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19,342 results for “Sequence”
Stress measurements for 42 Mw 4.0-5.4 earthquakes during the 2019 Ridgecrest earthquake sequence
<p>The csv file “Ridgecrest_table2_v1.csv” contains measurements of apparent stress, stress parameter, and corner frequency.</p> <p><strong>EvtID</strong>: Earthquake’s Event ID in Southern California Earthquake Data Center (SCEDC, https://scedc.caltech.edu).</p> <p><strong>Mw: </strong>Moment magnitude</p> <p><strong>AST: </strong>Apparent stress measurements in MPa using a time domain algorithm.</p> <p><strong>AST_STD: </strong>Standard deviation of AST in log10 units.</p> <p><strong>ASF: </strong>Apparent stress measurements in MPa using a frequency domain algorithm. Station terms have been corrected.</p> <p><strong>ASF_STD: </strong>Standard deviation of ASF in log10 units.</p> <p><strong>Brune: </strong>Stress parameter or Brune’s stress drop in MPa</p> <p><strong>Brune_STD: </strong>Standard deviation of ASF in log10 units. Note that the uncertainty is estimated using a bootstrap approach.</p> <p><strong>Fc: </strong>Corner frequency of the geometric mean source spectra</p> <p><strong>Fc_STD: </strong>Standard deviation of Fc in log10 units. Note that the uncertainty is estimated using a bootstrap approach.</p> <p><strong>ASF_sub: </strong>Apparent stress measurements in MPa using a frequency domain algorithm. Unlike ASF, only the stations with station terms less than 3 are used. No correction for station terms.</p> <p><strong>ASF_stack: </strong>Apparent stress measurements in MPa using the geometric mean source spectra.</p> <p><strong>Depth: </strong>Centroid depth in km</p> <p><strong>Vs: </strong>S wave velocity at the centroid depth in km/s</p> <p><strong>Density: </strong>Density at the centroid depth in Mg/m<sup>3</sup></p> <p> </p>
Nonlinear methods for dimensionality reduction and clustering of bacterial single-cell sequencing data - intermediate data and figures (MSc thesis)
<p>Data, intermediate results and figures for analyses of my master's thesis in biostatistics at LMU Munich. I took a look on how to use Nonlinear Matrix Decomposition (NMD) (<a href="https://doi.org/10.1137/21M1405769">Saul, L., 2022</a>) in the context of bacterial scRNA-seq analysis (Heumos, L., et. al. 2023), replacing Principal Component Analysis in the optimized workflow, as outlined in Ostner, J. (2024).</p> <p>My thesis was structured along the following objectives:</p> <ul> <li>implement the algorithms from <a href="https://arxiv.org/abs/2305.08687">Seraghiti, G., et. al. (2023)</a> in the Python module <a href="https://github.com/flatironinstitute/nomad/">nomad</a> in cooperation with <a href="https://www.simonsfoundation.org/flatiron/" rel="nofollow">Flatiron Institute</a></li> <li>code for the simulation study of the algorithms in <a href="https://arxiv.org/abs/2305.08687">Seraghiti, G., et. al. (2023)</a> with varying sparsity can be found in <code>/simulation</code></li> <li>apply NMD in the context of the BacSC workflow (<a href="https://www.biorxiv.org/content/10.1101/2024.06.22.600071v1">Ostner, J., et. al. (2024)</a>) on raw and normalized counts (found in <code>/application/analysis</code>), also for manually set number of latent dimensions</li> <li>explore NMD's potential for imputation of <a href="https://www.nature.com/articles/s41467-021-27729-z" rel="nofollow">sampling zeros</a> (check <code>/application/NMD_zero_imputation /</code>)</li> <li>potential of Poisson-Hurdle model-based clustering (<a href="https://academic.oup.com/bioinformatics/article/39/1/btac782/6873739">Qiao, Z., et. al. (2023)</a>) for scRNA-seq (<code>/application/poisson_hurdle</code>).</li> </ul>
Linked collectors and determiners for: A new morphologically cryptic species of Phyllomedusa (Anura: Phyllomedusidae) from Amazonian forests of northern Peru revealed by DNA sequences.
Natural history specimen data linked to collectors and determiners held within, "A new morphologically cryptic species of Phyllomedusa (Anura: Phyllomedusidae) from Amazonian forests of northern Peru revealed by DNA sequences". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/f3b69bf6-f514-486a-ba89-4d7678090239">https://bionomia.net/dataset/f3b69bf6-f514-486a-ba89-4d7678090239</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/f3b69bf6-f514-486a-ba89-4d7678090239">https://gbif.org/dataset/f3b69bf6-f514-486a-ba89-4d7678090239</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Pollen characters and DNA sequence data converge on a monophyletic genus Iresine (Amaranthaceae, Caryophyllales) and help to elucidate its species diversity.
Natural history specimen data linked to collectors and determiners held within, "Pollen characters and DNA sequence data converge on a monophyletic genus Iresine (Amaranthaceae, Caryophyllales) and help to elucidate its species diversity". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a2afe874-9ec7-4101-8f63-da98506a340b">https://bionomia.net/dataset/a2afe874-9ec7-4101-8f63-da98506a340b</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a2afe874-9ec7-4101-8f63-da98506a340b">https://gbif.org/dataset/a2afe874-9ec7-4101-8f63-da98506a340b</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: New species and phylogenetic relationships of the spider genus Coptoprepes using morphological and sequence data (Araneae: Anyphaenidae).
Natural history specimen data linked to collectors and determiners held within, "New species and phylogenetic relationships of the spider genus Coptoprepes using morphological and sequence data (Araneae: Anyphaenidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8ceb6188-a9e2-4687-b929-47e5f380ed70">https://bionomia.net/dataset/8ceb6188-a9e2-4687-b929-47e5f380ed70</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8ceb6188-a9e2-4687-b929-47e5f380ed70">https://gbif.org/dataset/8ceb6188-a9e2-4687-b929-47e5f380ed70</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Combining target enrichment and Sanger sequencing data to clarify the systematics of the diverse Neotropical butterfly subtribe Euptychiina (Nymphalidae, Satyrinae).
Natural history specimen data linked to collectors and determiners held within, "Combining target enrichment and Sanger sequencing data to clarify the systematics of the diverse Neotropical butterfly subtribe Euptychiina (Nymphalidae, Satyrinae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/bfb878f3-8a74-46d3-a104-36485c32aaba">https://bionomia.net/dataset/bfb878f3-8a74-46d3-a104-36485c32aaba</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/bfb878f3-8a74-46d3-a104-36485c32aaba">https://gbif.org/dataset/bfb878f3-8a74-46d3-a104-36485c32aaba</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: A synopsis of Ptisana Murdock ferns (Marattiaceae) in New Caledonia based on sequence data and morphology with the recognition of a new vulnerable species, P. soluta (Compton) Murdock & Perrie, comb. nov., stat. nov..
Natural history specimen data linked to collectors and determiners held within, "A synopsis of Ptisana Murdock ferns (Marattiaceae) in New Caledonia based on sequence data and morphology with the recognition of a new vulnerable species, P. soluta (Compton) Murdock & Perrie, comb. nov., stat. nov.". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/9c423299-73fd-4c27-b497-fa7b98850ed9">https://bionomia.net/dataset/9c423299-73fd-4c27-b497-fa7b98850ed9</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/9c423299-73fd-4c27-b497-fa7b98850ed9">https://gbif.org/dataset/9c423299-73fd-4c27-b497-fa7b98850ed9</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: INSDC Environment Sample Sequences.
Natural history specimen data linked to collectors and determiners held within, "INSDC Environment Sample Sequences". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/583d91fe-bbc0-4b4a-afe1-801f88263016">https://bionomia.net/dataset/583d91fe-bbc0-4b4a-afe1-801f88263016</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/583d91fe-bbc0-4b4a-afe1-801f88263016">https://gbif.org/dataset/583d91fe-bbc0-4b4a-afe1-801f88263016</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: INSDC Sequences.
Natural history specimen data linked to collectors and determiners held within, "INSDC Sequences". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d8cd16ba-bb74-4420-821e-083f2bac17c2">https://bionomia.net/dataset/d8cd16ba-bb74-4420-821e-083f2bac17c2</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d8cd16ba-bb74-4420-821e-083f2bac17c2">https://gbif.org/dataset/d8cd16ba-bb74-4420-821e-083f2bac17c2</a>. Formatted as a Frictionless Data package.
A scalable CRISPR-Cas9 gene editing system facilitates CRISPR screens in the malaria parasite Plasmodium berghei - sequencing data
<p>This holds raw sequencing data, and extracted sgRNA counts </p>
Deep learning model for characterizing protein-RNA interactions from sequence at single-base resolution
<p> </p> <p><a href="https://zenodo.org/api/records/14021440/draft/files/encode_eclip.h5/content" target="_blank" rel="noopener noreferrer">encode_eclip.h5</a> - This file contains the training, validation, and test data for the Reformer model.</p> <p><a href="https://zenodo.org/api/records/14021440/draft/files/encode_eclip_bc.h5/content" target="_blank" rel="noopener noreferrer">encode_eclip_bc.h5</a> - This file contains the training, validation, and test data for the Reformer-BC model.</p> <p><a href="https://zenodo.org/api/records/14027315/draft/files/Reformer-code.zip/content" target="_blank" rel="noopener">Reformer-code.zip</a> - This file contains the training code of Reformer.</p>
AlphaFold2-Based Characterization of Apo and Holo Protein Structures and Conformational Ensembles Using Randomized Alanine Sequence Scanning Adaptation: Capturing Shared Signature Dynamics and Ligand-Induced Conformational Changes
<p>Proteins often exist in multiple conformational states, influenced by the binding of ligands or substrates. The study of these states, particularly the apo (unbound) and holo (ligand-bound) forms, is crucial for understanding protein function, dynamics, and interactions. In the current study, we use AlphaFold2 that combines<span> randomized</span> <span><span> </span>alanine<span> </span>sequence masking<span> </span>with shallow multiple sequence alignment<span> </span>subsampling to expand the conformational diversity of the predicted structural<span> </span>ensembles and<span> </span>capture conformational changes between apo and holo protein forms. Using several well-established datasets of<span> </span>structurally diverse apo-holo protein pairs, the proposed approach </span><span>enables<span> </span>robust predictions of apo and holo structures and conformational ensembles, while also displaying notably similar dynamics distributions. These observations are consistent with<span> </span>the view </span><span> </span>that the intrinsic dynamics of allosteric proteins is defined by the structural topology of the fold and favors conserved conformational motions driven by soft modes among orthologs. We also found<span> </span>a significant <span>correlation </span>between conformational flexibility and <span> </span>AlphaFold2 metric of statistical significance pLDDT for the apo-holo pairs in which ligand binding induced local moderate conformational changes. For apo-holo pairs exhibiting larger structural changes, this relationship<span> </span>becomes nonlinear, reflecting inability of AlphaFold2 confidence metrics to identify high energy functional conformations. Our findings support the notion that AlphaFold2 approaches can yield reasonable accuracy in predicting minor conformational adjustments between apo and holo states, especially for proteins with <span> </span>moderate localized changes upon ligand binding. However, for large, hinge-like domain movements, AF2 tends to predict the most stable domain orientation which is typically the apo form rather than the full range of functional conformations characteristic of the holo ensemble. These results indicate that modeling of multiple functional states of proteins may require more accurate detection of flexible region conformations and cannot solely rely on the pLDDT metric as the major determinant of the prediction accuracy in reproducing functional conformational ensembles.<span> </span></p>
Sequence-dependent activity and compartmentalization of foreign DNA in a eukaryotic nucleus
<p>In eukaryotes, DNA-associated protein complexes co-evolve with genomic sequence to orchestrate chromatin folding. Here, we investigate the relationship between DNA sequence and the spontaneous loading and activity of chromatin components in the absence of co-evolution. Using bacterial genomes integrated into S. cerevisiae, which diverged from yeast 1.5 billion years ago, we show that nucleosomes, cohesins and the transcriptional machinery can lead to the formation of two different chromatin archetypes, one transcribed and the other silent, independently of heterochromatin formation. These two archetypes also form on eukaryotic exogenous sequences, depend on sequence composition, and can be predicted using neural networks trained on the native genome. They do not mix in the nucleus, leading to a bipartite nuclear compartmentalization, reminiscent of the organization of vertebrate nuclei. </p> <p> </p>
Redefining the clade Spirale of the genus Trichoderma by re-analyses of marker sequences and the description of new species
<p>Alingnments used to build the phylogenetic trees shown in the manuscript.</p> <p>Antagonism - data on antagonism of Trichoderma species against plant pathogens.</p> <p>Clade comparisons - data used to build Fig S6.</p>
Table 1 in First insights into past biodiversity of giraffes based on mitochondrial sequences from museum specimens
<p><b>Table 1.</b> Currently accepted giraffe subspecies (Muller <i>et al.</i> 2018) with their synonyms (modified after Shorrocks 2016).</p><table><tbody><tr><th><b>Subspecies</b></th><th><b>Description</b></th><th><b>Type specimen</b></th><th><b>Type locality</b></th><th><b>Synonyms</b></th></tr></tbody><tbody><tr><th><i>camelopardalis</i></th><td>Linnaeus 1758</td><td>Living giraffe illustrated by Belon du Mans (1553), never deposited in a museum collection.</td><td>Sennar (Sudan) and Ethiopia</td><td><i>Camelopardalis biturigum</i> Duvernoy, 1844 <i>Camelopardalis aethiopica</i> Ogilby, 1837 <i>Giraffa camelopardalis typica</i> Bryden, 1899</td></tr><tr><th><i>giraffa</i></th><td>Boddaert 1784</td><td>Specimens of the Prince of Orange Museum (The Hague) and of Vosmaer (1787) (Museum Leiden), Netherlands.</td><td>Cape of Good Hope, South Africa</td><td><i>Camelopardalis</i> <i>capensis</i> Lesson, 1842 <i>Camelopardalis</i> <i>australis</i> Swainson, 1835 <i>Camelopardalis maculata</i> Weinland, 1863 <i>Giraffa camelopardalis wardi</i> Lydekker, 1904</td></tr><tr><th><i>antiquorum</i></th><td>Jardine 1835</td><td>SMF-498: unspec. type and SMF-497: paratype</td><td>South of Darfour, Sudan</td><td><i>Giraffa camelopardalis senaariensis</i> Trouessart, 1898 <i>Giraffa camelopardalis congoensis</i> Lydekker, 1903</td></tr><tr><th><i>peralta</i></th><td>Thomas 1898</td><td>NHMUK-1898.2.18.1</td><td>Lokoja junction Niger and Benue rivers, Nigeria</td><td>–</td></tr><tr><th><i>tippelskirchi</i></th><td>Matschie 1898</td><td>ZMB-084951 (syntype); second specimen might be considered lost</td><td>Lake Eyasi, Tanzania</td><td><i>Giraffa schillingsi</i> Matschie, 1898</td></tr><tr><th><i>reticulata</i></th><td>de Winton 1899</td><td>NHMUK-18971.30.1</td><td>Loroghi Mountains, Kenya</td><td><i>Giraffa hagenbecki</i> Knottnerus-Meyer, 1910 <i>Giraffa reticulata nigrescens</i> Lydekker, 1911 <i>Giraffa camelopardalis australis</i> Rhoads, 1896</td></tr><tr><th><i>rothschildi</i></th><td>Lydekker 1903</td><td>NHMUK-1903.4.15.1</td><td>Guasin-gisha Plateau east of Mount Elgon, Kenya</td><td><i>Giraffa camelopardalis cottoni</i> Lydekker, 1904</td></tr><tr><th><i>angolensis</i></th><td>Lydekker 1903</td><td>NHMUK- 1939.480</td><td>Cunene River, Angola</td><td><i>Giraffa camelopardalis infumata</i> Noack, 1908</td></tr><tr><th><i>thornicrofti</i></th><td>Lydekker 1911</td><td>NHMUK-1910.10.17.1</td><td>Petauke district, Zambia</td><td>–</td></tr></tbody></table>
Data from: Koe: Web-based software to classify acoustic units and analyse sequence structure in animal vocalisations
<p>1. Classifying acoustic units is often a key step in studying repertoires and sequence structure in animal communication. Manual classification by eye and ear remains the primary method, but new tools and techniques are urgently needed to expedite the process for large, diverse datasets.</p> <p>2. Here we introduce <i>Koe</i>, an application for classifying and analysing animal vocalisations. <i>Koe</i> offers bulk-labelling of units via interactive ordination plots and unit tables, as well as visualisation and playback, segmentation, measurement, data filtering/exporting and new tools for analysing repertoire and sequence structure—in an integrated environment.</p> <p>3. We demonstrate <i>Koe</i> with a real-world case study of New Zealand bellbird <i>Anthornis melanura</i> songs from an archipelago metapopulation. Having classified 21,500 units in <i>Koe</i>, we compare repertoires and sequence structure between sites and sexes.</p> <p>4. <i>Koe</i> is web-based (koe.io.ac.nz) and easy to use, making it ideal for collaboration, education and citizen science. By enabling large-scale, high-resolution classification and analysis of animal vocalisations, <i>Koe</i> expands the possibilities for bioacoustics research.</p>
Code and data associated with Christiansen et al. 2021 "Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing"
<p>All code and data input and output files (except reference genome and raw sequencing data) needed to reproduce the results of Christiansen et al. 2021 as released on <a href="https://github.com/notothen/radpilot">https://github.com/notothen/radpilot</a> alongside journal publication. See published paper:</p> <p>Christiansen, H., Heindler, F.M., Hellemans, B. <em>et al.</em> Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing. <em>BMC Genomics</em> <strong>22, </strong>625 (2021). <a href="https://doi.org/10.1186/s12864-021-07917-3">https://doi.org/10.1186/s12864-021-07917-3</a></p>
Accurate annotation of protein coding sequences with IDTAXA - Training Data
<p>Training data used to test IDTAXA, HMMER, and BLAST performance of classification of amino acid and nucleotide sequences.</p>
Accurate annotation of protein coding sequences with IDTAXA - classification results
<p>Raw classification results generated by IDTAXA, BLAST, and HMMER on a training set scraped from KEGG of > 1.5M sequences. HMMER and BLAST results are also converted into IDTAXA like objects for ease of comparison.</p>
Generation of transcriptional novelty by transposable element insertions in Arabidopsis, RNAseq Control Condition Sequencing Data
<p><strong>Arabidopsis stranded 150 bp paired end RNA sequencing data (Illumina) of plants that were grown under control conditions for the manuscript "Generation of transcriptional novelty by transposable element insertions in Arabidopsis"</strong></p> <p><strong><strong>Plant growth conditions</strong></strong></p> <p>Sequenced F4 seeds were sterilized for 10 minutes in 10% bleach, rinsed, and stratified at 4°C for four days in the dark before being sown on 0.5x Murashige & Skoog media (Du<em>schefa cat# M0222</em>) and transferred to growth chambers under long day conditions (16h of light at 24°C followed by 8h of darkness at 21°C; 20 seeds per plate, 6 replicate plates). Ten days after sowing, plants were subjected to 6°C for 24 hours and control plants were returned to normal long day growing conditions for 24 hours before harvesting (3 replicate plates per condition).</p> <p><strong><strong>RNA extraction and sequencing</strong></strong></p> <p>Seedlings were harvested and RNA extractions were done on pools of 5 plants. RNA extractions were performed for 3 biological replicate samples for each line in each condition (n=96) using the Macherey-Nagel NucleoSpin RNA kit (cat# 740955.50). Samples were sent to Novogene for Illumina 150bp paired-end sequencing using a stranded poly-A library.</p> <p><strong>RNAseq sample descriptions of the plants grown under control conditions</strong></p> <p>wt_control: wild-type plants.</p> <p>wtHS_control: wild-type plants that have been submitted to heat stress in a previous generation.</p> <p>wtAZ_control: wild-type plants that have been submitted to epigenetic drug treatments (alpha-amanitin and zebularine) in a previous generation.</p> <p>htLine#: plants carrying additional <em>ONSEN</em> transposable element insertions.</p> <p>Files description: Forward and reverse strand RNA seq data are combined in one file. The numbering at the end ("_1") denominates the biological replicate number.</p>
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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.