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285
datasets available to search
ShareScore release 0.9.0
Dataset results
285 results for “Computational analysis”
Computational analysis of genome-wide DNA-methylation during the differentiation of human embryonic stem cells along the endodermal lineage
GEO Series GSE21715. Homo sapiens. 6 samples. Type: Expression profiling by array.
A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks [bulk RNA-seq]
GEO Series GSE175888. Mus musculus. 9 samples. Type: Expression profiling by high throughput sequencing.
A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks
GEO Series GSE175890. Mus musculus. 28 samples. Type: Expression profiling by high throughput sequencing.
Junction Usage Model (JUM) is a computational method for comprehensive annotation-free analysis of alternative pre-mRNA splicing patterns
GEO Series GSE118193. Drosophila melanogaster. 12 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic computational analysis of mastic oil-treated Lewis lung carcinomas
GEO Series GSE15287. Mus musculus. 40 samples. Type: Expression profiling by array.
A single-cell atlas of the microenvironment of implanted biomaterials and computational analysis of the transcriptional signalling networks [single-cell RNA-seq]
GEO Series GSE175889. Mus musculus. 19 samples. Type: Expression profiling by high throughput sequencing.
Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically-diverse Caenorhabditis nematodes.
GEO Series GSE272535. Caenorhabditis elegans. 24 samples. Type: Expression profiling by high throughput sequencing.
Computational Analysis of Bacterial RNA-Seq Data
GEO Series GSE45444. Neisseria gonorrhoeae F62. 3 samples. Type: Expression profiling by high throughput sequencing.
DATASET: Hierarchical Bayesian Operational Modal Analysis: Theory and Computations
<p>Inquiries about these data sets should be addressed to <strong>Dr. Omid Sedehi</strong> at <strong>osedehi@connect.ust.hk</strong>.</p> <p>To cite this data set, you may refer to <strong>https://doi.org/10.1016/j.ymssp.2020.106663</strong></p>
LAMMPS input files and analysis for estimating the glass transition temperature using ensemble molecular dynamcs of a selection of epoxy resins using different protocols for computing the density-temperature behaviour.
<p>LAMMPS input files and analysis for estimating the glass transition temperature using ensemble molecular dynamcs of a selection of epoxy resins using different protocols for computing the density-temperature behaviour. </p>
Data from "Cross-Domain Foundation Model Adaptation: Pioneering Computer Vision Models for Geophysical Data Analysis"
<p>This dataset includes the collected geoscientific data of<strong> lunar images, seismic data, and DAS arrays</strong>.</p> <p>It can be used to test the foundation model adaptation in the geophysical domain.</p> <p>Below are some brief desription of the datasets:</p> <p>1) Lunar images for<strong> crater detection<a href="https://moon.bao.ac.cn/">[CAS]</a></strong> : 1000 are used for training and 199 for testing, each with a size of 1022x1022.</p> <p>2) Seismic data for <strong>geobody identification<a href="https://kaggle.com/competitions/tgs-salt-identification-challenge">[TGS]</a></strong> : 3000 are used for training and 1000 for testing, each with a size of 224x224.</p> <p>3) Seismic data for <strong>facies classification<a href="https://www.aicrowd.com/challenges/seismic-facies-identification-challenge">[SEAM]</a></strong> : 250 are used for training and 45 for testing, each with a size of 1006x782.</p> <p>4) Seismic data for <strong>deep fault detection </strong>: 1081 are used for training and 269 for testing, each with a size of 896x896.</p> <p>5) DAS arrays for <strong>seismic event detection<a href="../records/8270895">[Biondi]</a></strong> : 115 are used for training and 28 for testing, each with a size of 512x512.</p> <p><strong>Tips: All the images are “float32” and the labels are "int8".</strong></p> <p>The test code has been published on GitHub: <strong><a href="https://github.com/ProgrammerZXG/Cross-Domain-Foundation-Model-Adaptation/">Cross-Domain-Foundation-Model-Adaptation</a></strong>.</p>
Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool
<p>We uploaded the database of the patients entrolled in the manuscript: Grassi, Roberto, Salvatore Cappabianca, Fabrizio Urraro, Vincenza Granata, Giuliana Giacobbe, Simona Magliocchetti, Diletta Cozzi, Roberta Fusco, Roberta Galdiero, Carmine Picone, Maria P. Belfiore, Alfonso Reginelli, Umberto Atripaldi, Ornella Picascia, Michele Coppola, Elio Bignardi, Roberta Grassi, and Vittorio Miele. 2021. "Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool" <em>Journal of Personalized Medicine</em> 11, no. 7: 641. https://doi.org/10.3390/jpm11070641</p>
Sentiment analysis of media's political bias in micro-blogging - A computational framework for optimized recommendation systems
<p>This dataset contains tweets from four Pakistani news channels, namely DAWN, GEO, ARY, and 24News, collected using the twarc command line tool with a Twitter academic researcher account. The tweets were collected between Nov, 2015, and April 4, 2022, and relate to three major political parties in Pakistan, PTI, PMLN, and PPP through their official names in the relevant news channel page tweets. </p>
Uncertainty Analysis of Computational Model to Simulate Neurostimulation Caused by Gradient Fields in MRI
ClinicalTrials.gov study NCT04674787. IPD Sharing: YES. Countries: 1. Publications: 0.
Antepartum Cardiotocography With and Without Computer Analysis in High Risk Pregnancies
ClinicalTrials.gov study NCT03862976. IPD Sharing: NO. Countries: 1. Publications: 0.
Automated Retinal Image Analysis System (EyeQuant) for Computation of Vascular Biomarkers
ClinicalTrials.gov study NCT04567745. IPD Sharing: NO. Countries: 1. Publications: 0.
Clinical Significance of Computer Aided Image Analysis in Treatment Response Evaluation of Lung Cancer
ClinicalTrials.gov study NCT03954847. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Socket Evaluation System to Predict Labial Bone Formation Around Immediate Implants. A Retrospective Cone Beam Computed Tomography Analysis.
ClinicalTrials.gov study NCT06246253. IPD Sharing: NO. Countries: 1. Publications: 0.
Kidney Stone Structural Analysis By Helical Computed Tomography (CT)
ClinicalTrials.gov study NCT00169780. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The WATS3D (Wide Area Transepithelial Sample Biopsy With 3-Dimensional Computer-Assisted Analysis) U.S. Registry
ClinicalTrials.gov study NCT02988934. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.