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464 results for “model structure”
Velocity models from "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities"
<p>The isotropic velocity models from joint inversion of Rayleigh- and Love-wave group-velocity measurements of S1222a. The details about these models and the joint inversion are in "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities" which is submitted to GRL.</p>
Sn velocity model and original catalogue data for essay "Uppermost mantle structure of the Japan subduction zone from Sn tomography"
<p>Sn velocity model and original catalogue data for essay “Uppermost mantle structure of the Japan subduction zone from Sn tomography”</p> <p> </p>
UAV-Based Height Measurement and Height-Diameter Model integrating Taxonomic Effects: Exploring Vertical Structure of Aboveground Biomass and Species Diversity in a Malaysian Tropical Forest
<p>These Excel files are the dataset used for the analysis in the submitted paper</p> <p>Dataset S1: Data for 6-ha pot in Pasoh Forest Researve</p> <p>Dataset S2: Data for height–diameter (HD) models</p>
A structured evaluation of regression models for predicting CO2 concentration from plasma emission spectra, dataset
<p>Dataset for publication: <a href="https://doi.org/10.1016/j.sab.2022.106467">https://doi.org/10.1016/j.sab.2022.106467</a>.</p> <p>The recorded spectra are stored as comma separated values, the set includes a meta data-file (.mat-file), and a column descriptions (columns.pdf).</p>
3D structure model of the TgREMIND F-BAR dimer
<p>Coordinates of the AlphaFold2 3D structure model of TgREMIND F-BAR domain dimer (amino acids 80 to 345, UniProt S7W754_TOXGG). The model of the dimer was made using ColabFold v1.5.2 (Mirdita, M., Schütze, K., Moriwaki, Y. <em>et al.</em> ColabFold: making protein folding accessible to all. <em>Nat Methods</em> <strong>19</strong>, 679–682 (2022). https://doi.org/10.1038/s41592-022-01488-1; https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb)</p> <pre> </pre>
STL files: Modeling and design of heterogeneous hierarchical bioinspired spider web structures using deep learning and additive manufacturing
<p>STL files for paper titled modeling and design of heterogeneous hierarchical bioinspired spider web structures using deep learning and additive manufacturing</p>
Parameters & Complexity Indexes of 3D CAD models from "Unleashing the Potential of Artificial Reefs Design: A Purpose-Driven Evaluation of Structural Complexity"
<p>You'll find here data frames related to the paper <strong>"Unleashing the Potential of Artificial Reefs Design: A Purpose-Driven Evaluation of Structural Complexity"</strong>:</p> <ul> <li>df_parameters: displays parameters from 3D CAD models of the study</li> <li>df_complexity_Indexes: displays the complexity indexes computed with the parameters of the 3D CAD models</li> </ul>
RNA 3D structure modeling by fragment assembly with Small Angle X-ray Scattering restraints
<p>Structure determination is a key step in the functional characterization of many non-coding RNA molecules. High-resolution RNA 3D structure determination efforts, however, are not keeping up with the pace of discovery of new non-coding RNA sequences. This increases the importance of computational approaches and low-resolution experimental data, such as from the Small Angle X-ray Scattering experiments. We present RNA Masonry, a computer program and a web service for a fully automated modeling of RNA 3D structures. It assemblies RNA fragments into geometrically plausible models that meet user-provided secondary structure constraints, restraints on tertiary contacts and Small Angle X-ray Scattering data. We illustrate the method description with detailed benchmarks and its application to structural studies of viral RNAs with SAXS restraints.</p>
Dataset of dynamical structure factor of Lieb-Liniger model
<p>This dataset contains all data and scripts to plot the figures of the article arXiv:2303.09208</p>
Alphafold predicted structures of VPS13 proteins from model organisms
<p>This upload contains AlphaFold-predicted structures of VPS13 proteins from a variety of organisms. Given the large size of these proteins, only partial sequences were predicted with AlphaFold(1) and the resulting structures were aligned in PyMOL(2). A summary of the structures uploaded here is presented as a collection of domain cartoons in the "VPS13 domain organization across eukaryotic evolution.pdf" file. </p> <p>The structures were generated with AlphaFold v2.029 on the Yale High Performance Cluster. Each *.zip file contains the best ranked predictions (out of five) for each sequence (*.pdb files) and the PyMOL assembled full structure (*.pse file). In a few cases, where a good alignment was not possible due to long disordered regions in the C-terminal portions (mostly in proteins from <em>D. discoideum</em> and <em>A. thaliana</em>), the full structures were aligned manually in PyMOL based on the continuity of the lipid transfer groove. The structures in PyMOL can be colour-coded by the confidence value of AlphaFold predictions using the following prompt:</p> <p>set_color n0, [0.051, 0.341, 0.827]<br> set_color n1, [0.416, 0.796, 0.945]<br> set_color n2, [0.996, 0.851, 0.212]<br> set_color n3, [0.992, 0.490, 0.302]<br> color n0, b < 100; color n1, b < 90<br> color n2, b < 70; color n3, b < 50</p> <p>Considering that full length structures were assembled by aligning different protein fragments and in view of the presence of flexible loops with low prediction confidence scores, the relative positions of different folded domains are not necessarily correct.</p> <p> </p> <p><strong>References</strong></p> <p>1. J. Jumper, <em>et al.</em>, Highly accurate protein structure prediction with AlphaFold. <em>Nature</em> 596, 583–589 (2021).</p> <p>2. The PyMOL Molecular Graphics System, Version 2.0. Schrödinger LLC.</p>
Modeling flexible protein structure with AlphaFold2 and cross-linking mass spectrometry
<p>Ensembles of models predicted by AlphaFold for the proteins C3 (Complement component 3), luciferase and QBP (glutamine-binding periplasmic protein). Models interpolated between two conformations of C3, and luciferase are also included. This dataset is cited in the following paper: https://www.biorxiv.org/content/10.1101/2023.09.11.557128v1</p>
Supplementary material for "Learning Conceptual Modeling: Structuring Overview, Research Themes and Paths for Future Research"
<p>This material containing a list of the bibliographical data of the final sample and the raw data set of 345 publications before excluding publications outside of our focus supplements the following literature review:</p> <p>Rosenthal, Kristina; Ternes, Benjamin; Strecker, Stefan, (2019). “Learning Conceptual Modeling: Structuring Overview, Research Themes and Paths for Future Research”. In: Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm and Uppsala, Sweden, June 8–14, 2019.</p>
Developing hierarchical density-structured models to study the national-scale dynamics of an arable weed
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Data from: Phylogenomic structure and speciation in an emerging model: The Sphagnum magellanicum complex (Bryophyta)
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Pleiotropic effects of trisomy and pharmacologic modulation on structural, functional, molecular, and genetic systems in a Down syndrome mouse model
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Structural models and Sort-seq data for: Packing of apolar amino acids is not a strong stabilizing force in transmembrane helix dimerization
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Data from: Nature versus nurture: Structural equation modeling indicates that parental care does not mitigate consequences of poor environmental conditions in Eastern bluebirds (Sialia sialis)
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Models from: Non-destructive in situ monitoring of structural changes of 3D tumor spheroids during the formation, migration, and fusion process
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The role of spatial structure in multi-deme models of evolutionary rescue
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Multi-species occupancy modeling provides novel insights into amphibian metacommunity structure and wetland restoration
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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)
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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.