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3,878 results for “Molecular Data”
FIGURE 7 in Revision of some historical types of the genus Lithobius Leach, 1814 (Chilopoda, Lithobiomorpha) from the 1949/50 Austrian Iran Expedition, with new molecular data for L. iranicus Attems, 1951
FIGURE 7. Ocellar field in lateral view. A. Lithobius iranicus Attems, 1951, paralectotype ♂, NHMW MY3964. B. Lithobius inaequidens Attems, 1951 syn. nov., syntype ♂, NHMW MY3962. C. Lithobius inaequidens Attems, 1951 syn. nov., syntype ♂, NHMW MY10385. D. Lithobius iranicus Attems, 1951, syntype ♂, NHMW MY10383. E. Lithobius rhiknus Attems, 1951 syn. nov., syntype ♂, NHMW MY4044. Abbreviation: TO = Tömösváry's organ.
Data for "Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition"
<p>Data for "Neutron scattering and neural-network quantum molecular dynamics investigation of the vibrations of ammonia along the solid-to-liquid transition".</p> <p>neutron_data.zip --> neutron data in .nxspe form. S(Q,E) calculated using the DAVE software. Includes logbook spreadsheet. </p> <p>Training_Data.xyz --> xyz file containing training data used to generate Allegro machine learning forcefield in the paper</p> <p>nh3_pimd.deploy --> Trained Allegro model to that can be used in LAMMPS and RXMD software a ML forcefield </p> <p>POSCAR_UNIT_CELL_AMMONIA --> NH3 unit cell in solid phase in POSCAR format that can be read by the VASP software used to perform the DFT simmulations.</p>
FIGURE 10 in A systematic assessment of Leporinus tigrinus (Characiformes: Anostomidae) using morphological and molecular data
FIGURE 10. Partial map of South America showing the distribution of Leporinus tigrinus based on material examined in the present study.
FIGURE 9 in A systematic assessment of Leporinus tigrinus (Characiformes: Anostomidae) using morphological and molecular data
FIGURE 9. (A) Pectoral fin, (B) pelvic fin and (C) caudal fin of Leporinus tigrinus (MZUEL 20673, 112.0 mm SL)
FIGURE 4 in A systematic assessment of Leporinus tigrinus (Characiformes: Anostomidae) using morphological and molecular data
FIGURE 4. Photographs of living specimens of Leporinus tigrinus from (A) rio Araguaia, Luiz Alves, Goiás (photo by José Birindelli), and (B) rio Xingu, Altamira, Pará (photo by Leandro Sousa).
FIGURE 6 in A systematic assessment of Leporinus tigrinus (Characiformes: Anostomidae) using morphological and molecular data
FIGURE 6. Cranium bones of Leporinus tigrinus (MZUEL 20673, 112.0 mm SL) in (A) dorsal, (B) lateral and (C) ventral view.
FIGURE 2 in A systematic assessment of Leporinus tigrinus (Characiformes: Anostomidae) using morphological and molecular data
FIGURE 2. Phylogenetic tree of Leporinus tigrinus and related species generated by Bayesian Inference based on cytochrome oxidase subunit I (COI) sequences. The colors represent the molecular operational taxonomic units found. Vertical bars on the left show the results of delimitation species analyses.
FIGURE 5 in A systematic assessment of Leporinus tigrinus (Characiformes: Anostomidae) using morphological and molecular data
FIGURE 5. (A) Suspensorium of Leporinus tigrinus (MZUEL 20673, 112.0 mm SL); (B) Premaxilla, maxilla, dentary and anguloarticular; (C) Infraorbital bones.
FIGURE 7 in A systematic assessment of Leporinus tigrinus (Characiformes: Anostomidae) using morphological and molecular data
FIGURE 7. (A) Hyoid arc and (B and C) branchial apparatus of Leporinus tigrinus (MZUEL 20673, 112.0 mm SL)
HER2 RNA Molecular Simulation Data
<p>This is a data file for the HER2 RNA molecular simulation research by Arli Aditya Parikesit. More on me, please kindly check this link: orcid.org/0000-0001-8716-3926 </p>
Kreysing_et_al_2024_molecular_dynamics_simulation_data
<p>The molecular dynamics simulation data set accompanying Kreysing et al, 2024, containing (i) representative coordinates and measurements described therein, (ii) selected simulation trajectories, and (iii) LAMMPS input files.</p>
Data for "FC2DES: Modeling 2D electronic spectroscopy for the Generalized Brownian Oscillator Molecular Hamiltonian"
<p>Within is the 2DES presented in the manuscript: "FC2DES: Modeling 2D electronic spectroscopy for the Generalized Brownian Oscillator Molecular Hamiltonian" as well as the parameter and input files used to create the spectra via the Python code package MolSpecPy.</p>
FIGURE 2 in Cymbidium biflorens (Orchidaceae; Epidendroideae), a new species from China: evidence from morphological and molecular data
FIGURE 2. Phylogenetic relationships of C. biflorens based on the combined plastid DNA. The numbers near the nodes are Bayesian posterior probabilities (PP), maximum likelihood bootstrap percentages (BP ML) and maximum parsimony bootstrap percentages (BP MP). "*" indicates that the node has BP 100 or PP 1.00. "-" indicates that the node is incongruent between the Bayesian and MP/ML trees.
Data for 'Ranking Single Fluorescent Protein Based Calcium Biosensor Performance by Molecular Dynamics Simulations'
<h2>Melike Berksoz, Canan Atilgan* </h2> <h3>Faculty of Engineering and Natural Sciences, Sabanci University </h3> <p><strong>*Correspondance:</strong> Canan Atilgan, Faculty of Natural Sciences and Engineering, Sabancı University, Tuzla 34956 Istanbul, Türkiye, E-mail: canan@sabanciuniv.edu</p> <p>Genetically Encoded Fluorescent Biosensors (GEFBs) have become indispensable tools for visualizing biological processes <em>in</em> <em>vivo.</em> A typical GEFB is composed of a sensory domain (SD) which undergoes a conformational change upon ligand binding and a genetically fused fluorescent protein (FP). Ligand binding in the SD allosterically modulates the chromophore environment and changes its spectral properties. Single fluorescent (FP)-based biosensors, a subclass of GEFBs, offer a simple experimental setup; they are easy to produce in living cells, structurally stable and simple due to their single-wavelength operation. However, they pose a significant challenge for structure optimization, especially concerning the length and residue content of linkers between the FP and SD which effect how well the chromophore responds to conformational change in the SD. In this work, we use classical all-atom molecular dynamics simulations to analyze the dynamic properties of a series of calmodulin-based calcium biosensors, all with different FP-SD interaction interfaces and varying degrees of calcium binding dependent fluorescence change. Our results indicate that biosensor performance can be predicted based on distribution of water molecules around the chromophore and shifts in hydrogen bond occupancies between the ligand-bound and ligand-free sensor structures.</p> <p>Hydrogen bond occupancies were calculated with merging_bonds.py script. Double counted hydrogen bonds where a residue acts both as acceptor and donor are merged into a single entry with merge_files.py. To run sasa.tcl, you need VMD software. Trajectories were created with NAMD2 with a dcdfrequency of 5000 timesteps (every 10 ps) and strided in a 1:100 ratio (every 1 ns=1 frame in dcd). </p>
Estimating the time since admixture from phased and unphased molecular data
<p>After admixture, recombination breaks down genomic blocks of contiguous ancestry. The breakdown of these blocks forms a new `molecular clock', that ticks at a much faster rate than the mutation clock, enabling accurate dating of admixture events in the recent past. However, existing theory on the break down of these blocks, or the accumulation of delineations between blocks, so called `junctions', has mostly been limited to using regularly spaced markers on phased data. Here, we present an extension to the theory of junctions using the Ancestral Recombination Graph that describes the expected number of junctions for any distribution of markers along the genome. Furthermore, we provide a new framework to infer the time since admixture using unphased data. We demonstrate both the phased and unphased methods on simulated data and show that our new extensions have improved accuracy with respect to previous methods, especially for smaller population sizes and more ancient admixture times. Lastly, we demonstrate the applicability of our method on three empirical datasets, including labcrosses of yeast (Saccharomyces cerevisae) and two case studies of hybridization in swordtail fish and Populus trees.</p>
Data Sets for Article: Exploration on Learning Molecular Docking with Deep Learning Models
<p>The MOL2 and CSV file of the clustered compounds from ChemDiv are available in <strong>Additional file 2</strong></p> <p>Docking scores of training set1 and the following traing set2 for each target were saved as csv files and provided in <strong>Additional file 3.</strong></p> <p>The SMILES, MOL2, SDF of DUD-E compounds and PDB of receptors used for validation are provided in <strong>Additional file 4</strong>.</p> <p>The SMILES of 500,000 compounds randomly selected from the ChEMBL database are provided in <strong>Additional file 5</strong></p> <p>The SMILES of compounds with activities from the ChEMBL database for each target are provided in <strong>Additional file 6</strong></p>
FIGURE 3. Tetrataenium mianguaqi. A in A new species of Tetrataenium (Tordyliinae, Apiaceae) from SW Yunnan, China, based on morphological and molecular data
FIGURE 3. Tetrataenium mianguaqi. A. plants; B. root; C. basal leaf; D. inflorescences; E. young fruit. Photographed by Li Chen.
FIGURE 1. Jackknife 50 in A new species of Tetrataenium (Tordyliinae, Apiaceae) from SW Yunnan, China, based on morphological and molecular data
FIGURE 1. Jackknife 50% majority-rule tree of tribe Tordylieae (Apiaceae) and outgroups based on the nrITS region. The MP jackknife support (JK) values are shown above the branches and the BI posterior probabilities (PP) are given below the branches.
FIGURE 2. Tetrataenium mianguaqi. A in A new species of Tetrataenium (Tordyliinae, Apiaceae) from SW Yunnan, China, based on morphological and molecular data
FIGURE 2. Tetrataenium mianguaqi. A. plants; B. inflorescences with petals; C. inflorescences without petals; D. infructescence with young fruits; E. flower with petals; F. young fruit. Drew by Dr. Yuan Luo.
Figure 6 in Molecular and phenotypic data reveal a new Amazonian species of pit vipers (Serpentes: Viperidae: Bothrops)
Figure 6. Geographic map of South America showing the distribution of Bothrops oligobalius sp. nov. (yellow) and B. brazili (red). Outlined diamonds and circles represent sites with genetic samples available. Diamonds with an inner dot indicate the type locality of each both species. The Amazonian biome is highlighted in green; the Amazon River is also indicated. Photos: B. oligobalius sp. nov. from French Guiana, by Maël Dewynter; B. brazili from Porto Velho, RO, Brazil, by FDV.
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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.