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241 results for “Structural relationships”
Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome
<p>Dataset linked to the article with the same title</p> <p>The model itself is very similar to its non-plastic counterpart under the following DOI: <a href="../record/7930275">10.5281/zenodo.7930275</a>, i.e. a 1.5 mm diameter cortical tissue comprising 211,712 neurons and their connectivity in the front limb and jaw subregions and the dysgranular zone of the Paxinos & Watson rat brain atlas. It's formatted in the open <a href="https://github.com/AllenInstitute/sonata">SONATA</a> standard and contains neuron locations and their properties (such as morphological types, cortical layer, etc.), their detailed morphologies, and synaptic connectivity (with all their anatomical and physiological parameters). The main difference from the non-plastic version is the addition of plasticity related parameters to <em>O1/S1nonbarrel_neurons__S1nonbarrel_neurons__chemical/edges.h5. </em>Extrinsic synaptic connections from the thalamus are included in this release, but for inputs from neurons in the remainder of non-barrel somatosensory cortex please see the non-plastic version of the circuit.</p> <p><strong>Analyzing the model</strong></p> <p>The model can be analyzed in terms of its anatomy, physiology and connectivity using the packages <a href="https://neurom.readthedocs.io/en/stable/">NeuroM</a>, <a href="https://bluebrainsnap.readthedocs.io/en/stable/">BlueBrain SNAP</a> and <a href="https://github.com/BlueBrain/ConnectomeUtilities">ConnectomeUtilities</a>. (see first Jupyter notebook)</p> <p><strong>Simulating the model</strong></p> <p>To simulate the model we'd recommend using out using our open-source simulator <a href="https://github.com/BlueBrain/neurodamus">Neurodamus</a>. The reference version is the branch <em>nbS1-2023</em>, which is archived under the following DOI: <a href="http://doi.org/10.5281/zenodo.8075202">10.5281/zenodo.8075202</a>. Instructions on how to use the simulator are provided on the GitHub page linked above. Briefly, you'll first have to <a href="https://github.com/BlueBrain/neurodamus#install-neurodamus">install Neurodamus</a>. Next, build a <em>"special"</em> executable that include compiled versions of ion channel and synapse models. To do that, follow <a href="https://github.com/BlueBrain/neurodamus#build-special-with-mod-files">these instructions</a>, where <em>mod-files-from-released-circuit </em>is replaced by the location of <em>O1/mods</em> on your system. Finally, <a href="https://github.com/BlueBrain/neurodamus#examples">run a simulation</a>. The specific simulation conditions and stimuli are specified in simulation configuration files. An exemplary simulation configuration is included in this release (<em>simulation_config.zip</em>).</p> <p><strong>Analyzing simulation results</strong></p> <p>Simulation results can be analyzed with <a href="https://bluebrainsnap.readthedocs.io/en/stable/">BlueBrain SNAP</a>, <a href="https://github.com/BlueBrain/ConnectomeUtilities">ConnectomeUtilities</a>, and <a href="https://github.com/BlueBrain/assemblyfire">assemblyfire</a>. Notebooks 2-5 go though these analysis and recreate some of the panels from our article. In most cases the notebooks can be run with the shared HDF5 files and don't require running any simulations.</p> <p><strong>Version 2</strong></p> <p>Bug fix in simulation_config.json and therefore new version of results (and corresponding notebooks). The underlying circuit model (O1.xz) did not change from v1.</p> <p>--</p> <p><em>The development of this dataset was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.</em></p>
Data and results in "Relationship between crustal structure and plate convergence around the Izu collision zone in central Japan"
<p>“allrfstationlist.dat” contains the list of the used seismic stations. The four columns indicate the name, latitude, longitude, and altitude (m) of each station, respectively.</p> <p>“allrfevent.dat” contains the list of the used teleseismic events. From left to right, the 10 columns indicate the year, month (in number), day, hour, minute, and second of the origin time (Japan Standard Time), and the latitude (from –90 to 90), longitude (from –180 to 180), depth of the hypocenter, and magnitude of each event, respectively.</p> <p>“RFmoho.dat” contains the depth distribution of the Moho determined by our RF analysis. The third column indicates the depth (km) of the Moho at the given latitude (the second column) and longitude (the first column)</p> <p>“Tomo_depth_limited.txt” contains the depth distribution of the lower boundary of a layer with a P-wave velocity of 7.5–7.7 km/s in the model by Ishise et al. (2021), which was assumed as the Moho. The third column indicates its depth (km) at the given latitude (the first column) and longitude (the second column)</p> <p>“crustthickness_tomorf.dat” contains the thickness distribution of the crust of the Philippine Sea Plate determined from the geometry of its upper surface estimated by Hirose et al. (2008a, b) and Nakajima et al. (2009) and the Moho depth distribution shown in RFmoho.dat and Tomo_depth_limited.txt. The third column indicates the thickness (km) of the crust at the given latitude (the second column) and longitude (the first column). “RF” and “tomo” in the fourth column indicate the corresponding thickness determined based on the RF analysis and the model by Ishise et al. (2021), respectively.</p>
DFT optimised structure used for the paper "Cation Insertion to Break the Activity/Stability Relationship for Highly Active Oxygen Evolution Reaction Catalyst"
<p>DFT optimised structures used to calculate the OER activities in "Cation Insertion to Break the Activity/Stability Relationship for Highly Active Oxygen Evolution Reaction Catalyst". The structures are bundled in two databases, LiIrO3.db which contains all structures for alpha-LiIrO<sub>3</sub> and KLiIrO3-disordered.db which contains all the structures for the disordered Li<sub>0.75</sub>K<sub>0.25</sub>(H<sub>2</sub>O)<sub>0.50</sub>IrO<sub>3 </sub>structure. The structures can be retrieved using the Atomic Simulation Environment (ASE, https://wiki.fysik.dtu.dk/ase/index.html). The keywords 'ads' and 'surface' can be used to search the structure, e.g. surface='Z-step' and ads='*OOH' will give the structure with OOH adsorbed on the Z-step surface (see paper for details on the different surfaces).</p>
Chemical-genetic interrogation of RNA polymerase mutants reveals structure-function relationships and physiological tradeoffs
<p>The multi-subunit bacterial RNA polymerase (RNAP) and its associated regulators carry out transcription and integrate myriad regulatory signals. Numerous studies have interrogated the inner workings of RNAP, and mutations in genes encoding RNAP drive adaptation of <i>Escherichia coli</i> to many health- and industry-relevant environments, yet a paucity of systematic analyses has hampered our understanding of the fitness benefits and trade-offs from altering RNAP function. Here, we conduct a chemical-genetic analysis of a library of RNAP mutants. We discover phenotypes for non-essential insertions, show that clustering mutant phenotypes increases their predictive power for drawing functional inferences, and demonstrate that some RNA polymerase mutants both decrease average cell length and confer insensitivity to killing by cell-wall targeting antibiotics. Our findings demonstrate that RNAP chemical-genetic interactions provide a general platform for interrogating structure-function relationships <i>in vivo</i> and for identifying physiological trade-offs of mutations, including those relevant for disease and biotechnology. This strategy should have broad utility for illuminating the role of other important protein complexes.</p>
Classification of Matching Molecular Series on the Basis of SAR Phenotypes and Structural Relationships
<p>A database comprising a total of 13,236 pairs of MMS with different SAR characteristics is provided. For each pair the corresponding MMS-cores are provided as SMILES. In addition, for each MMS-core the number of compounds and the SAR phenotype are given. ChEMBL target IDs (CHEMBLID_Target) designate target sets from which the MMS pairs originate. </p>
Research data supporting: "Machine learning of microscopic structure-dynamics relationships in complex molecular systems"
<p>This repository contains the set of data and the code to reproduce the results shown in "Machine learning of microscopic structure-dynamics relationships in complex molecular systems" published on Machine Learning: Science and Technology (DOI: 10.1088/2632-2153/ad0fa5).</p>
FIG. 2 in Nematode community structure of forest woodlots. I. Relationships based on similarity coefficients of nematode species
FIG. 2. Dendrogram of forest sites in Tippecanoe County, Ind., based on similarity indices of nematode species.
FIG. 1 in Nematode community structure of forest woodlots. I. Relationships based on similarity coefficients of nematode species
FIG. 1. Influence of the number of soil cores taken at Tippecanoe County, Ind., at site P on the number of nematode species recovered.
The chloroplast genomes of Sanicula (Apiaceae): plastome structure, comparative analyses, and phylogenetic relationships
<p><em>Sanicula</em> (Apiaceae subfamily Saniculoideae) is a taxonomically difficult genus of medicinal value. Its distribution center is in China, where there are 18 species (11 of which are endemic). To provide plastid genome resources, whole chloroplast genomes of five <em>Sanicula</em> species (<em>S. flavovirens</em>, <em>S. giraldii</em>, <em>S. lamelligera</em>, <em>S. odorata</em>, and <em>S. rubriflora</em>) were sequenced and compared to the previously published <em>S. orthacantha</em> plastome. These genomes exhibit a typical quadripartite structure. All contain 129 different genes, including 84 protein-coding, 37 tRNA, and 8 rRNA genes. Loci <em>rpl2</em>, <em>matK</em>, <em>psbA</em>, and <em>ycf1</em> are the most variable. Results of maximum likelihood analysis of 90 whole plastome sequences from Apioideae and Saniculoideae and the outgroup <em>Hydrocotyle</em> (Araliaceae) reveal sectional relationships in <em>Sanicula</em> different from the traditional classification system, support the monophyly of Apioideae and its sister group relationship to Saniculoideae, and show concordant topologies to nrDNA ITS and other plastome-based phylogenies. <em>Sanicula orthacantha</em> and <em>S. chinensis</em> form a clade sister group to <em>S. lamelligera</em> and <em>S. odorata</em>, consecutively. These four species comprise a clade sister group to the clade of <em>S. rubriflora</em> and <em>S. flavovirens</em>, with this entire group sister to <em>S. giraldii</em>. The plastid genome resources provided herein will be important for future systematic, evolutionary, phylogenomic, and population-level studies of <em>Sanicula</em>.</p>
Sequence-structure-function relationships in the microbial protein universe
<p>The Microbiome Immunity Project (MIP) dataset contains models predicted with both Rosetta and DMPFold (folder `dataset/`). It also contains DeepFRI function predictions for all models. </p> <p>The `metadata` folder contains additional data which may be useful for searching the MIP database (FASTA files, BLAST databases and useful scripts for structure/function search) as well as retrieving the sequence/structural annotations.</p> <p>The `intermediate_data` folder contains preprocessed output for reproducing many of the figures in our manuscript in conjunction with scripts and Juypter notebooks found in our git repository: https://github.com/microbiome-immunity-project/protein_universe .</p> <p>More information about the dataset and associated metadata is provided in the `README.md` file).</p> <p>We are also providing workflows to search the MIP database against a protein sequence or structure or function of interest (see `SEARCHING.md` for more details).</p>
Figs 121–126 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 121–126. Proboscis and hooks of Paratrajectura longcementglandatus (Transvenidae): 121 — proboscis of P. longcementglandatus with longer anterior hooks; 122 — shorter and more deeply embedded posterior hooks. Note sensory pore just posterior to basal hooks; 123, 124 — a Gallium-cut longitudinal sections of a middle and a more posterior hook, respectively, showing consistent solid core and thin cortical layers continuous with roots; 125 — a partially vacuolated core of another hook in a Gallium cut cross section; 126 — an unusually branched hook in middle of proboscis.
Figs 103–108 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 103–108. Proboscis and hooks of Pallisentis (Pallisentis) nandai (figs 103–107) and Pallisentis (Pallisentis) paranandai (fig. 108) (Quadrigyridae): 103 — an apical view of the proboscis of P. nandai showing the hook arrangement and the proboscis bumps; 104 — an anterior hook with latero-ventral serrations; 105 — a higher magnification of the base of an anterior hook at indented insertion in elevated proboscis ring; note the latero-ventral serrations; 106–107 — a Gallium-cut longitudinal and cross sections of anterior hooks showing the proportion of cortical and core layers and continuity with root elements. These hooks had very high levels of calcium and sulfur but negligible levels of phosphorous; 108 — anterior and middle hooks of P. paranandai also showing elevated serrations at their base.
Figs 97–102 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 97–102. Proboscis and hooks of Acanthogyrus (Acanthosentis) kashmirensis (figs 97–99), Acanthogyrus (Acanthosentis) fusiformis (fig. 100), and Pallisentis (Brevitritospinus) indica (figs 101–102)(Quadrigyridae):97—proboscisof A. kashmirensis showing hook arrangement and sensory pore at its base; 98 — profile of anterior and middle hooks showing their emaciated appearance; 99 — the appearance of the hooks in fig. 98 is explained by their hollow core; see this figure of a Gallium-cut cross section of an anterior hook; 100 — the unusual shape of the proboscis of A. fusiformis with the smaller hooks on the anterior constricted part of the proboscis; 101 — the proboscis of P. indica showing proboscis bumps and sensory pore at its posterior end; 102 — a middle hook showing its angle and relative dimensions.
Figs 73–78 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 73–78. SEM of proboscis and hooks of Nephridiacanthus major (Oligacanthorhynchidae): 73 — hook arrangement and prominent neck of N. major; 74 — a dorso-lateral view of proboscis showing slightly elevated surface of apical organ; 75 — dorsal view of a short posterior hook; 76 — a Gallium-cut section of a hook near its base with prominent ventral expansion similar to that in M. hirudinaceus with almost no cortical layer seen; 77 — a perfectly spherical Gallium cut cross section of another hook near its terminal end; 78 — a lateral Gallium-cut section of another hook showing the same core-cortical relationships as in figs 76 & 77. Note the continuity with the elaborate root.
Figs 49–54 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 49–54. SEM of proboscis and hooks of Moniliformis Saudi (figs 49–50) and Moniliformis kalahariensis (figs 51–54) (Moniliformidae): 49 — apical end of a proboscis of M. Saudi also had 2 sensory pores like M. cryptosaudi; 50 — a middle hook with high levels of calcium and phosphorous; 51 — the proboscis of M. kalahariensis; hooks gradually decrease in size posteriorly; 52 — undeveloped hooks from cockroach; 53 — developing hooks in a juvenile beginning to develop lateral grooves; 54 — fully developed hooks in an adults with completely formed lateral grooves. Hooks of M. kalahariensis, also had high levels of calcium and phosphorous like hooks of M. saudi.
Figs 79–84 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 79–84. SEM of proboscis and hooks of Pachysentis canicola (Oligacanthorhynchidae) (figs 79–82) and Corynosoma strumosum (Polymorphidae) (figs 83, 84): 79 — the proboscis of a female P. canicola showing hook arrangement and sensory pores at posterior proboscis and neck; 80 — an anterior hook deeply recessed in thick cuticular fold; 81 — a posterior hook also deeply recessed in a boat-like cuticular fold; 82 — a Gallium-cut cross section of a hook near its base showing the ventral protrusion as seen in other oligacanthorhynchid genera: Macracanthorhynchus and Nephridiacanthus; 83 — the proboscis of a specimen of C. strumosum showing its bare apical end and larger hooks at the bulge; 84 — a high magnification of a hook showing micropores.
Figs 91–96 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 91–96. Proboscis and hooks of Southwellina hispida (Polymorphidae): 91 — a proboscis of a juvenile S. hispida showing the long anterior hooks, the shorter and thicker middle hooks at swelling, and the smaller posterior hooks; 92 — a few anterior hooks; 93 — shorter and more robust middle hooks at swelling; 94–95 — variations on the degree of vacuolation of the core of hooks with relatively thick cortical layer; 96 — a Gallium-cut section of a middle hook showing a thin cortical layer and solid core.
Figs 31–36 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 31–36. SEM and microscope image of proboscis and hooks of Intraproboscis sanghae (figs 31–34) and SEM of Mediorhynchus africanus (figs 35, 36) (Gigantorhynchidae): 31 — anterior and posterior proboscis of I. sanghae; 32 — a microscope black and while image of proboscides showing the dark receptacle within the posterior proboscis; 33 — the flat apical end of the anterior proboscis with hooks; 34 — a higher magnification of an anterior hook showing the lamellar texture of the lateral and ventral surface; 35 — proboscis of M. africanus showing the divide between anterior hooks and posterior spine-like hooks; 36 — face view of anterior hooks of M. africanus showing proboscis swelling at insertion.
Figs 7–12 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 7–12. SEM of proboscides and hooks of Parhadinorhynchus magnus (Cavisomidae) (figs 7–9) and Centrorhynchus globirostris (Centrorhynchidae) (figs 10– 12): 7 — long cylindrical proboscis with gradually decreasing hook size posteriorly; 8 — a ventral hook; note its curvature and robust base; 9 — a Gallium-cut cross section of a middle hook showing in thick core with high phosphorous and calcium content, and thin cortical layer; 10 — the globular proboscis of C. globirostris showing the separation line between the larger anterior hooks and the smaller posterior spine-like hooks where the anterior end of the receptacle inserts; 11 — an anterior hook showing the ribbed surface found on all hooks; 12 — a Gallium-cut longitudinal section of a hook showing its thick core and marginal cortical layer.
Figs 25–30 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 25–30. SEM of proboscis and hooks of Echinorhynchus cinctulus (figs 25–28) and Echinorhynchus gadi (figs 29–30) (Echinorhynchidae): 25–27 — anterior hooks in some specimens of E. cinctulus with a variety of spines or thorns mostly on the dorsal side of hooks; 28 — the welldeveloped core and thinner cortical layer of a Gallium-cut longitudinal section of a middle hook; 29 — a proboscis of an E. gadi specimen with 15 hooks per row and elevated anterior hooks; 30 — a high magnification of depressed posterior hooks on the same proboscis in fig. 29.
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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.