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.
330
datasets available to search
ShareScore release 0.7.1
Dataset results
330 results for “Anticancer”
Interpretable prediction for anticancer sensitivity of glycoside amides
<p><a href="https://anti-cancer.eu/" target="_blank" rel="noopener">Development Timeline: Selective Anticancer Logic of Glycoside Amides</a></p> <p>/ Second supplemented edition /</p> <h2>📊 Interpretable Prediction Dataset:</h2> <h3>Transparent Modeling of Anticancer Sensitivity to Glycoside Amides</h3> <p>The current dataset presents the <strong>exact results</strong> of our interpretable prediction model for anticancer sensitivity to glycoside amides. It is provided in *.xlsx format and includes:</p> <ul> <li> <p>✅ Analytical data</p> </li> <li> <p>✅ Theoretical framework</p> </li> <li> <p>✅ Authorial conclusions</p> </li> <li> <p>✅ Full filtered dataset</p> </li> <li> <p>✅ Complete raw data</p> </li> </ul> <p>All information is organized in a <strong>user-friendly structure</strong>, fully compatible with standard data export formats and ready for integration into clinical modeling, pharmaceutical analysis, or transcriptomic mapping.</p> <div> </div> <h3>🔍 Transparency and Scientific Integrity</h3> <p>This dataset is not a closed interpretation. It reflects <strong>our original research findings</strong>, derived from a specific theoretical and biochemical framework. We fully acknowledge that the data may be interpreted differently depending on the analytical model, clinical context, or pharmacological assumptions.</p> <p>That is precisely why we have chosen to publish the <strong>exact numerical calculations</strong>—not just summaries or visualizations. This decision underscores our commitment to <strong>transparency</strong>, <strong>scientific reproducibility</strong>, and <strong>open dialogue</strong> with the broader research community.</p> <div> </div> <h3>🧠 A Platform for Collaboration</h3> <p>We invite clinicians, researchers, and data scientists to explore the dataset, challenge its assumptions, and build upon its structure. Whether used for comparative modeling, transcriptomic validation, or therapeutic design, the data is intended to serve as a <strong>foundation for further inquiry</strong>, not a final verdict.</p>
Comprehensive 16s rRNA sequencing and metabolomics to investigate the effect of anticancer bioactive peptides combined with oxaliplatin on gastric cancer
<p>背景: 胃癌的发生、发展与肠道菌群密切相关。既往研究发现抗癌生物活性肽(ACBP)与奥沙利铂(OXA)联合对胃癌有显着的治疗作用,但ACBP-OXA对肠道菌群的影响仍不清楚。</p><p><strong>Methods:</strong> We established a nude mouse model of ACBP-OXA combined therapy for gastric cancer, the diversity of gut microbiota and fecal metabolomics were studied, and the correlation between gut microbiota and metabolites was analyzed.</p><p><strong>Results: </strong>ACBP-OXA联合疗法对肠道菌群具有很强的调节作用。16s rRNA研究发现,在门中,ACBP-OXA处理后,厚壁菌门和拟杆菌门的相对丰度发生显着变化,厚壁菌门的相对丰度下降,拟杆菌门的相对丰度增加。属内,ACBP-OXA组中毛螺菌科NK4AB6组的相对丰度降低,odpribacter和拟杆菌属的相对丰度增加。ACBP组乳酸菌相对丰度增加,ACBP-OXA和OXA组葡萄球菌相对丰度下降。GO和KEGG研究发现联合治疗机制与代谢和免疫有关。通过代谢组学研究,本研究发现差异代谢物与Benzenoids、Ligans、neoligans、其中脂质和脂类大多参与酪氨酸代谢、不饱和脂肪酸生物合成、苯丙氨酸代谢α-生物过程。将代谢组学与16s rRNA长寿素相结合,发现氨基酸相关代谢物与Jetgalilicus、Staphylococcus、Proteiniphilum等细菌属相关。</p><p>结论: ACBP与ACBP-OXA联合治疗可能通过改变肠道菌群的分布多样性和菌群结构来改善和恢复胃癌裸鼠的肠道菌群,这可能是抑制胃癌发生、发展的关键。该研究为进一步研究ACBP-OXA在胃癌治疗中的应用提供了新的方向。</p>
Gene-guided discovery and ribosomal biosynthesis of anticancer moroidin peptides
<p>Moroidin is a bicyclic plant octapeptide with tryptophan side-chain crosslinks, originally isolated as a pain-causing agent from Australian stinging tree <em>Dendrocnide moroides</em>. Moroidin and its analog celogentin C, derived from <em>Celosia argentea</em>, are inhibitors of tubulin polymerization and, thus, lead structures for cancer therapy. However, low isolation yields from source plants and challenging organic synthesis hinder moroidin-based drug development. Here, we present biosynthesis as an alternative route to moroidin-type bicyclic peptides and report that they are ribosomally synthesized and posttranslationally modified peptides (RiPPs) derived from BURP-domain peptide cyclases in plants.</p> <p>This submission includes the 793 plant transcriptomes from the 1kp databases [1] of Table S2 which were assembled de novo by rnaSPAdes [2,3] and searched for moroidin peptide cyclases.</p> <ol> <li>Yan, Z., Carpenter, E.J., Wickett, N.J., Mirarab, S., Nguyen, N., Warnow, T., Ayyampalayam, S., Barker, M. and Burleigh, J.G., 2014. Data access for the 1,000 Plants (1KP) project. <em>Gigascience</em>, <em>3</em>(1), pp.2047-217X.</li> <li>Bankevich, A., Nurk, S., Antipov, D., Gurevich, A.A., Dvorkin, M., Kulikov, A.S., Lesin, V.M., Nikolenko, S.I., Pham, S., Prjibelski, A.D. and Pyshkin, A.V., 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. <em>Journal of computational biology</em>, <em>19</em>(5), pp.455-477.</li> <li>Bushmanova, E., Antipov, D., Lapidus, A. and Prjibelski, A.D., 2019. rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data. <em>GigaScience</em>, <em>8</em>(9), p.giz100.</li> </ol> <p> </p>
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>
Ir and NMR for article Synthesis and Biological Activity Evaluation of New Isatin-Gallate Hybrids as Antioxidant and Anticancer Agents (in vitro) and In-silico Study as Anticancer Agents and Coronavirus Inhibitors
<p>this is IR and NMR data for article titled <strong>Synthesis and Biological Activity Evaluation of New Isatin-Gallate Hybrids as Antioxidant and Anticancer Agents (<em>in vitro</em>) and In-silico Study as Anticancer Agents and Coronavirus Inhibitors </strong></p> <p> </p>
Figure 1 in The inhibitory and anticancer properties of Annona squamosa L. seed extracts
Figure 1. (A) DPPH scavenging activity of A. squamosa seed extracts (B) Superoxide scavenging activity of A. squamosa seed extracts (C) H O scavenging activity of A. squamosa seed extracts (D) Nitric oxide scavenging activity of A. squamosa seed extracts (E) Reducing 2 2 potential of the A. squamosa seed extracts.
Figure 2 in The inhibitory and anticancer properties of Annona squamosa L. seed extracts
Figure 2. Cytotoxicity assay of (A). Extracts PSE, ASE, ESE and MSE on H,EK293 cells. (B) Anti-proliferation assay of extracts PSE, ASE, ESE and MSE on M,CF7 cells and (C). Extracts PSE, ASE, ESE and MSE on H,epG2 cells. The mean SD of the data, which reflect testing of experiments, is displayed. The positive control utilised is coumarin. [PSE (petroleum ether seed extract),ASE (acetone seed extract), ESE (ethanol seed extract), MSE (Methanol seed extract)].*p <0.02; **p <0.05; ***p <0.002 related by the control.
Figure 3 in The inhibitory and anticancer properties of Annona squamosa L. seed extracts
Figure 3. Drugs' molecular interactions with the EGFR kinase: (A) Anethole; (B) Cyclopentane, 1,1,3-trimethyl; (C) Phosphine oxide, tributyl; (D) CID22311.
Figure 5. 3D in Studies on the recombinant production and anticancer activity of thermostable L- asparaginase I from Pyrococcus abyssi
Figure 5. 3D structure of L-asparaginase, α-helices are shown in red, β-pleated sheets in yellow. The interaction of enzyme and L-asparagine is shown, ligand atoms are shown in balls at active site.
Figure 4 in Studies on the recombinant production and anticancer activity of thermostable L- asparaginase I from Pyrococcus abyssi
Figure 4. Lineweaver-Burk plot indicating used for the calculation of KM and Vmax of recombinant L-asparaginase.
Figure 3 in Studies on the recombinant production and anticancer activity of thermostable L- asparaginase I from Pyrococcus abyssi
Figure 3. Effect of pH on the enzyme activity. The pH value for optimum enzyme activity was found 8.
Figure 6 in Studies on the recombinant production and anticancer activity of thermostable L- asparaginase I from Pyrococcus abyssi
Figure 6. ConSurf generated conserved sequences of L-asparaginase gene, the active site residues associated with interaction of ligand are shown in boxes.
Figure 1. SDS-PAGE photograph. M in Studies on the recombinant production and anticancer activity of thermostable L- asparaginase I from Pyrococcus abyssi
Figure 1. SDS-PAGE photograph. M, Protein marker; E, cellular extract from experimental culture; F1 and F2, purified enzyme fractions collected from chromatography colum; C, negative control experiment (extract of cells transformed with plasmid without gene of interest).
A Study of SAR444245 Combined With Other Anticancer Therapies for the Treatment of Participants With Gastrointestinal Cancer (Master Protocol) (Pegathor Gastrointestinal 203)
ClinicalTrials.gov study NCT05104567. IPD Sharing: YES. Countries: 9. Publications: 0.
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>
Original data for publication: The Atomically Precise Gold/Captopril Nanocluster Au25(Capt)18 Gains Anticancer Activity by Inhibiting Mitochondrial Oxidative Phosphorylation
<p> Original data for publication: The Atomically Precise Gold/Captopril Nanocluster Au<sub>25</sub>(Capt)<sub>18</sub> Gains Anticancer Activity by Inhibiting Mitochondrial Oxidative Phosphorylation, ACS Applied Materials & Interfaces</p>
Cystargolide-based amide and ester Pz analogs as proteasome inhibitors and anticancer agents
<p>A series of cystargolide-based beta-lactone analogs containing nitrogen atoms at the Pz portion of the scaffold were prepared and evaluated as proteasome inhibitors and for their cytotoxicity profile towards several cancer cell lines. Inclusion of one, two or even three nitrogen atoms at the Pz portion of the cystargolide scaffold is well-tolerated, producing analogs with low nanomolar proteasome inhibition activity, in many cases superior to carfilzomib. Additionally, analog 8g, containing an ester and pyrazine group at Pz, was shown to possess significant activity towards RPMI 8226 cells (IC50 = 21 nM) and to be less cytotoxic towards the normal tissue model MCF10A cells than carfilzomib.</p>
Photoresponsive Nanocarriers Based on Lithium Niobate Nanoparticles for Harmonic Imaging and On-Demand Release of Anticancer Chemotherapeutics
<p>Data set associated with the following publication:</p> <p>Gheata, A., Gaulier, G., Campargue, G., Vuilleumier, J., Kaiser, S., Gautschi, I., Riporto, F., Beauquis, S., Staedler, D., Diviani, D., Bonacina, L., Gerber-Lemaire, S. Photoresponsive Nanocarriers Based on Lithium Niobate Nanoparticles for Harmonic Imaging and On-Demand Release of Anticancer Chemotherapeutics. <em>ACS Nanoscience Au</em> <strong>2022</strong>, <em>2</em>, 355-366.</p> <p>Raw data for characterization of molecules and nanoparticles: NMR, TEM, DLS.</p> <p>Raw data for cell assays, cell imaging, cytotoxicity experiments and EGFR quantification.</p> <p>Metadata file.</p> <p>Copy of labbooks.</p>
Synergistic activity of Hsp90 inhibitors and anticancer agents in pancreatic cancer cell cultures (raw data)
<p>This data set includes raw data supporting the paper "<strong>Synergistic activity of Hsp90 inhibitors and anticancer agents in pancreatic cancer cell cultures</strong>".</p> <p><strong>The files include the following data</strong>:</p> <p>1. MTT assay results used for calculation of <strong><em>EC</em><sub>50</sub> values</strong> of tested compounds and their combinations in cancer cells;</p> <p>2. The data used for calculating <strong>combination index</strong> in order to evaluate synergistic activity;</p> <p>3. The raw data from compound activity evaluation in <strong>3D tumor spheroid assay</strong>;</p> <p>4. The data from <strong>compound and hyperthermia </strong>effect evaluation in cancer cells.</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.