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19,342 results for “Sequences”
Data and configuration files for "Expansion of accreting main-sequence stars during rapid mass transfer"
<p>Data and configuration files that can be used to reproduce results from the paper <a href="https://ui.adsabs.harvard.edu/abs/2024ApJ...966L...7L/abstract">Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer</a>. This directory contains MESA inlists and starting models used for calculations performed with MESA r15140, and YAML configuration files for calculations performed with COMPAS v02.41.04.</p> <p>See README.txt for a description of all files.</p> <p> </p> <p>Any work making use of these files should cite</p> <p>Lau, M., Hirai, R., Mandel, I., Tout, C., 2024, Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer, ApJL, 966, 1</p> <div></div>
Aligned DNA sequence matrix for phylogenetic analyses in the article "Three new species of Torrent Treefrogs (Anura: Hylidae) of the Hyloscirtus bogotensis group from the eastern Andean slopes and the biogeographic history of the genus"
<p>Aligned DNA sequence matrix for phylogenetic analyses of the article "Three new species of Torrent Treefrogs (Anura: Hylidae) of the Hyloscirtus bogotensis group from the Amazon foothills and the biogeographic history of the genus"</p> <p>The matrix is in NEXUS format and has 3259 bp and 25 terminals.</p> <p>Partitions are as follows:</p> <div>charset 12S = 1-955;</div> <div>charset ND1_nonCoding1 = 956-1279;</div> <div>charset ND1_Pos1 = 1280-2240\3;</div> <div>charset ND1_Pos2 = 1281-2241\3;</div> <div>charset ND1_Pos3 = 1282-2242\3;</div> <div>charset ND1_nonCoding2 = 2243-2361;</div> <div>charset cmyc_Pos1 = 2362-2779\3;</div> <div>charset cmyc_Pos2 = 2363-2780\3;</div> <div>charset cmyc_Pos3 = 2364-2781\3;</div> <div>charset Rag1_Pos1 = 2782-3415\3;</div> <div>charset Rag1_Pos2 = 2783-3416\3;</div> <div>charset Rag1_Pos3 = 2784-3417\3;</div>
Development of Multiomics in situ Pairwise Sequencing (MiP-Seq) for Single-cell Resolution Multidimensional Spatial Omics
<p>The original data used in the article: Development of Multiomics in situ Pairwise Sequencing (MiP-Seq) for Single-cell Resolution Multidimensional Spatial Omics</p> <p>Delineating the spatial multiomics landscape will pave the way to understanding the molecular basis of physiology and pathology. However, current spatial omics technology development is still in its infancy. Here, we developed a high-throughput targeted in situ sequencing strategy, multiomics in situ pairwise sequencing (MiP-Seq), to efficiently decipher multiplexed DNAs, RNAs, proteins, and small biomolecules at subcellular resolution. MiP-Seq simultaneously sequenced the dual barcode base of padlock probes, dramatically increasing the detection capacity to 10N by N rounds of sequencing. We delineated spatial gene profiles in the hypothalamus using MiP-Seq. Moreover, MiP-Seq was unitized to detect tumor gene mutations and allele-specific expression of parental genes and to differentiate sites with and without the m6A RNA modification at specific sites. MiP-Seq was combined with in vivo Ca2+ imaging and Raman imaging to obtain a spatial multiomics atlas correlated to neuronal activity and cellular biochemical fingerprints. Importantly, we proposed a “signal dilution strategy” to resolve the crowded signals that challenge the applicability of in situ sequencing. Together, our method improves spatial multiomics and precision diagnostics, and facilitates analyzing cell function in connection with gene profiles.</p>
Imputation panel for low-pass whole genome sequencing (GLIMPSE2 format)
<p>This dataset includes autosomal genotypes from the 1000 Genomes +HGDP project (<a href="https://doi.org/10.1101/2023.01.23.525248" target="_blank" rel="noopener">10.1101/2023.01.23.525248 </a>) as well as X chromosome genotypes from the NY Genome Center (as of yet, a comparable dataset that includes HGDP is not available for the X; see 10.1016/j.cell.2022.08.004). The genotypes were down-sampled so as to be appropriate for low-pass imputation; uncertain phase calls were removed (any PP tags), and individuals deemed to be outliers or relatives (based on autosomal data, as per the first citation) were also removed. Similarly, singleton polymorphisms were also excluded. Hemizygous genotypes on the X were converted into (quasi) diploid genotypes.</p> <p>These data were then converted into a binary imputation panel format using glimpse v2 (https://odelaneau.github.io/GLIMPSE/; using the static binaries provided). The "chunk" size was doubled from the defaults (which considers a minimum number of snps, genetic length and physical length) so as to be more performant.</p>
Supplementary Data Files for the paper "Intrinsically disordered compositional bias in proteins: Sequence traits, region clustering, and generation of hypothetical functional associations"
<div> <div> <div> <div> <p><strong>Supplementary data files relating to <a href="https://doi.org/10.1177/11779322241287485">https://doi.org/10.1177/11779322241287485. </a></strong></p> <p><strong><span>Suppl. File 1: Protein Family Clusters.</span></strong></p> <p><strong><span>Suppl. File 2: Cluster GO enrichments/depletions. </span></strong></p> <p><strong><span>Suppl. File 3: The raw ID-CBR data with annotations. </span></strong></p> <p><strong><span>Suppl. File 4: ­ID-CBR Cluster membership.</span></strong></p> <p><strong><span>Each file has an explanatory header. </span></strong></p> <p> </p> </div> </div> </div> </div>
GWAS Summary Statistics for Publication: Identifying novel genetic and phenotypic associations to genomic features by leveraging off-target reads in exome sequencing data
<p>This dataset contains summary statistics for genome-wide association studies (GWAS) conducted on genomic features derived from off-target reads in whole-exome sequencing (WES) data. The study utilized tools like Seeing Beyond the Target (SBT) and ImReP to construct novel phenotypic features from unmapped reads in ~50,000 participants in the UK Biobank. Features include mitochondrial DNA (mtDNA) copy number, ribosomal DNA (rDNA) copy number (5S, 18S, 28S), immune repertoire metrics (e.g., T-cell receptor alpha diversity), and microvial genome load (viral and fungal).</p> <p>Summary statistics can be used for replication studies, meta-analyses, or further exploration of these phenotypes.</p>
Sequence-based microsatellite data of Anadenanthera colubrina (Leguminosae)
<p>The file contains SSRseq genotyping data of <em>Anadenanthera colubrina</em> populations. Individuals from two life stages were scored at 25 SSRseq loci. Goncalves AL, García MV, Chancerel E, Lepais O, Heuertz M. High-throughput sequence-based microsatellite genotyping for the non-model Neotropical tree species <em>Anadenanthera colubrina</em> (Leguminosae).</p> <p>The file contains</p> <p>- Two different data sets:</p> <p>GS: Genotypes based on sequence identity.<br>GL: Genotypes based on amplicon length.</p> <p>- Allele sequence information</p>
Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project
SV analysis of the long-read sequencing data of 1,019 samples from the 1000 Genomes Project. The data is hosted at the International Genome Sample Resource (IGSR) in the <a href="https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1KG_ONT_VIENNA/">1KG_ONT_VIENNA</a> directory. Please see the <a href="https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1KG_ONT_VIENNA/README_1KG_ONT_VIENNA.md">README</a> and <a href="https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1KG_ONT_VIENNA/README_1KG_ONT_VIENNA_datareuse_statement.md">data reuse statement</a> for further information about this dataset.
FASTA file containing the MYB encoding gene An2-like and Ant1 coding sequences corresponding to wild and cultivated tomato accessions
<p>The coding sequence (CDS) of the MYB encoding genes <em>Ant1</em> and <em>An2-like</em>. Sequences were retrieved from regions corresponding to the<em> Aft</em> locus from <em>Solanum galapagense </em>accession LA1141, <em>S. lycopersicum</em> variety OH8245, and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences were compared to available CDS available from the Sol genomics network (SGN) and the National Center for Biotechnology Information. The CDS was retrieved from <em>S. lycopersicum</em> variety Indigo Rose [MN433087 (Yan et al., 2020)], <em>S. lycopersicum</em> accession LA1996 [MN242011.1, EF433417.1( Sapir et al., 2008; Colanero et al., 2020)], and <em>S. chilense </em>accession LA1930 [MN242012.1 (Colanero et al., 2020)], The orthologous CDS corresponding to the <em>Aft </em>MYB encoding genes from <em>Solanum tuberosum</em> L. Group Phureja clone DM1-3 genome (PGSC DM v4.03 Pseudomolecules) was retrieved from the Potato Genome Sequence Consortium (PGSC: Potato Genome Sequencing Consortium et al., 2011), and the Capsicum annum cv. CM334 genome was retrieved from <em>Capsicum annuum </em>cv CM334 genome chromosome release 1.55 (Hulse-Kemp et al. 2018). These CDS were obtained using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at https://solgenomics.net/tools/blast/). Comparison of syntenic chromosomal regions using known positions of tomato, potato, and pepper markers with comparative map viewer from SGN: (available at https://solgenomics.net/cview) on chromosome 10, was used as a quality check for S.<em> tuberosom</em> and <em>C. annuum.</em> Orthologous CDS corresponding to <em>Salvia miltiorrhiza, Arabidopsis thaliana</em>, [NM_105308.2, NM_105310.4 (Teng et al., 2005, Cominelli et al., 2008; Beradini et al., 2015)] were chosen based on tomato <em>Aft</em> sequence homology and gene annotations of positive R2R3 MYB regulation of anthocyanin. The CDS corresponding to the <em>Aft</em> genes were retrieved from the CDS reference genomes available from the Sol Genomics Network SGN: Tomato Genome CDS (ITAG release 4.0), Potato PGSC DM v3.4 CDS sequences, <em>Capsicum annuum </em>cv CM334 Genome CDS (release 1.55), or from the National Center for Biotechnology Information (NCBI: https://www.ncbi.nlm.nih.gov) reference sequences (RefSeq) section of the Genbank records. When accessed from Genank records, the CDS sequence was extracted from the “features” section and exported as a FASTA file.</p>
De novo sequencing of phages T4 and T7
<p>Raw data and assemblies of the <em>de novo </em>sequencing of the "model" phages T4 and T7, performed with Illumina NextSeq 2x150 and Oxford Nanopore, generated for the "Phage Annotation Workshop" held online on November 2021:</p> <p>https://github.com/quadram-institute-bioscience/phage-annotation-workshop/</p>
THE INTEGER SEQUENCE A348960
<p>This is a sequence of integers that was registered by me in the On-line Encyclopedia of Integers (OEIS) under the code: A348960. In this report, the sequence is evaluated for integers <strong>n,</strong> taking values within the range [0,70]. An algorithm in MATHEMATICA for the sequence under study is also presented.</p> <p>The empirically discovered sequence is as follows: <span class="math-tex">\(a(n) = \lfloor log(\pi n!)\rfloor\)</span></p> <p> </p>
Reference sequences and analyses
<p>Reference sequences used to train PlasX. Includes contig sequences, gene calls, and gene functional annotations.</p>
Supplementary data for "Single extreme storm sequence can offset decades of predicted shoreline retreat by sea-level rise"
<p>This dataset comprises topography and bathymetric data at three coastal locations in Australia (Narrabeen), UK (Perranporth) and used for the publication "Single extreme storm sequence can offset decades of predicted shoreline retreat by sea-level rise". Please refer to readme files for metadata</p>
epiGBS2: Improvements and evaluation of highly multiplexed, epiGBS-based reduced representation bisulfite sequencing
<p>We present epiGBS2, a laboratory protocol based on epiGBS (Gurp et al., 2016) with a revised and user-friendly bioinformatics pipeline for a wide range of species with or without reference genome. Performance of several critical steps in epiGBS2 was evaluated against baseline data sets from <em>Arabidopsis thaliana</em> and Great tit (<em>Parus major</em>), which confirmed overall good performance of epiGBS2. We provide here the raw bisulfite sequencing data of the epiGBS2 run for <em>Arabidopsis thaliana.</em></p> <p>A detailed description of the laboratory protocol and an extensive manual of the bioinformatics pipeline are publicly accessible on github (<a href="https://github.com/nioo-knaw/epiGBS2">https://github.com/nioo-knaw/epiGBS2)</a> and zenodo (https://doi.org/10.5281/zenodo.4764652).</p> <p>Demultiplexed data were deposited on NCBI under the BioProject ID PRJNA764918</p>
Targeted Re-sequencing Identifies Candidate Fusiform Rust Resistance Genes in Loblolly Pine
<p>A fasta file containing the subset of the v2.01 Pita genome in addition to the novel NLR genes that were targeted by hybridization probes. </p> <p>A bed file describing the intervals targeted by the hybridization probes.</p> <p>Trinity assemblies of the 30 RNAseq libraries along with predictions by transdecoder of CDS and peptide sequences from those trinity assemblies. </p>
Deciphering polymorphism in 61,157 Escherichia coli genomes via epistatic sequence landscapes
<p>We use computational models based on Direct Coupling Analysis - DCA - trained on PFAM domains of distant distant homologues to accurately predict the polymorphisms segregating in a panel of 61,157 <em>Escherichia coli </em>genomes.</p> <p>We show that the genetic context (<em>i.e. </em>the rest of the protein sequence) strongly constrains the tolerable amino acids in 30% to 50% of amino-acid sites. Our study also suggests the gradual build-up of genetic context over long evolutionary timescales by the accumulation of small epistatic contributions.</p> <p>Please refer to the README file for additional information on the structure of this dataset.</p> <p>Code to analyse this dataset is available at https://github.com/GiancarloCroce/DCA_polymorphism_Ecoli.</p> <p> </p>
NCBI Enterobacteriacea Closed Chromosome sequences
<p>This is a dataset of high-quality complete chromosomes from NCBI which can be used as part of the MOB-suite as a chromosomal DNA depletion strategy to identify plasmids.</p>
DNA sequence and taxonomic gap analyses to quantify the coverage of aquatic cyanobacteria and eukaryotic microalgae in reference databases: Results of a survey in the Alpine region
<p>This dataset has been prepared as part of the Interreg Alpine Space project Eco-AlpsWater (ASP569) - <em>Innovative Ecological Assessment and Water Management Strategy for the Protection of Ecosystem Services in Alpine Lakes and Rivers</em>, <a href="https://www.alpine-space.eu/projects/eco-alpswater/en/home">https://www.alpine-space.eu/projects/eco-alpswater/en/home</a></p> <p>Individual archives include 16S rRNA (cyanobacteria) and 18S rRNA (microalgae) FASTA sequences and associated blastn results obtained from the high throughput sequencing of plankton and biofilm bulk/eDNA samples collected in 2019 in 37 lakes and 22 rivers across the Alpine region. These are supporting files for the paper by Salmaso et al., 2022. DNA sequence and taxonomic gap analyses to quantify the coverage of aquatic cyanobacteria and eukaryotic microalgae in reference databases: Results of a survey in the Alpine region. Science of the Total Environment, in press.</p>
VirHunter: a deep learning-based method for detection of novel RNA viruses in plant sequencing data
<p>This storage contains 2 archives: toy datasets to test the training of the VirHunter and weights of the fully trained VirHunter models for 3 host species (peach, grapevine, sugar beet) and for fragment sizes 500 and 1000. .</p> <p>The toy dataset consists of 3 archived files: 'viruses.fasta', 'host.fasta', 'bacteria.fasta'.</p> <p>'viruses.fasta' contains 10000 randomly selected plant viruses from the virus dataset described in the paper.</p> <p>'host.fasta' consists of peach chromosome 2.</p> <p>'bacteria.fasta' consists of 10 bacterial genomes selected randomly: GCF_000284415, GCF_000590555, GCF_001548055, GCF_002795265, GCF_003330825, GCF_003957805, GCF_005845345, GCF_009176625, GCF_010748935, GCF_014681765</p> <p> </p>
Predicting Exon Criticality from Protein Sequence
<p>Exon ByPASS (predicting Exon-skipping Based in Protein amino acid SequenceS), predictions on test exons from Human and Mouse transcripts. The exons in the test set from the two genomes are those that are not predicted to be skippable in hg38 and mm10 annotation and are also exons that in-frame when skipped. The preprocessed data includes the ensemble transcript id and exon rank as well the amino acid sequence for the upstream, downstream, and exon of interest. Additionally, the table contains the output probability from the model in the last column. The input data is transformed data of the amino acid sequence that is the Exon ByPASS model can use as an input.</p>
ScienceDex guides
Understand access before you commit
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.