Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,199
datasets available to search
ShareScore release 0.9.0
Dataset results
1,199 results for “Alignement”
CELL CONTRACTILITY AND AN ACTIN GRADIENT DRIVE POLAR ALIGNMENT OF FIBROBLASTS IN CONSTRAINED GEOMETRIES
GEO Series GSE148155. Rattus norvegicus. 2 samples. Type: Expression profiling by high throughput sequencing.
Alignment of Mitotic Chromosomes in Human Cells Involves SR-Like Splicing Factors Btf and TRAP150
GEO Series GSE102465. Homo sapiens. 16 samples. Type: Expression profiling by array.
Circadian alignment of early onset caloric restriction promotes longevity in male C57BL/6J mice
GEO Series GSE190939. Mus musculus. 288 samples. Type: Expression profiling by high throughput sequencing.
LiBis: An ultrasensitive alignment method for low-input bisulfite sequencing
GEO Series GSE147454. Homo sapiens. 4 samples. Type: Methylation profiling by high throughput sequencing.
Alignment of the Transcriptome with Individual Variation in Animals Selectively Bred for High Drinking-In-the-Dark (HDID).
GEO Series GSE97032. Mus musculus. 69 samples. Type: Expression profiling by high throughput sequencing.
Increased dermal collagen bundle alignment in Systemic Sclerosis is associated with a cell migration signature and role of Arhgdib in directed fibroblast migration on aligned ECMs
GEO Series GSE100250. Mus musculus; Homo sapiens. 92 samples. Type: Expression profiling by high throughput sequencing.
Translational activators align mitochondrial mRNAs at the small ribosomal subunit for translation initiation
GEO Series GSE282943. Saccharomyces cerevisiae. 35 samples. Type: Other.
Stage-resolved genome architecture maps throughout meiotic prophase link regional variations in chromosome organization with homolog alignment
GEO Series GSE155638. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Alignment and quantification of ChIP-exo crosslinking patterns reveal the spatial organization of protein-DNA complexes
GEO Series GSE140923. Saccharomyces cerevisiae. 15 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Dataset used in COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations
<p>This dataset consists of two hdf5 files that contain pre-computed log-mel spectrograms that have been used to to train audio embedding models. The dataset is split into a training set and a validation set containing respectively 170793 and 19103 spectrogram patches with their accompanying multi-hot encoded tags from a vocabulary of 1000 tags provided by <a href="https://freesound.org/">Freesound</a> users.</p> <p>More details can be found in "COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations" by X. Favory, <a href="https://kdrossos.net">K. Drossos</a>, <a href="https://tutcris.tut.fi/portal/en/persons/tuomas-virtanen(210e58bb-c224-40a9-bf6c-5b786297e841).html">T. Virtanen</a>, and X. Serra. The code is available at this <a href="https://github.com/xavierfav/coala">GitHub repository</a>.</p> <p> </p> <p>License:</p> <p>This dataset is derived from content from the Freesound collection. All sounds are released under Creative Commons (CC) licenses from either <a href="https://creativecommons.org/publicdomain/zero/1.0/">CC0</a>, <a href="https://creativecommons.org/licenses/by/3.0/">CC-BY,</a> <a href="https://creativecommons.org/licenses/sampling+/1.0/">CC-S+</a>, or <a href="https://creativecommons.org/licenses/by-nc/3.0/">CC-BY-NC</a>. We attribute authors of all the sounds used in the dataset and provide their corresponding licenses in the attributions.txt file.</p> <p> </p>
Metashape: Identifying and Fixing Alignment Problems
<p>https://youtu.be/OgvvPCSU31M</p> <p>Instructional video</p>
A unique case of complex interaction between MSTIDs and mid-latitude field-aligned plasma depletions over geomagnetic low-mid latitude transition region
<p>630.0 nm airglow emission data from Hanle all-sky imager</p> <p>New Delhi Ionograms</p> <p>GIRI Radar Data</p>
Bioinspired structural hydrogels with highly ordered hierarchical orientations by flow-induced alignment of nanofibrils
Open the record for dataset details and reuse information.
Transcriptome profiling of derived-hepatocyte progenitors from human iPSCs with nanoCAGE - part2 - genomic alignments (hg19 + hg38)
<p>This repository contains genomic alignments (BED files) of paired-end nanoCAGE sequencing data (CAGEscan data) collected from Illumina MiSeq run IDs "181114_M00528_0390_000000000-C7P58" (aka "NC_LIMMS3") and "190218_M00528_0406_000000000-CB4HR" (aka "NC_LIMMS4") FASTQ files were processed with the MOIRAI pipeline OP-WORKFLOW-CAGEscan-short-reads-v2.1 (Hasegawa et al. BMC Bioinformatics 2014 May 16;15:144. doi: 10.1186/1471-2105-15-144.). Filtered pairs of reads were aligned on the human genome assemblies hg19 and hg38. See tables below for a detailed description of the samples contained in each nanoCAGE library, including barcodes and index sequences used for the demultiplexing of sequencing reads. Corresponding raw sequencing data files (FASTQ files) were deposited at Zenodo under the following Digital Object Identifier: 10.5281/zenodo.2572390.</p> <p><em><strong>"181114_M00528_0390_000000000-C7P58" ("NC_LIMMS3"):</strong></em></p> <p><strong>sample_name group barcode_sequence index_sequence</strong><br> LIMMS43_04_PETRI_S4D7_rep1 iPSC_CLONE_TODAI ACAGAT NNNNNNNN<br> LIMMS44_24_PETRI_S4D7_rep2 iPSC_CLONE_TODAI ATCGTG NNNNNNNN<br> LIMMS45_31_PETRI_S4D7_rep3 iPSC_CLONE_TODAI CACGAT NNNNNNNN<br> LIMMS46_36_PETRI_S4D14_rep1 iPSC_CLONE_TODAI CACTGA NNNNNNNN<br> LIMMS47_46_PETRI_S4D14_rep2 iPSC_CLONE_TODAI CTGACG NNNNNNNN<br> LIMMS48_63_PETRI_S4D14_rep3 iPSC_CLONE_TODAI GAGTGA NNNNNNNN<br> LIMMS49_79_PETRI_CELLARTIS_rep1 iPSC_CLONE_TODAI GTATAC NNNNNNNN<br> LIMMS50_92_PETRI_CELLARTIS_rep2 iPSC_CLONE_TODAI TCGAGC NNNNNNNN<br> LIMMS51_09_PETRI_CELLARTIS_rep3 iPSC_CLONE_TODAI ACATGA NNNNNNNN<br> LIMMS52_21_PETRI_TODAI_rep1 iPSC_CLONE_CELLARTIS ATCATA NNNNNNNN<br> LIMMS53_33_PETRI_TODAI_rep2 iPSC_CLONE_CELLARTIS CACGTG NNNNNNNN<br> LIMMS54_45_PETRI_TODAI_rep3 iPSC_CLONE_CELLARTIS CGATGA NNNNNNNN<br> LIMMS55_57_iPSC_rep1 CONTROL_iPSC GAGATA NNNNNNNN</p> <p><em><strong>"190218_M00528_0406_000000000-CB4HR" ("NC_LIMMS4"):</strong></em></p> <p><strong>sample_name group barcode_sequence index_sequence</strong><br> LIMMS56_04_iPSC_rep4 CONTROL_iPSC ACAGAT NNNNNNNN<br> LIMMS57_24_LSECS_1_11 LSECS_PETRI_MONO ATCGTG NNNNNNNN<br> LIMMS58_31_LSECS_2_11 LSECS_PETRI_MONO CACGAT NNNNNNNN<br> LIMMS59_36_LSECS_3_11 LSECS_PETRI_MONO CACTGA NNNNNNNN<br> LIMMS60_46_LSECS_1-06 LSECS_PETRI_MONO CTGACG NNNNNNNN<br> LIMMS61_63_B3_MONO_11_D3 BC_MONO_D3 GAGTGA NNNNNNNN<br> LIMMS62_79_B9_CO_10_D14 BC_CO_D14 GTATAC NNNNNNNN<br> LIMMS63_92_B13_CO_11_D3 BC_CO_D3 TCGAGC NNNNNNNN<br> LIMMS64_09_P2_10_D14 PETRI_MONO ACATGA NNNNNNNN<br> LIMMS65_21_P3_10_D14 PETRI_MONO ATCATA NNNNNNNN<br> LIMMS66_33_P3_11_D14 PETRI_MONO CACGTG NNNNNNNN<br> LIMMS67_45_B1_MONO_10_D14 BC_MONO_D14 CGATGA NNNNNNNN<br> LIMMS68_57_B2_MONO_10_D14 BC_MONO_D14 GAGATA NNNNNNNN<br> LIMMS69_69_B1_MONO_11_D14 BC_MONO_D14 GCTCTC NNNNNNNN<br> LIMMS70_81_B2_MONO_11_D14 BC_MONO_D14 GTATGA NNNNNNNN<br> LIMMS71_93_B6_CO_10_D14 BC_CO_D14 TCGATA NNNNNNNN<br> LIMMS72_11_B7_CO_10_D14 BC_CO_D14 AGTAGC NNNNNNNN<br> LIMMS73_23_B8_CO_10_D14 BC_CO_D14 ATCGCA NNNNNNNN<br> LIMMS74_35_B9_CO_11_D3 BC_CO_D3 CACTCT NNNNNNNN<br> LIMMS75_47_B11_CO_11_D14 BC_CO_D14 CTGAGC NNNNNNNN<br> LIMMS76_59_B12_CO_11_D14 BC_CO_D14 GAGCGT NNNNNNNN<br> LIMMS77_71_B14_CO_11_D14 BC_CO_D14 GCTGCA NNNNNNNN<br> LIMMS78_83_B15_CO_11_D14 BC_CO_D14 TATAGC NNNNNNNN<br> LIMMS79_95_iPSC_rep1_4 CONTROL_iPSC TCGCGT NNNNNNNN</p>
Lexical Alignment and Conversational Partner Identity (Social Status)
<p>The csv file contains the following columns: </p> <p><strong>participant.ID</strong>: unique id per participant <br> <strong>item</strong>: word associated with each stimulus <br> <strong>lexical-choice</strong>: participants’ lexical choice (1 for each item)<br> <strong>alignment</strong>: 1 where item = lexical-choice, 0 if item ≠ lexical-choice<br> <strong>condition</strong>: HS for high status partner/LS for low status partner<br> <strong>gender</strong>: Female/Male<br> <strong>age</strong>: 18-30<br> <strong>sim</strong>: cosine similarity between participants and partner description vectors (DS) 0-1<br> <strong>item_n</strong>: order of presentation (fixed)<br> <strong>stimuli_set</strong>: 1 if items belong to set 1, 2 if items belong to set 2. Set1 and set2 have been matched for items’ acceptability and frequency of use <br> <strong>stimuli_presentation</strong>: 1 for if the item was presented in the first session, 2 if the item was presented in the second session (the order of presentation was randomised)</p>
Genome in a Bottle Direct-RNA Sequencing: GM24631 Calibration-Strand Aligned Reads
Open the record for dataset details and reuse information.
WCCM 2024: Mechanical modeling of cardiac fibrosis with explicit spatial representation of myocyte loss and collagen alignment
<p>Recording of 5 minutes talk for World Congress of Computational Mechanics 2024 talk.</p>
Fig. 2 in Generic Changes for Some Nearctic Prosternini (Coleoptera: Elateridae: Dendrometrinae: Neopristilophus Buysson, 1894 and Pristilophus Latreille, 1834) to Align with Palearctic Concepts
Fig. 2. Characters of Neopristilophus. N. aethiops: A) Habitus, lateral view, female, Ohio, USA, C) Internal female genitalia and ovipositor, dorsal view, Ohio, D) Male genitalia, ventral view, Ohio, USA. N. praeses: B) Habitus, lateral view, male, Lincoln Co., Montana, USA, E) Internal female genitalia and ovipositor, dorsal view, F) Male genitalia, ventral view, Gallatin Co., Montana, USA, G) Female ovipositor only, not to scale, Wyoming, USA. Terms for internal female genitalia (C and E)—acg: accessory gland; bc: bursa copulatrix; cg: colleterial gland; o: ovipositor; v: vagina; te: terminal element. Terms for ovipositor (G)—g: gonocoxite; pa: paraproct; pr: proctiger.
Fig. 3 in Generic Changes for Some Nearctic Prosternini (Coleoptera: Elateridae: Dendrometrinae: Neopristilophus Buysson, 1894 and Pristilophus Latreille, 1834) to Align with Palearctic Concepts
Fig. 3. Dorsal habitus of Pristilophus and Selatosomus species. A) P. castanicolor, Wyoming, USA, B) P. festivus, Montana, USA, C) P. funereus, Montana, USA, D) P. morulus, Montana, USA, E) S. lateralis, California, USA, F) S. semimetallicus, Montana, USA. Not to scale.
Fig. 1 in Generic Changes for Some Nearctic Prosternini (Coleoptera: Elateridae: Dendrometrinae: Neopristilophus Buysson, 1894 and Pristilophus Latreille, 1834) to Align with Palearctic Concepts
Fig. 1. Dorsal habitus of Neopristilophus species. A) N. coniungens, male, California, USA, B) N. praeses, male, Lincoln Co., Montana, USA, C) N. aethiops, male, Maryland, USA, D) N. maurus, male, California, USA. Not to scale.
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.