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1,199 results for “Alignement”
Supplementary collection of preprocessed and analysed data objects for the paper: "Gene-level alignment of single cell trajectories"
<p>Supplementary collection of h5ad data files containing preprocessed and analysed single-cell reference and query datasets discussed in the case studies of the paper:<em><strong>"Gene-level alignment of single cell trajectories"</strong></em> (<a href="https://doi.org/10.1101/2023.03.08.531713" rel="nofollow">https://doi.org/10.1101/2023.03.08.531713</a>).</p> <p>Our artificial thymic organoid raw sequencing data are available from ArrayExpress (E-MTAB-12720).</p> <p>Below lists the original sources of the literature datasets we downloaded prior to our own preprocessing and trajectory analysis.</p> <ul> <li> <p>Original pan fetal reference data from: Suo, C. et al. (2022) "Mapping the developing human immune system across organs" (<a href="https://doi.org/10.1126/science.abo0510">https://doi.org/10.1126/science.abo0510</a><a href="http://paperpile.com/b/XTpgLG/TQtQ3">), </a>downloaded from <a href="https://developmental.cellatlas.io/fetal-immune">https://developmental.cellatlas.io/fetal-immune</a>.</p> </li> </ul> <ul> <li> <p>Original healthy/IPF data from: Adams, T. S. et al. (2020), "Single-cell RNA-seq reveals ectopic and aberrant lung-resident cell populations in idiopathic pulmonary fibrosis" (<a href="https://doi.org/10.1126/sciadv.aba1983">https://doi.org/10.1126/sciadv.aba1983</a>), downloaded from GEO (GSE136831).</p> </li> </ul> <p>We have run our scripts in <a href="https://github.com/Teichlab/G2G_notebooks">https://github.com/Teichlab/G2G_notebooks</a> to generate new latent embeddings and infer pseudotime trajectories for the above datasets, and used them to model trajectory alignments with our newly developed framework: ‘Genes2Genes’ <a href="https://github.com/Teichlab/Genes2Genes">https://github.com/Teichlab/Genes2Genes</a>. </p>
Supporting data for "Collisional alignment and molecular rotation control the chemi-ionization of individual conformers of hydroquinone with metastable neon"
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Alignement results
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Experimental and calulated data for "Dissociative ionization and post-ionization alignment of aligned O<sub>2</sub> in an intense femtosecond laser field"
<h3>raw_expt_data.itx</h3> <p>Raw data for the experimental result (delay dependence of time-of-flight spectra) as an Igor text file.</p> <h3>CTMC_PIA_a.itx, CTMC_PIA_b.itx</h3> <p>Lists of initial conditions (time, internuclear distance, polar angle, azimuth angle and conjugated angular velocities) of all the classical trajectories and results (index, initial polar angle, final polar and azimuth angles) of the dissociation trajectories as Igor text files.</p> <h3>GAMESS.zip</h3> <p>Input and output files for the quantum chemical calculations by GAMESS.</p>
Physiological Characteristics of Neurons in the Mammillary Bodies align with Topographical Organization of Subicular Inputs
<p>Batch data is deposited in cell explorer format</p> <p>Please refer to https://cellexplorer.org/ for additional explanation about the data structure </p> <p>See https://github.com/buzsakilab/buzcode for code </p> <p> </p>
nad1 alignment in Description of three widespread new Peronospora species parasitising Caryophyllales
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COX2/cox2-1 spacer/COX1 alignment in Description of three widespread new Peronospora species parasitising Caryophyllales
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ITS alignment in Description of three widespread new Peronospora species parasitising Caryophyllales
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hsp90 alignment in Description of three widespread new Peronospora species parasitising Caryophyllales
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RPS10 alignment in Description of three widespread new Peronospora species parasitising Caryophyllales
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Example alignment for CRUK-CI RNA-seq course
<p>An alignment file with indices used in our RNA-seq course.<br> It is aligned to chr 1 of mm10 reference genome</p>
Data for the paper "Impacts of multiscale field-aligned currents (FACs) on the ionosphere-thermosphere system: GITM simulation"
<p>This dataset serves for the paper "Impacts of multiscale field-aligned currents (FACs) on the ionosphere-thermosphere system: GITM simulation".</p> <p> The uploaded zip file contains 6 directories, each directory contains 1 CDF file, detailed description for each file are listed as follows:</p> <p><strong>fig1: </strong></p> <p>vars: 'mlt', 'mlat', 'avg_lg', 'std_lg', 'avg_ms', 'std_ms', 'avg_sm', 'std_sm'</p> <p>avg_lg, std_lg: large-scale mean FAC and FAC variability </p> <p>avg_ms, std_ms: meso-scale mean FAC and FAC variability </p> <p>avg_sm, std_sm: small-scale mean FAC and FAC variability </p> <p><strong>fig2: </strong></p> <p>vars: 'mlt', 'mlat', 'avg_lg', 'std_lg', 'avg_ms', 'std_ms', 'avg_sm', 'std_sm'</p> <p>avg_lg, std_lg: Magnitudes of the large-scale mean electric field and electric field variability </p> <p>avg_ms, std_ms: Magnitudes of the meso-scale mean electric field and electric field variability </p> <p>avg_sm, std_sm: Magnitudes of the small-scale mean electric field and electric field variability </p> <p><strong>fig3:</strong></p> <p>vars: 'fac', 'dBy'</p> <p>fac: FAC along the track</p> <p>dBy: East-westward magnetic perturbation along the same track</p> <p><strong>fig4:</strong></p> <p>vars: 'glon', 'glat', 'Emag', 'int_jh'</p> <p>glon, glat: geographic longitude and latitude</p> <p>Emag: electric field magnitude </p> <p>int_jh: height-integrated Joule heating </p> <p><strong>fig6:</strong></p> <p>vars: 'glon', 'glat', 'gitm_evar_lg', 'gitm_evar_ms', 'de2_evar_lg', 'de2_evar_ms'</p> <p>glon, glat: geographic longitude and latitude</p> <p>'gitm_evar_lg', 'gitm_evar_ms': magnitudes of the simulated large-scale and mess-scale electric field variabilities</p> <p>'de2_evar_lg', 'de2_evar_ms': magnitudes of the large-scale and mess-scale electric field variabilities from the data in geographic coordinates</p> <p><strong>fig7:</strong></p> <p>vars: 'glon', 'glat', 'gitm_jh_lg', 'gitm_jh_ms'</p> <p>glon, glat: geographic longitude and latitude</p> <p>'gitm_jh_lg', 'gitm_jh_ms': Increase of the height-integrated JH related to the large- and mess-scale FAC variabilities </p>
Alignment, ML and MCC trees of dataset A from "Reconstruction of the genetic history and the current spread of HIV-1 subtype A in Germany"
<p>-Alignment and phylogeographic MCC tree of 708 HIV subtype A1 sequences called dataset A in the manuscript "Reconstruction of the genetic history and the current spread of HIV-1 subtype A in Germany"</p> <p>-marked up MCC tree showing SDRM in dataset A</p> <p>-marked up ML tree showing transmission cluster selection in dataset A</p>
Fig. 5. Characters distinguishing Selatosomus and Pristilophus. P in Generic Changes for Some Nearctic Prosternini (Coleoptera: Elateridae: Dendrometrinae: Neopristilophus Buysson, 1894 and Pristilophus Latreille, 1834) to Align with Palearctic Concepts
Fig. 5. Characters distinguishing Selatosomus and Pristilophus. P. suckleyi suckleyi, Washington, USA: A) Dorsal habitus, D) Elytra, dorsal view, showing supplemental stria (white arrow) on ninth interval, with intervals labeled. P. festivus: B) Scutellar shield, dorsal view. S. semimetallicus: C) Scutellar shield, dorsal view, E) Elytra, dorsal view, with intervals labeled. Not to scale.
Fig. 4 in Generic Changes for Some Nearctic Prosternini (Coleoptera: Elateridae: Dendrometrinae: Neopristilophus Buysson, 1894 and Pristilophus Latreille, 1834) to Align with Palearctic Concepts
Fig. 4. Characters distinguishing Selatosomus and Pristilophus. Last abdominal ventrite: A) S. semimetallicus, B) P. festivus, C) P. funereus, D) P. morulus. Male aedeagus, dorsal view: E) S. aeripennis, after Brown (1935b), F) P. festivus, after Brown (1935a), G) P. funereus, after Brown (1936), H) P. morulus, after Brown (1935a).
Alignment of ITS sequences of Erysiphe specimens from Koelreuteria hosts, with Golovinomyces spp. as outgroup. The scientific names are followed by the respective GenBank accession number.
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Data for the publication "Wind farm layout optimization with alignment constraints", submitted to Wind Energy Science, 2024
<p>The data in pickle format contains the optimal layouts corresponding to the numerical applications of the paper "Wind farm layout optimization with alignment constraints" submitted in Wind Energy Science, 2024.</p>
Halamphora witkowskii alignment and phylogenetic tree
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61 taxa and 2399 loci alignment of phylodiverse Klebsormidiophyceae trimmed gene-wise with clipkit
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FLIR aligned - LLVIP COCO annotations [CAFF-DINO architecture]
<p>Contains the annotations converted in COCO format for : </p> <ul> <li>LLVIP dataset :</li> <li>FLIR-Aligned dataset : </li> </ul> <p>[Used for the CAFF-DINO dev. : <em><strong>CAFF-DINO: Multi-spectral object detection transformers with cross-attention</strong></em><br><em><strong>features fusion, Helvig et al, 2024, CVPR workshop on Perception beyond the visible spectrum]</strong></em></p>
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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.