-dir/I-TASSERmod/runI-TASSER.pl -pkgdir path-to-I-TASSER-dir -libdir path-to-I-TASSER-lib-dir -seqname P96787 -datadir path-to-workdir -outdir path-to-outdir -java_home /usr/ -restraint2 P96787_1UAZ.fasta</p> <p>For detailed data please refer to I-TASSER documentation.</p> <p>The P96787_1UAZ_IT.zip is an archieve with I-TASSER output for the best achaerhodopsin-3 prediciton.</p> <p>SCRIPTS_GENERAL.zip contains all the scripts for the structure postprocessing: addition of hydrogen atoms,<br> chromophore insertion and equilibration, internal waters addition.</p> <p>P96787_wi.pdb is a final prepared structure.</p> <p>Input files for spectra calculations are rhodopsin_gaussian.inp and rhodopsin_orca.inp.</p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.