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1,375 results for “molecular analysis”
The predator problem and PCR primers in molecular dietary analysis: swamped or silenced; depth or breadth? - Dataset
<p>Raw sequencing data and other metadata files are associated with Cuff et al. (2022), available at https://doi.org/10.5281/zenodo.4708418</p> <p>The associated code, files and description pertain to the non-metric multi-dimensional scaling plot presented in this review (Figure 4). The code and data required for the boxplot (Figure 3) are given at the Zenodo link above (for Cuff et al. 2022).</p> <p>Data were collected and processed according to Cuff et al., (2022) up to the point of aggregating the two primer pair datasets. Binary matrices for prey detections were combined for the two primer pairs, but each sample represented separately for each primer pair (i.e., not aggregated by sample). Instances where taxa were only identified to genus (or lower, e.g., family) level by only one of the primer pairs resulted in aggregation for the other primer pair at that taxonomic level, except for species within those groups that were reliably identified to species level by both primers. Samples for which only one primer pair generated prey data were removed. The non-metric multidimensional scaling spider plot was created using ‘metaMDS’ with a Jaccard distance matrix and 999 tries in the ‘vegan’ package (Oksanen et al., 2016). Outliers that obscured the overall patterns were removed, the final plot having a stress of 0.061. Point colours were assigned using the ‘set1’ palette of the ‘RColorBrewer’ package (Neuwirth, 2014) and the final plot created using ‘ggplot2’ (Wickham, 2016).</p>
A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories
<p>Containes input data for MD simulations of 3 HSP90- small compound complexes from the paper</p> <p>A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories" from Daria B. Kokh, Bernd Doser , Stefan Richter , Fabian Ormersbach , Xingyi Cheng, Rebecca C. Wade, publishe in J. Chem. Phys. <strong>153</strong>, 125102 (2020); <a href="https://doi.org/10.1063/5.0019088">https://doi.org/10.1063/5.0019088</a></p> <ul> <li>ref.pdb - structure of the complex in PDB format</li> <li>ref.prmtop - topology file in AMBER</li> <li>ref-equal-NTP.pdb - structure after NTP equilibration </li> <li>ref-equal-NTP.rst7 - coordinates after NTP equilibration</li> <li>ref-equal-NTP.crd - coordinates after NTP equilibration </li> <li>gromacs.gro - coordinates in Gromacs format (after NTP equalibration)</li> <li>gromacs.top - Gromacs topology </li> </ul> <p> </p>
MeV SIMS analysis of irradiation effects on molecular signatures
<p>Characterizing the effect of MeV ion beam irradiation on biological tissues is important for proton beam therapy, which is routinely used as a form of cancer treatment. It is also important for optimizing protocols for multimodal elemental and molecular imaging. Elemental mapping of trace elements in tissues has been carried out for a long time using nuclear microprobe analysis. However, the effect of MeV ion beams on biological samples is largely unexplored. These effects have been explored in Surrey using two mass spectrometry imaging (MSI) techniques – matrix-assisted laser desorption electrospray (MALDI) and desorption electrospray ionization (DESI). The combination of these techniques with ion beam analysis (IBA) presents a few challenges, namely substrate compatibility and de-localization of elemental markers during measurements. As such, MeV-secondary ion mass spectrometry (SIMS) is being explored as an alternative technique for molecular imaging of biological tissues. MeV SIMS, unlike conventional keV SIMS, allows the detection of intact molecules, making it a prime candidate for the molecular analysis of biological samples. This presents an opportunity to benchmark the capabilities of MeV SIMS against established and widely used techniques such as DESI and MALDI. Experiments carried out at Surrey (reported at the ICNMTA 2020) observed that proton beam-induced damage could be mitigated through the application of a MALDI matrix (employed in MALDI as an ionization aid and sample protection). Thus, the role of this matrix is explored in MeV SIMS experiments.</p>
Molecular dynamics simulation based analysis of celecoxib-polymer interactions
<p>This dataset contains scripts and coordinate files for running and analysing molecular dynamics simulations to investigate celecoxib-polymer interactions in aqueous solution. Trajectory files (stripped of water and ions) are included.</p> <p>The associated study is described in:</p> <p>" Comparative analysis of drug-salt-polymer interactions by experiment and molecular simulation improves biopharmaceutical performance", Sumit Mukesh, Goutam Mukherjee, Ridhima Singh, Nathan Steenbuck, Carolina Demidova, Prachi Joshi, Abhay T. Sangamwar, Rebecca C. Wade, submitted.</p>
Structural and Molecular Analysis of Adult Mouse Astrocytes and Vascular Connectivity in the Cortex and Hippocampus
<p>After image acquisition (0-RAW_CL230331_E2_serie1) and deconvolution (1-Deconvolved_CL230331_E2_serie1) using confocal microscopy and the SVI Huygens software,respectively, the image processing was conducted using Imaris, Fiji, and Matlab software. This process involved a sequence of manual operations (2-Imaris_surfaces_CL230331_E2_serie1) and custom Groovy scripts (5-Groovy scripts).</p> <p>The dataset analysis (3-Imaris_final_CL230331_E2_serie1_ims) allowed for a deeper investigation of morphological and molecular properties of adult mouse astrocytes (4-Image analysis_CL230331_E2_serie1) in two brain regions, the Isocortex and the Hippocampus, known to be interconnected to support multiple cognitive functions.</p>
Proteomic analysis reveals different molecular mechanisms to face water deficit in mycorrhizal and nonmycorrhizal sorghum plants
<p>Differential accumulated proteins in response to water deficit in mycorrhizal and nonmycorrhizal sorghum plants were recovered from 2D gels and identified by HPLC-MSMS. MS analysis was performed by a Nano acquity nanoflow LC system (Waters, Milford, MA, USA) coupled to a linear ion trap (LTQ) velos mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) equipped with a nanoelectrospray ion source.</p>
Fig. 2 in The identification of the species of the 'Spilogona contractifrons species-group' and the 'Spilogona nitidicauda species-group' (Diptera, Muscidae) based on morphological and molecular analysis
Fig. 2. Spilogona orthosurstyla Xue & Tian, 1988. A. Terminalia, lateral view. B. Terminalia, dorsal view. C. Sternite 5. Scare bars: 0.25 mm.
Fig. 1 in The identification of the species of the 'Spilogona contractifrons species-group' and the 'Spilogona nitidicauda species-group' (Diptera, Muscidae) based on morphological and molecular analysis
Fig. 1. Males of Spilogona Schnabl, 1911. A–C. Male head and scutum, anterior view. A. S. contractifrons (Zetterstedt, 1838). B. S. arctica (Zetterstedt, 1838). C. S. alticola (Malloch, 1920). D–F. Sternite 5. D. S. contractifrons. E. S. arctica. F. S. alticola. G–I. Abdomen, dorsal view. G. S. contractifrons. H. S. arctica. I. S. alticola. J–L. Terminalia, lateral view. J. S. contractifrons. K. S. arctica. L. S. alticola. Scale bars: 1 mm.
Fig. 5 in The identification of the species of the 'Spilogona contractifrons species-group' and the 'Spilogona nitidicauda species-group' (Diptera, Muscidae) based on morphological and molecular analysis
Fig. 5. Males of Spilogona Schnabl, 1911. A–C. Terminalia, lateral view. A. S. imitatrix (Malloch, 1921). B. S. nitidicauda (Schnabl, 1911). C. S. platyfrons Sorokina, 2018. D–F. Cercal plate, posterior view. D. S. imitatrix. E. S. nitidicauda. F. S. platyfrons. G–I. Sternite 5. G. S. imitatrix. H. S. nitidicauda. I. S. platyfrons. Scale bars: 0.25 mm.
Fig. 6 in The identification of the species of the 'Spilogona contractifrons species-group' and the 'Spilogona nitidicauda species-group' (Diptera, Muscidae) based on morphological and molecular analysis
Fig. 6. Localities of the species of Spilogona Schnabl, 1911 used in the DNA analysis. Symbols denote the species, whilst the colour shows the same DNA sequences. A. 'S. contractifrons species-group'. B. 'S. nitidicauda species-group'.
Fig. 4 in The identification of the species of the 'Spilogona contractifrons species-group' and the 'Spilogona nitidicauda species-group' (Diptera, Muscidae) based on morphological and molecular analysis
Fig. 4. Males of Spilogona Schnabl, 1911. A–C. Head, lateral view. A. S. imitatrix (Malloch, 1921). B. S. nitidicauda (Schnabl, 1911). C. S. platyfrons Sorokina, 2018. D–F. Frons, anterior view. D. S. imitatrix. E. S. nitidicauda. F. S. platyfrons. G–I. Abdomen, dorsal view. G. S. imitatrix. H. S. nitidicauda. I. S. platyfrons. Scale bars: 1 mm.
Analysis of insulin glulisine at the molecular level by X-ray crystallography and biophysical techniques
<p>Raw diffraction images for the study:- Gillis, R.B., Solomon, H.V., Govada, L. <em>et al.</em> Analysis of insulin glulisine at the molecular level by X-ray crystallography and biophysical techniques. <em>Sci Rep</em> <strong>11, </strong>1737 (2021). https://doi.org/10.1038/s41598-021-81251-2 </p> <p>PDB code 6GV0.</p>
FIGURES 34 37. Lamyctes hellyeri n in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 34 37. Lamyctes hellyeri n. sp. QVMAG 23: 23048, female, pretarsus of leg 14, scales 10 m. 34 36, anterior, posterior, and ventral views; 37, detail of lateral pore and ornament on scutes of main claw.
FIGURES 11 17. Lamyctes hellyeri n in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 11 17. Lamyctes hellyeri n. sp. 11, 14 17, QVMAG 23: 23046, female. 11, anterior part of head shield and basal part of antennae, scale 100 m; 14, sensilla on dorsal side of antenna, scale 10 m; 15 16, antennal articles, dorsal side, scales 50 m; 17, cephalic pleurite with Tömösváry organ, scale 50 m. 12 13, QVMAG 23: 23047, female. 12, ventral view of clypeus and labrum, scale 100 m; 13, labral midpiece and inner parts of sidepieces, scale 30 m.
FIGURES 1 4 in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 1 4. Lamyctes coeculus (Brölemann). 1, 3, AM KS 57961, female, Mellong Range, NSW, Australia. 2, 4, MCZ DNA 100472, female, Cerro San Javier, Tucumán, Argentina. 1 2, ventral view of head, scales 100 m; 3 4, dental margin of maxillipede coxosternite, scales 50 m.
FIGURES 18 25. Lamyctes hellyeri n in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 18 25. Lamyctes hellyeri n. sp. QVMAG 23: 23046, female. 18, ventral view of maxillipede, scale 100 m; 19 20, dental margin of maxillipede coxosternite, scales 50 m, 10 m; 21, tarsus and claw of second maxilla, scale 50 m; 22, distal part of tarsus and claw of second maxilla, scale 10 m; 23, coxal projections and telopods of first maxillae, scale 50 m; 24, first maxillae, scale 100 m; 25, plumose setae on inner margins of telopods of first maxillae, scale 10 m.
Figure 5 in A new genus of xenophyophores (Foraminifera) from Japan Trench: morphological description, molecular phylogeny and elemental analysis
Figure 5. Inductively coupled plasma mass spectrometry (ICPMS) values for the composition of the total fragment and different structural parts of Shinkaiya lindsayi gen. et sp. nov. (total fragment), and of the environmental sediment. The mass of elemental aluminium (Al), lead (Pb), magnesium (Mg), uranium (U), barium (Ba), strontium (Sr), and mercury (Hg), per gram of dry material, is shown. A semiquantitative method has been used for Pb, U, and Hg.
Figure 4 in A new genus of xenophyophores (Foraminifera) from Japan Trench: morphological description, molecular phylogeny and elemental analysis
Figure 4. Phylogenetic position of Shinkaiya lindsayi gen et sp. nov. among Foraminifera, based on complete small-subunit ribosomal DNA (SSU rDNA) gene sequences. The tree was obtained using the maximum-likelihood method with the general time-reversible (GTR + G + I) model, with four rates categories, and 1000 replicates for bootstrap analysis. Only bootstrap support values higher than 70% are indicated.
Figure 3 in A new genus of xenophyophores (Foraminifera) from Japan Trench: morphological description, molecular phylogeny and elemental analysis
Figure 3. Shinkaiya lindsayi gen. et sp. nov. A, scanning electron micrograph (SEM) of an open tube, showing its inner surface with many radiolarian tests, a granellare string (right-hand arrow), and a stercomare string (left-hand arrow). B, SEM image of an open stercomare string, containing stercomata (spherical pellets). C, SEM image of the organic sheath of the granellare. D, SEM image showing details of the external surface of the test, with agglutinated material. E, F, transmission electronic microscopy (TEM) images of a stercomare section, showing its wall (W), stercomata (S), and cytoplasm (C). Scale bars: 100 Mm (A), 10 Mm (B–D), 2 Mm (E), 1 Mm (F).
Figure 1 in A new genus of xenophyophores (Foraminifera) from Japan Trench: morphological description, molecular phylogeny and elemental analysis
Figure 1. Schematic representation of the small-subunit ribosomal DNA (SSU rDNA) sequence of Shinkaiya lindsayi gen. et sp. nov., showing the conserved regions, as well as the largest insertion and primers used for DNA amplifications.
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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.