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1,199 results for “Alignement”
Cephalopod retinal development shows vertebrate-like mechanisms of neurogenesis: Multiple sequence alignments and phylogenetic trees
<p>Coleoid cephalopods, including squid, cuttlefish and octopus, have large and complex nervous systems and camera-type eyes that are comparable only to features that have independently evolved in the vertebrate lineage. The changes in development that result in the evolution of nervous system size and diversity of neural cell-types are not well understood. Here, we have pioneered live-imaging techniques and performed functional interrogation to show the squid, <em>Doryteuthis</em> <em>pealeii</em>, utilizes mechanisms during retinal neurogenesis that are hallmarks of vertebrate processes. Given the convergent evolution of elaborate visual systems in cephalopods and vertebrates, these results reveal common mechanisms that underlie the growth of highly proliferative neurogenic primordia that may alter ontogenetic allometry and contribute to the evolution of complex nervous systems.</p>
Supplementary Alignment Files from: A re-assessment of diversity among Philippine gymnures (Mammalia: Erinaceidae: Podogymnura), with a new species from Eastern Mindanao
<p>This dataset upload contains two sequence alignment files used in the phylogenetic analysis of <em>Podogymnura</em> from eastern Mindanao, Philippines. One sequence alignment file contains the complete annotated sequence alignment of CYTB and 12S rRNA, including alignment-ambiguous positions, aligned according to the secondary structure model for mammalian 12S rRNA by Springer & Douzery (1996). The second sequence alignment file contains the concatenated sequence alignment after alignment-ambiguous positions were removed, which was used in the phylogenetic analysis.</p>
Data for: Alignments of chloroplast DNA and ITS of tribe Adonideae
<p><span>The Euro-Siberian steppe flora consists of warm- and cold-adapted species, which may have responded differently to Pleistocene glacials and interglacials. Genotyping-by-sequencing individuals from across the distribution range of the pheasant's eye (<em>Adonis vernalis</em>), we aimed to gain insight into steppe florogenesis based on the species' evolutionary history. Although the primary area of origin of the species group comprising <em>A. vernalis</em>, <em>A. villosa</em> and <em>A. volgensis</em> is in Asia, our results indicate that <em>A. vernalis</em> itself is not of Asian origin but evolved in southern (incl. Southeastern) Europe during the Pleistocene, with Spanish populations being clearly genetically distinct<a> </a></span><span>from the Southeastern European populations. We inferred<a> </a></span><span>that <em>A. vernalis</em> migrated eastwards from the sub-Mediterranean forest-steppes of Southeastern Europe into the continental forest-steppe zone. Eastern European populations</span><span> had the highest private allelic richness, indicating long-term large population sizes in this region. As a thermophilic species, <em>A. vernalis</em> seems unlikely to have survived in the cold deserts of the Last Glacial Maximum in Western Siberia, so this region was likely</span><span> (re)colonized postglacially. Overall, our results reinforce the importance of identifying the area of origin and the corresponding ecological requirements of steppe plants in order to understand the composition of today's steppe flora.</span></p>
Dataset of Simulation of Dawn-to-Dusk Electric Field in the Jovian Inner Magnetosphere via Region 2-like Field-Aligned Current
<p>This dataset contains the input parameters and the simulated results used for figures in the paper "Simulation of Dawn-to-Dusk Electric Field in the Jovian Inner Magnetosphere via Region 2-like Field-Aligned Current" by Y. Nakamura, K. Terada, C. Tao, N. Terada, Y. Kasaba, F. Leblanc, H. Kita, A. Nakamizo, A. Yoshikawa, S. Ohtani, F. Tsuchiya, M. Kagitani, T. Sakanoi, G. Murakami, K. Yoshioka, T. Kimura, A. Yamazaki, and I. Yoshikawa.</p> <p>Detailed informations about the data files can be found in "README.txt".</p>
LJ Speech - Aligned IPA transcriptions
<p>Files:</p> <ul> <li> <p><code>grids.zip</code></p> <ul> <li>contains TextGrids for all audio files containing three tiers <code>words</code>, <code>phonemes</code> and <code>transcription</code> <ul> <li><code>words</code> contains the aligned normalized English words</li> <li><code>phonemes</code> contains IPA pronunciations transcribed using CMU dictionary which then were aligned with Montreal Forced Aligner. The pronunciations were then mapped from ARPAbet to IPA and duration marks were applied (without punctuation)</li> <li><code>transcription</code> contains unaligned phonemes including punctuation and word boundary labels (SIL0)</li> </ul> </li> </ul> </li> <li> <p><code>preview.png</code></p> <ul> <li>preview of the first TextGrid opened in Praat</li> </ul> </li> <li> <p><code>words-vocabulary.txt</code></p> <ul> <li>contains all words from tier <code>words</code></li> </ul> </li> <li> <p><code>phonemes-vocabulary.txt</code></p> <ul> <li>contains all phonemes from tier <code>phonemes</code></li> </ul> </li> <li> <p><code>transcription-vocabulary.txt</code></p> <ul> <li>contains all phonemes/punctuation from tier <code>transcription</code></li> </ul> </li> <li> <p><code>phonemes-durations.pdf</code></p> <ul> <li>contains the plotted phoneme duration distribution of tier <code>phonemes</code></li> </ul> </li> <li> <p><code>phonemes-durations-simple.pdf</code></p> <ul> <li>contains the plotted phoneme duration distribution of tier <code>phonemes</code> if all duration markers are ignored</li> </ul> </li> <li> <p><code>pronunciations.dict</code></p> <ul> <li>contains the pronunciations for each word including punctuation and weights (occurrence)</li> </ul> </li> <li> <p><code>script.sh</code></p> <ul> <li>contains the script to reproduce all results</li> </ul> </li> </ul> <p>Phoneme duration marker:</p> <ul> <li><code>˘</code> -> [0, 20) percentile</li> <li><code>ˑ</code> -> [80, 90) percentile</li> <li><code>ː</code> -> [90, inf) percentile</li> </ul> <p>Silence marker:</p> <ul> <li><code>SIL0</code> -> no silence</li> <li><code>SIL1</code> -> [0, 33.33) percentile</li> <li><code>SIL2</code> -> [33.33, 66.66) percentile</li> <li><code>SIL3</code> -> [66.66, inf) percentile</li> </ul> <p> </p>
Alignment used for voltage gated ion channels phylogenetic analysis
<p>Alignment (performed with MAFFT) of sequences of voltage gated ion channels used to performe the phylogenetic analysis (PhyML SMS option) present in the supplementary figures.</p>
Real-time Alignments for Predicting Decision-Making Time for Diagnostics over NGS Cycles
<p>Input datasets for an interpretable learning approach to predict decision-making time for diagnostics over NGS cycles. The dataset contains alignment files of two clinical sputum samples sequenced with an Illumina MiSeq sequencing device, and following a real-time sequencing protocol.</p> <p>The datasets consist of real-time alignment files for specific sequencing cycle intervals. The alignment has been performed to a database of respiratory microbes. Data preprocessing, including the removal of human host DNA, is integrated into the real-time alignment approach that has been applied to generate the alignments.</p>
Data: Large old trees increase growth under shifting climatic constraints: Aligning tree longevity and individual growth dynamics in primary mountain spruce forests
<p>In a world of accelerating changes in environmental conditions driving tree growth, tradeoffs between tree growth rate and longevity could curtail the abundance of large, old trees (LOTs), with potentially dire consequences for biodiversity and carbon storage. However, the influence of tree-level tradeoffs on forest structure at landscape scales will also depend on disturbances, which shape tree size and age distribution, and on whether LOTs can benefit from improved growing conditions due to climate warming.</p> <p>We analyzed temporal and spatial variation in radial growth patterns from ~5000 Norway spruce (<em>Picea abies </em>(L.) H. Karst) live and dead trees from the Western Carpathian primary spruce forest stands. We applied mixed-linear modeling to quantify the importance of LOT growth histories and stand dynamics (i.e. competition and disturbance factors) on lifespan. Finally, we assessed regional synchronization in radial growth variability over the 20<sup>th</sup> century, and modelled the effects of stand dynamics and climate on LOTs recent growth trends.</p> <p>Tree age varied considerably among forest stands, implying an important role of disturbance as an age constraint. Slow juvenile growth and longer period of suppressed growth prolonged tree lifespan, while increasing disturbance severity and shorter time since last disturbance decreased it. The highest age was not achieved only by trees with continuous slow growth, but those with slow juvenile growth followed by subsequent growth releases. Growth trend analysis demonstrated an increase in absolute growth rates in response to climate warming, with late summer temperatures driving the recent growth trend. Contrary to our expectation that LOTs would eventually exhibit declining growth rates, the oldest LOTs (>400 years) continuously increase growth throughout their lives, indicating a high phenotypic plasticity of LOTs for increasing biomass, and a strong carbon sink role of primary spruce forests under rising temperatures, intensifying droughts, and increasing bark beetle outbreaks.</p>
Aligned and curated mtDNA sequences from: Ancient DNA of narrow-headed voles reveals common features of the Late Pleistocene population dynamics in cold-adapted small mammals
<p><span>Narrow-headed vole, together with collared lemming and common vole, was the most abundant small mammal species across Eurasian Late Pleistocene steppe-tundra environments. Previous ancient DNA studies of </span><span>the latter</span><span> </span><span>two</span><span> revealed dynamic past population histories shaped by climatic fluctuations. To investigate the extent to which species with similar adaptations share common evolutionary </span><span>histories,</span><span> we generated a dataset comprising mitochondrial genomes of 139 ancient and 6 modern narrow-headed voles from multiple sites across Europe and north-</span><span>western</span><span> Asia and covering the last ca. 100 thousand years (ka). We inferred Bayesian time-aware phylogenies using 11 </span><span>radiocarbon-dated</span><span> samples for calibration of the molecular clock. We found that across the three </span><span>species,</span><span> divergence of the main mtDNA lineages occurred during Marine Isotope Stages (MIS) 7 and MIS 5, suggesting a common response </span><span>of species adapted to open habitat to the interglacial environments. </span><span>In European narrow-headed voles, we identified multiple </span><span>time-structured</span><span> mtDNA lineages, implying lineage turnovers. Timing of some of these turnovers was synchronous across all three </span><span>species,</span><span> allowing us to identify the main drivers of the Late Pleistocene dynamics of steppe- and cold-adapted species.</span></p>
Aligned DNA sequence matrix for phylogenetic analyses in the article "A new species of spiny-backed tree frog, genus Osteocephalus (Anura: Hylidae), from the Yanachaga Chemillén National Park in central Peru"
<p>Aligned DNA sequence matrix for phylogenetic analyses of the article "Systematics of Huicundomantis, a new subgenus of Pristimantis (Anura, Strabomantidae) with extraordinary cryptic diversity and eleven new species"</p> <p>The matrix is in NEXUS format and has 14791 bp and 38 terminals.</p> <p>Partitions are as follows:</p> <p>charset 12S_16S = 1-2442;<br> charset mtGenome_other_genes = 2443-9180; charset nonCoding = 3132- 3138 4776- 4857 5203- 5214;<br> charset codonPos1 = 2443-3130\3 3139-4774\3 4858-5200\3 5215-9178\3;<br> charset codonPos2 = 2444-3131\3 3140-4775\3 4859-5201\3 5216-9179\3;<br> charset codonPos3 = 2445-3129\3 3141-4773\3 4860-5202\3 5217-9180\3;<br> charset 16S_ND1nonCoding = 9181- 9428 10390- 10506 ;<br> charset 16S_ND1codonPos1 = 9429-10389\3;<br> charset 16S_ND1codonPos2 = 9430-10387\3;<br> charset 16S_ND1codonPos3 = 9431-10388\3;<br> charset POMCcodonPos1 = 10507-11068\3;<br> charset POMCcodonPos2 = 10508-11066\3;<br> charset POMCcodonPos3 = 10509-11067\3;<br> charset CO1codonPos1 = 11069-12608\3;<br> charset CO1codonPos2 = 11070-12609\3;<br> charset CO1codonPos3 = 11071-12610\3;<br> charset CytbcodonPos1 = 12611-13757\3;<br> charset CytbcodonPos2 = 12612-13758\3;<br> charset CytbcodonPos3 = 12613-13759\3;<br> charset ND2codonPos1 = 13760-14789\3;<br> charset ND2codonPos2 = 13761-14790\3;<br> charset ND2codonPos3 = 13762-14791\3;</p>
SKOS Datasets for Aligning INSEE Concepts
<p>This is the list of datasets used for the alignments of INSEE concepts.</p> <p>The Github repository at https://github.com/MondecaLabs/INSEE-Alignment presents the procedure and the results</p>
Multiple sequence alignments of newly reconstructed and published cervid and human mtDNA
<p><span>Assigning prehistoric objects to specific individuals is usually impossible outside of burial contexts. Here we present a non-destructive method for gradually releasing DNA from ancient bone and tooth artifacts. Application of the method to an Upper Paleolithic deer tooth pendant from Denisova Cave (Russia) resulted in the recovery of DNA from both the deer and a female human individual. Genetic dates obtained from the deer and human mitochondrial genomes estimate the age of the pendant at approximately 20,000 to 24,000 years. Nuclear DNA from its presumed maker or wearer shows strong affinities to contemporaneous Ancient North Eurasian individuals previously found further east in Siberia. Our work opens up new possibilities for linking cultural and genetic records in prehistoric archaeology.</span></p>
Data and code for "Cell shape characterization, alignment and comparison using FlowShape"
<p><strong>Code</strong></p> <p>This folder contains a snapshot of the FlowShape Python package at the time of paper submission. The latest version is available at: <a href="https://bitbucket.org/pgmsembryogenesis/flowshape/src/main/">https://bitbucket.org/pgmsembryogenesis/flowshape/src/main/</a></p> <p><strong>Data</strong></p> <p>Contain 3D meshes of <em>C. elegans</em> early embryo cells, in Wavefront .obj format. Each filename has three parts sepparated by underscores</p> <ul> <li>Embryo identifier</li> <li>Cell name</li> <li>Timestep For example: <code>wt13_ABar_18</code> Embryo = wt13 Cell = ABar Timestep = 18</li> </ul> <p>The timesteps are frames from the original timelapse, where one frame corresponds to 90 seconds. The starting point is arbitrary, so time is aligned by EMS division.</p> <p>Embryo labels:</p> <ul> <li><code>7cell01-7cell07</code>: 7 wild-type embryos imaged only around the seven-cell stage.</li> <li><code>wt01-wt19</code>: 19 wild-type embryos imaged for a longer time.</li> <li><code>dshmig01-dshmig05</code>: 5 dsh-2 / mig-5 RNAi knockdown embryos, imaged around seven-cell stage.</li> </ul> <p><code>cell_filters.csv</code> is a CSV file containing identifiers of embryos left out of the analysis because of automatically detected errors. Further, wt06 was also left out because of problems with labeling the cells.</p> <p><strong>Images</strong></p> <p>Contains raw microscopy data that was used to generate the meshes. <code>resolution.csv</code> contains a list of Z, Y and X resolutions (micron / pixel).</p> <p><strong>Changelog</strong></p> <p>0.1.0</p> <ul> <li>Initial upload</li> </ul> <p>0.2.0</p> <ul> <li>Added microscopy images.</li> <li>Removed cells 6 and 7 from dsh-2 / mig-5 dataset, which were not supposed to be included there.</li> <li>Removed Python cache files.</li> </ul>
Phylogenetic alignments and trees (16S, COI, 16S+COI) of Haploniscidae (Crustacea: Isopoda) from the Northwest Pacific Ocean
<p>The role of geomorphological features as drivers for benthic deep-sea biodiversity remains poorly understood. By disentangling the putative <em>Haploniscus belyaevi </em>Birstein, 1963 species complex from the abysso-hadal Kuril-Kamchatka Trench (KKT) region in the Northwest Pacific Ocean, we aim to shed light on deep-sea differentiation and how it is related to potential bathymetric barriers such as the KKT and the Kuril-Island Ridge (KIR). Our integrative taxonomic approach featured morphological and molecular delimitation methods, also considering the post-marsupial development due to pronounced sexual dimorphism. Mitochondrial 16S and COI markers were sequenced and several molecular species delimitation methods were applied. By combining the different results we were able to delineate six distinct species within the <em>belyaevi </em>complex, including several morphologically cryptic species, and found hints of three additional species groups in the complex. Even though several of these species were distributed across the KKT and/or KIR, limited gene flow and depth-differentiation were indicated supporting previous notions that these geomorphological features play a role in deep-sea benthos speciation.</p> <p>These files comprise the 16S, COI and 16S+COI alignments of these analyses and their phylogenetic trees as calculated by IQTree.</p>
L-ins-i alignment and RAxML inference of Anthracoidea umbrosae sp. nov.
<p>The files contain the L-ins-i alignment of LSU sequences and the RAxML phylogeny of species in the genus Anthracoidea. Based on these a new species (A. umbrosae) of these plant parasitic fungi is proposed</p>
Source data for VALIS: Virtual Alignment of pathoLogy Image Series for multi-gigapixel whole slide images publication
<p>Source data used to create figures in <em>VALIS: Virtual Alignment of pathoLogy Image Series for multi-gigapixel whole slide images</em> (Nature Communications, 2023)</p>
GTN Tutorial: Cancer alignment
<p>Data belonging to the GTN tutorial on cancer alignment. This tutorial is based on the Bioinformatics.ca cancer workshop</p>
CSV Dataset Files and JSON OpenRefine Recipes for Alignment of the Schoenberg Dataset of Manuscripts (SDBM) Name Authority with Wikidata
<p>Dataset CSVs and JSON recipe files for OpenRefine for a project to align Name Authority records in the Schoenberg Dataset of Manuscripts (SDBM) with Wikidata Items</p>
Dataset of ``Plasma Distribution Solver: A Model for Field-Aligned Plasma Profiles Based on Spatial Variation of Velocity Distribution Functions"
<p>This dataset contains the plasma distribution data in the Jupiter–Io system, calculated from the Plasma Distribution Solver and used for figures in the paper “Plasma Distribution Solver: A model for field-aligned plasma profiles based on spatial variation of velocity distribution functions” by K. Saito et al. (2023).</p> <p> </p> <p>The contents of files ‘all_Case_1.csv’ and ‘all_Case_2.csv’ are as follows:</p> <ul> <li>Position along the magnetic field line (0 at the magnetic equator) [m] (column 1)</li> <li>Distance from the Jovian center [km] (column 2)</li> <li>Magnetic latitude [rad]([degree]) (column 3(4))</li> <li>Magnetic flux density [T] (column 5)</li> <li>The initial condition of electrostatic potential [V] (column 6)</li> <li>The result of electrostatic potential [V] (column 7)</li> <li>Number density profiles [m<sup>-3</sup>] (columns 8-17)</li> <li>Charge density profiles obtained from the integration of velocity distribution functions [C m<sup>-3</sup>] (column 18)</li> <li>Charge density profiles obtained from Poisson’s equation [C m<sup>-3</sup>] (column 19)</li> <li>Convergence value (column 20)</li> <li>Particle flux density [m<sup>-2</sup> s<sup>-1</sup>] (columns 21-30)</li> <li>Mean flow velocity parallel to the field line [m s<sup>-1</sup>] (columns 31-40)</li> <li>Plasma pressure perpendicular to the field line [Pa] (columns 41-50)</li> <li>Plasma pressure parallel to the field line [Pa] (columns 51-60)</li> <li>Plasma dynamic pressure [Pa] (columns 61-70)</li> <li>Perpendicular temperature [J] (columns 71-80)</li> <li>Parallel temperature [J] (columns 81-90)</li> <li>Alfvén speed considering the displacement current term in Ampère’s law [m s<sup>-1</sup>] (column 91)</li> <li>Alfvén speed per the speed of light (column 92)</li> <li>Ion inertial length using averaged mass [m] (column 93)</li> <li>Electron inertial length [m] (column 94)</li> <li>Ion Larmor radius using averaged mass [m] (column 95)</li> <li>Ion acoustic gyroradius using averaged mass [m] (column 96)</li> <li>Electron Larmor radius [m] (column 97)</li> <li>Current density [A m<sup>-2</sup>] (column 98)</li> </ul> <p>The Python codes ‘plot_all.py,’ ‘plot_plasma_beta_comparison.py,’ and ‘plot_Alfven_speed_comparison.py’ can plot Figures 5, 6, 7, and 9 of the paper using the above CSV files.</p> <p> </p> <p>The files ‘boundary_conditions_Case_1.csv’ and ‘boundary_conditions_Case_2.csv’ contain the boundary conditions for Cases 1 and 2.</p> <p> </p> <p>The zip files ‘probability_density_function_Case_1_H_Io.zip’ and ‘probability_density_function_Case_1_H_Jupiter_North.zip’ are zipped CSV files with the same name. The contents of these files are as follows:</p> <ul> <li>Magnetic latitude [degree] (column 1)</li> <li>Perpendicular velocity at the particle position [m s<sup>-1</sup>] (column 2)</li> <li>Parallel velocity at the particle position [m s<sup>-1</sup>] (column 3)</li> <li>Perpendicular velocity at the boundary [m s<sup>-1</sup>] (column 4)</li> <li>Parallel velocity at the boundary [m s<sup>-1</sup>] (column 5)</li> <li>Probability density function [s<sup>3</sup> m<sup>-3</sup>] (column 6)</li> <li>Differential flux per number density [cm<sup>-2</sup> s<sup>-1</sup> sr<sup>-1</sup> keV<sup>-1</sup>] (column 7)</li> </ul> <p>The Python code ‘plot_velocity_distribution_function.py’ can plot Figure 8 of the paper using this CSV file.</p>
Aligning the percepts and concepts from a brief glance
<p>23/06/2023 Qualia Structure Meeting presentation: Aligning the percepts and concepts from a brief glance</p> <p>YouTube video: <a href="https://youtu.be/juK5huqGlCA">https://youtu.be/juK5huqGlCA</a></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
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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.