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819
datasets available to search
ShareScore release 0.9.0
Dataset results
819 results for “Brain Tumor”
Valproic Acid With Temozolomide and Radiation Therapy to Treat Brain Tumors
ClinicalTrials.gov study NCT00302159. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Risk-Adapted Therapy for Young Children With Embryonal Brain Tumors, Choroid Plexus Carcinoma, High Grade Glioma or Ependymoma
ClinicalTrials.gov study NCT00602667. IPD Sharing: Not stated. Countries: 2. Publications: 3.
Evaluation of Tumor Response to Ipilimumab in the Treatment of Melanoma With Brain Metastases
ClinicalTrials.gov study NCT00623766. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Evaluation of cCeLL-Ex Vivo Confocal Microscopy for Real-time Brain Tumor Diagnosis
ClinicalTrials.gov study NCT06098248. IPD Sharing: NO. Countries: 2. Publications: 6.
Augmented Brain Tumor Multimodal Dataset Based on Reconstruction Consistency Loss
<p>We solved the problem that the brain MRI data only has the T2 modality and the other three modalities are missing. The data synthesis of the missing modal I data was completed, and the missing modal data of Flair, T1, and T1ce were completed, and 10,685 pieces of data were generated for each group of modalities.</p>
An example dataset for Multi-modal brain tumor data completion based on reconstruction consistency loss
<p>This is part of inputs and corresponding prediction results of the method, which is proposed in "Multi-modal brain tumor data completion based on reconstruction consistency loss" . This dataset can be only used for paper review, please do not share, thanks. The struction of this dataset is as follows:</p> <p>1.There are three folders, where pred_data stores the network image outputs. test_data stores the input images. trained model include the trained model by our network.</p> <p>2.The serial number is in a one-to-one correspondence.</p> <p>3.If you want to use the trained model, please download brats18 dataset and preprocess your dataset, which can refer to <a href="https://github.com/zhangshuang317/RAGAN/">https://github.com/zhangshuang317/RAGAN/</a>.</p>
Synthetic brain tumor MRIsamples - 2022-07
<p>Synthetic brain tumor MRI generated using DDPM</p> <p>https://openreview.net/forum?id=Oz7lKWVh45H</p>
RNA velocity objects of FACS-sorted (CD31+/CD45-) endothelial cells of overall merge of brain tumors
<p><strong>RNA velocity objects (zip files of .h5ad) of FACS-sorted (CD31+/CD45-) endothelial cells of overall merge of brain tumors:<br></strong></p> <p><em><span>-> part of the manuscript: Single-cell atlas of the human brain vasculature across development, adulthood and disease</span></em><span><br><em><span>https://www.nature.com/articles/s41586-024-07493-y</span></em></span></p> <p><br>--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><em>- Overall merge of tumor sorted endothelial cells_RNA velocity.zip:</em> <br> -> this is a zip file of an RNA velocity object (.h5ad) of the overall merge of FACS-sorted (CD31+/CD45-) endothelial cells isolated from brain tumors (lower-grade glioma, high-grade glioma (glioblastoma), brain metastasis, meningiomas). </p>
Supplementary video for "Rapid brain tumor classification from sparse epigenomic data"
<p>Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.</p> <div> <div> <div> <p> </p> <p>The video is a composite of 10 clinical demonstrator runs with timings for DNA extraction and library preparation.</p> </div> </div> </div>
Methylation data for "Rapid brain tumor classification from sparse epigenomic data"
<p>Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.</p> <p> </p> <p>This dataset provides methylation data from ONT and PacBio sequencing in feather file format. </p>
nCNV-seq: nanopore-based CNV analysis tool for brain tumor classification & grading
<p>An available glioma test-dataset designed for nCNV-seq analysis and its corresponding database</p>
A Phase 1, Open-Label, Dose Escalation Study of ANG1005 in Patients With Advanced Solid Tumors and Metastatic Brain Cancer
ClinicalTrials.gov study NCT00539383. IPD Sharing: Not stated. Countries: 1. Publications: 1.
GW572016 to Treat Recurrent Malignant Brain Tumors
ClinicalTrials.gov study NCT00107003. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Assessing Sleep and Circadian Rhythms in Primary Brain Tumors Patients
ClinicalTrials.gov study NCT04669574. IPD Sharing: YES. Countries: 1. Publications: 3.
Executive and Socio-cognitive Functions in Survivors of Primary Brain Tumor: Impact on Patients' Quality of Life
ClinicalTrials.gov study NCT02693405. IPD Sharing: NO. Countries: 1. Publications: 9.
A Pediatric Phase I Trial of RMP-7 and Carboplatin in Brain Tumors
ClinicalTrials.gov study NCT00001502. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Enzastaurin to Treat Recurrent Brain Tumor
ClinicalTrials.gov study NCT00108056. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Multimodal Connectome Study of Brain Tumor-operated Patients
ClinicalTrials.gov study NCT04163315. IPD Sharing: NO. Countries: 1. Publications: 4.
Valproic Acid in Childhood Progressive Brain Tumors
ClinicalTrials.gov study NCT01861990. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Neuropharmacokinetics of Eribulin Mesylate in Treating Patients With Primary or Metastatic Brain Tumors
ClinicalTrials.gov study NCT02338037. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.