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2,556 results for “catalogs”
The RNA Atlas expands the catalog of human non-coding RNAs
GEO Series GSE138734. Homo sapiens. 921 samples. Type: Expression profiling by high throughput sequencing.
Comprehensive catalog of dendritically localized mRNA isoforms from sub-cellular sequencing of single mouse neurons
GEO Series GSE115480. Mus musculus. 32 samples. Type: Expression profiling by high throughput sequencing.
Expanding the Catalog of Enhancer Marks In Vivo
GEO Series GSE37151. Mus musculus. 34 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Atlas of pathogen-sensitive myeloid lncRNA networks in humans (SMyLR catalog) [RNA-seq]
GEO Series GSE268547. Homo sapiens. 97 samples. Type: Expression profiling by high throughput sequencing.
Cataloging human PRDM9 variability utilizing long-read sequencing technologies reveals PRDM9 population-specificity and two distinct groupings of related alleles
GEO Series GSE166483. Homo sapiens. 18 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other.
A systems approach delivers a functional microRNA catalog and expanded targets for seizure suppression in temporal lobe epilepsy
GEO Series GSE137473. Rattus norvegicus; Mus musculus. 114 samples. Type: Non-coding RNA profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Catalogs and stress history for "stress dependent b value variations in a heterogeneous rate-and-state fault model"
<p>Catalogs of synthetic seismicity and stress history used in the manuscrit "stress dependent b value variations in a heterogeneous rate-and-state fault model".</p>
Raster files catalog to forest growth simulation performed by r.recovery module (Grass Gis).
<p>This repository contains all publicly available raster files to calibrate/validate the parameters of the Diffusive-logistic growth (DLG) model and generate prognostics by means of the GRASS-GIS module r.recovery (Richit et al., 2019).</p> <p>Three .tiff files are needed for perform calibration/validation: two are EVI raster maps (two time-lapsed conditions of forest density) and a soil use file. In the repository the example files are:</p> <p>Calibration_EVI_2000;</p> <p>Calibration_EVI_2011 and</p> <p>Calibration_soil_use_2000, respectively.</p> <p>The others files in the repository are four EVI .tiff files and their respectively soil use .tiff files that were used to perform simulations by the means of calibrated parameters of the DGL model. The files are:</p> <p>AMNP_EVI_2016 and AMNP_soil_use_2016;</p> <p>FPSP_EVI_2016 and FPSP_soil_use_2016;</p> <p>MDRB_EVI_2016 and MDRB_soil_use_2016;</p> <p>MNPTS_EVI_2016 and MNPTS_soil_use_2016.</p> <p>For more details on r.recovery module please check </p> <p>Richit, L.A., Bonatto, C., da Silva, R.V., Grzybowski, J.M.V., 2019. Prognostics of forest recovery with r.recovery grass-gis module: an open source forest growth simulation model based on the diffusive-logistic equation. Environmental modelling & software 111, 108–120.</p>
Figure 4 in The Diptera of Panama. I. Annotated catalog of the Tipulomorpha of Panama
Figure 4. Accumulation curve for species of crane flies recorded from Panama.
Relocated Earthquake Catalog for Java-Indonesia (April 2009 to November 2018)
<p>Relocated Earthquake Catalog for Java (April 2009 to November 2018). </p> <p>Please refer to:</p> <p>Widiyantoro, S., Gunawan, E., Muhari, A., Rawlinson, N., Mori, J., Hanifa, N.R., Susilo, S., Supendi, P., Shiddiqi, H.A., Nugraha, A. D., Putra, H. E. (2020). Seismic gaps south of Java, Indonesia: Implications for megathrust earthquakes and tsunamis, Scientific Reports, 10, 15274 (2020). https://doi.org/10.1038/s41598-020-72142-z</p>
The Zwicky Transient Facility Catalog of Periodic Variable Stars
<p>The number of known periodic variables has grown rapidly in recent years. Thanks to its large field of view and faint limiting magnitude, the Zwicky Transient Facility (ZTF) offers a unique opportunity to detect variable stars in the northern sky. Here, we exploit ZTF Data Release 2 (DR2) to search for and classify variables down tor ∼ 20.6 mag. We classify 781,602 periodic variables into 11 main types using an improved classification method. Comparison with previously published catalogs shows that 621,702 objects (79.5%) are newly discovered or newly classified, including ∼700 Cepheids, ∼5000 RR Lyrae stars, ∼15,000 δ Scuti variables, ∼350,000 eclipsing binaries,∼100,000 long-period variables, and about 150,000 rotational variables. The typical misclassification rate and period accuracy are on the order of 2% and 99%, respectively. 74% of our variables are located at Galactic latitudes, |b| < 10◦. This large sample of Cepheids, RR Lyrae, δ Scuti stars, and contact (EW-type) eclipsing binaries is helpful to investigate the Galaxy’s disk structure and evolution with an improved completeness, areal coverage, and age resolution. Specifically, the northern warp and the disk’s edge at distances of 15–20 kpc are significantly better covered than previously. Among rotational variables, RS Canum Venaticorum and BY Draconis-type variables can be separated easily. Our knowledge of stellar chromospheric activity would benefit greatly from a statistical analysis of these types of variables.</p> <p>These supplementary materials contain g and r bands single-exposure photometry for 781,602 periodic variables in Table 2 of the paper. </p> <p><br> SourceID is the internal source identifier joins these attachments to Table 2. Example: For variable star ZTFJ000000.19+320847.2 in Table 2, the SourceID=3 is adopted to search corresponding single-exposure information in both 'ztf2g' and ''ztf2r'. </p> <p>File Description:</p> <p>ztf2g g band single exposure photometry data of variables from ZTF2.</p> <p>SourceID, RAdeg, DEdeg, HJD, gmag, e_gmag, g_flag</p> <p>ztf2r r band single exposure photometry data of variables from ZTF2.</p> <p>SourceID, RAdeg, DEdeg, HJD, rmag, e_rmag, r_flag</p> <p>Table2 ZTF Variables Catalog.</p> <p>Table6 ZTF Suspected Variables Catalog.</p>
Synthetic earthquake catalogs generated for "Dual seismic migration velocities in seismic swarms"
<p>Synthetic earthquake catalog for 40 simulations presented in "Dual seismic migration velocities in seismic swarms" by P. Dublanchet and L. De Barros, submitted to Geophysical Research Letters. Each file corresponds to one simulation described in the original paper. The three columns of each file are:</p> <p>-time of earthquake (in s)</p> <p>-location of earthquake (in m)</p> <p>-size of earthquake (in m)</p>
eggNOG Mapper annotations of OM-RGC-v2 gene catalog
<p><a href="https://github.com/eggnogdb/eggnog-mapper">eggNOG-mapper</a> (v2.0.1) annotations of <a href="https://www.ocean-microbiome.org/">Ocean</a> (OM-RGC-v2) gene catalog.</p>
sQTL catalog generated by sqtlseeker2-nf in the GTEx dataset
<p>sQTL catalog generated by <a href="https://github.com/guigolab/sqtlseeker2-nf">sqtlseeker2-nf</a> in the <a href="https://www.gtexportal.org/home/">GTEx</a> dataset, as described in the publication<em> Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome</em> by Garrido-Martín et al. in Nat. Commun. (<a href="https://doi.org/10.1038/s41467-020-20578-2">https://doi.org/10.1038/s41467-020-20578-2</a>). It contains the results of the sqtlseeker2-nf pipeline, run using different input data: i) RSEM transcript quantifications and genotype data from GTEx V7, ii) LeafCutter intron excision ratios and genotype data from GTEx V7 and iii) RSEM transcript quantifications and genotype data from GTEx V8. For each GTEx tissue, it includes summary statistics corresponding to all the tests performed (both nominal and permutation passes) and the significant sQTLs identified.</p> <p> </p>
Data Catalog for: Flux-induced topological superconductivity in full-shell nanowires
<p>Data Catalog for: Flux-induced topological superconductivity in full-shell nanowires</p>
Rotifer World Catalog: Type data & habitat info
Open the record for dataset details and reuse information.
A catalog of genes, genomes and species of the cat (Felis catus) intestinal microbiota
<p></p><h1>Data sources</h1><br>This dataset was constructed using two different bioprojects:<br>PRJNA758898 from Ma et al. 2022. 16 samples from 16 animals.<br>PRJEB9357 from Deusch et al. 2015. 88 samples from 30 animals.<br>PRJEB4391 from Deusch et al. 2014. 36 samples from 18 animals.<br>PRJNA944553. 30 samples from 30 animals.<br>PRJNA908260 from Bai et al. 2023. 8 samples from 8 animals.<br>PRJNA923753 from Ho et al. 2023. 1 sample.<br><h1>Metagenomic assembly</h1><br>De novo metagenomic assembly was performed on samples listed above. First, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_018350175.1) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes. Contigs of less than 1500 bp were removed.<br><h1>MAGs recovery</h1><br>MAGs were generated with COMEBin (multi-coverage mode) and MAGs quality was assessed with CheckM2. MAGs with completeness < 70% or contamination > 5% or N50 < 5Kb were discarded. Pairwise Average Nucleotide Identity (ANI) was computed for all recovered MAGs with fastANI and dereplication at species level (ANI cutoff = 95%).<br><h1>Non-redundant gene catalog</h1><br>Genes were predicted on all contigs from metagenomic assemblies with Prodigal (parameters : -m -p meta). Genes were pooled and clustered with cd-hit-est (parameters -c 0.95 -aS 0.90 -G 0 -d 0 -M 0 -T 0) by choosing those from the longest contigs as representatives.<br><h1>MSPs recovery</h1><br>Samples from multiple cohorts (listed above + PRJNA906124 from Lee et al. 2022) were aligned against the non-redundant gene catalog with the Meteor software suite to produce a raw gene abundance table (1,3M genes quantified in 212 samples). Then, co-abundant genes were binned in 344 Metagenomic Species Pan-genomes (MSPs, i.e. gene clusters that likely belong to the same microbial species) using MSPminer.<br><h1>MAGs and MSPs taxonomic annotation</h1><br>Dereplicated MAGs were annotated with GTDB-Tk based on GTDB r214. Then, MAGs taxonomic annotation was propagated to the corresponding MSPs.<br><h1>Construction of the phylogenetic tree</h1><br>39 universal phylogenetic markers genes were extracted from the dereplicated MAGs with fetchMGs. Then, the markers were separately aligned with MUSCLE. The 40 alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni).<h1>Mapping rate distribution across public cohorts</h1>We generated mapping rate distribution plots using Meteor2 (default parameters) for PRJEB4391, PRJEB9357, PRJNA758898, PRJNA906124, PRJNA908260, PRJNA923753 and PRJNA944553 used in catalogue assembly.<p></p>
Integrated Earthquake Catalog III: Gakkel Ridge, Knipovich Ridge and Svalbard Archipelago
<p>Integrated Earthquake Catalog III: Gakkel Ridge, Knipovich Ridge and Svalbard Archipelago</p>
database-catalog
<p>Database catalog used for the geoacademy project</p>
The RR Lyrae variable catalog of ZTF DR3
<p>The RR Lyrae variable star catalog is published along with the journal paper of "Identifying RR Lyrae in the ZTF DR3 dataset".</p>
ScienceDex guides
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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.