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Dataset results
76 results for “anticancer drug”
In vivo metallophilic self-assembly of a light-activated anticancer drug
<p>This data set contains all data of our submitted manuscript with the same title.</p> <p> </p>
Data from: Intrinsic growth heterogeneity of mouse leukemia cells underlies differential susceptibility to a growth-inhibiting anticancer drug
<p>Cancer cell populations consist of phenotypically heterogeneous cells. Growing evidence suggests that pre-existing phenotypic differences among cancer cells correlate with differential susceptibility to anticancer drugs and eventually lead to a relapse. Such phenotypic differences can arise not only externally driven by the environmental heterogeneity around individual cells but also internally by the intrinsic fluctuation of cells. However, the quantitative characteristics of intrinsic phenotypic heterogeneity emerging even under constant environments and their relevance to drug susceptibility remain elusive. Here we employed a microfluidic device, mammalian mother machine, for studying the intrinsic heterogeneity of growth dynamics of mouse lymphocytic leukemia cells (L1210) across tens of generations. The generation time of this cancer cell line had a distribution with a long tail and a heritability across generations. We determined that a minority of cell lineages exist in a slow-cycling state for multiple generations. These slow-cycling cell lineages had a higher chance of survival than the fast-cycling lineages under continuous exposure to the anticancer drug Mitomycin C. This result suggests that heritable heterogeneity in cancer cells' growth in a population influences their susceptibility to anticancer drugs.</p>
SynProtX: A Large-Scale Proteomics-Based Deep Learning Model for Predicting Synergistic Anticancer Drug Combinations
<h2>SynProtX: A Large-Scale Proteomics-Based Deep Learning Model for Predicting Synergistic Anticancer Drug Combinations</h2> <p>SynProtX is a deep learning model that integrates large-scale proteomics data, molecular graphs, and chemical fingerprints to predict synergistic effects of anticancer drug combinations. It provides robust performance across tissue-specific and study-specific datasets, enhancing reproducibility and biological relevance in drug synergy prediction.</p> <p>This Zenodo repository includes a <code>.tar.gz</code> archive containing all essential components to reproduce the experiments described in the study. This archive is designed to work seamlessly with the coding pipeline available at: <a href="https://github.com/manbaritone/SynProtX" target="_blank" rel="noopener">https://github.com/manbaritone/SynProtX</a>.</p> <h3>License:</h3> <p>Creative Commons Zero v1.0 Universal (CC0)<br>This work is released under CC0, dedicating it to the public domain. You are free to use, modify, and distribute it without restriction.</p> <h3>Archive Contents:</h3> <p>This compressed file includes:</p> <ul> <li>Datasets<br>- Tissue Datasets: <code>ALMANAC-Breast</code>, <code>ALMANAC-Lung</code>, <code>ALMANAC-Ovary</code>, <code>ALMANAC-Skin</code><br>- Study Datasets: <code>FRIEDMAN</code>, <code>ONEIL</code></li> <li>Supporting Files<br>- Raw and preprocessed data<br>- Feature dictionaries<br>- Hyperparameter configurations<br>- Trained model weights</li> </ul> <h3>Folder Structure:</h3> <blockquote> <p><code>SynProtX/</code><br><code>├── data/ # Raw and preprocessed data</code><br><code>│ ├── export/ # Processed protein/gene expression & drug combinations</code><br><code>│ ├── nps/ # Numpy arrays for all datasets</code><br><code>│ ├── nps_intersected/ # Dataset-specific numpy arrays</code><br><code>│ └── raw/ # Original data from DrugComb, CCLE, COSMIC, ChEMBL V31, ProCan-DepMapSanger</code><br><code>├── feature_dicts/ # Feature dictionaries for drug combinations</code><br><code>├── hyperparams/ # Hyperparameter configs for SynProtX-GATFP</code><br><code>│ ├── classification/ # For classification tasks</code><br><code>│ └── regression/ # For regression tasks</code><br><code>├── state_dict/ # Trained model weights</code><br><code>│ ├── classification/ # PyTorch checkpoints for classification</code><br><code>│ └── regression/ # PyTorch checkpoints for regression</code><br><code>└── README_Zenodo.md # This file</code></p> </blockquote> <h3>For more information, please visit:</h3> <p><strong>GitHub:</strong> <a href="https://github.com/manbaritone/SynProtX" target="_blank" rel="noopener">https://github.com/manbaritone/SynProtX</a></p>
Testing the Addition of an Anticancer Drug, BAY 1895344, to the Usual Chemotherapy With FOLFIRI in Advanced or Metastatic Cancers of the Stomach and Intestines
ClinicalTrials.gov study NCT04535401. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Intrinsic growth heterogeneity of mouse leukemia cells underlies differential susceptibility to a growth-inhibiting anticancer drug
Open the record for dataset details and reuse information.
Dataset for Utilizing Pathway Dependency and Network Representation of Anticancer Drug Sensitivity for Drug Synergy Prediction
Open the record for dataset details and reuse information.
Repurposing Metformin as Anticancer Drug: in Advanced Prostate Cancer
ClinicalTrials.gov study NCT03137186. IPD Sharing: NO. Countries: 1. Publications: 12.
Impact of the DROP Program on the DRP (Drug Related Problems) Related to Oral Anticancer Drugs in Ambulatory Patients with Risk Factors
ClinicalTrials.gov study NCT03257969. IPD Sharing: NO. Countries: 1. Publications: 1.
A Study of E7386 in Combination With Other Anticancer Drug(s) in Participants With Solid Tumor
ClinicalTrials.gov study NCT04008797. IPD Sharing: YES. Countries: 10. Publications: 2.
Central European Society for Anticancer Research (CESAR) Study of Paclitaxel Therapeutic Drug Monitoring
ClinicalTrials.gov study NCT01326767. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Medico-economic Evaluation of the ONCORAL Program for Ambulatory Patients Under Oral Anticancer Drugs Versus Usual Care
ClinicalTrials.gov study NCT03660670. IPD Sharing: NO. Countries: 1. Publications: 1.
Identification of Anticancer Drugs Associated With Cancer Therapy-related Cardiac Dysfunction: a Pharmacovigilance Study
ClinicalTrials.gov study NCT06268535. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Reporting, Evaluating, Preventing and Treating the Cardiotoxicity Induced by Anticancer Drugs During a Specific Cardio-oncology Consult and Follow up in Routine Care
ClinicalTrials.gov study NCT03882580. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Irradiation Modulates the Pharmacokinetics of Anticancer Drugs for Head and Neck Cancer
ClinicalTrials.gov study NCT01609114. IPD Sharing: Not stated. Countries: 1. Publications: 1.
SNSynergy: similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations
Open the record for dataset details and reuse information.
Using the Anticancer Drug Olaparib to Treat Relapsed/Refractory Acute Myeloid Leukemia or Myelodysplastic Syndrome With an Isocitrate Dehydrogenase (IDH) Mutation
ClinicalTrials.gov study NCT03953898. IPD Sharing: YES. Countries: 1. Publications: 0.
Irradiation Modulates the Pharmacokinetics of Anticancer Drugs
ClinicalTrials.gov study NCT01755585. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Perturbation-informed signatures from crosswise integration of transcriptome and chromatin accessibility analyses predict susceptibility to candidate anticancer drugs [RNA-Seq]
GEO Series GSE179057. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing.
Mitochondrial Rewiring with Small-Molecule Drug-Free Nanoassemblies Unleashes Anticancer Immunity
GEO Series GSE272255. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Exosomal SNHG26 derived from drug-resistant tongue squamous cell carcinoma cells inhibits the anticancer effect of NK cells in the microenvironment_scRNAseq
GEO Series GSE296834. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
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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.