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3,251
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ShareScore release 0.9.0
Dataset results
3,251 results for “ovarian cancer”
Oregovomab and PLD in PARP Inhibitor Resistant Ovarian, Fallopian Tube, or Primary Peritoneal Cancer Patients Not Candidate for Platinum Retreatment
ClinicalTrials.gov study NCT05407584. IPD Sharing: NO. Countries: 1. Publications: 1.
Study of Safety & Biological Activity of IP IMNN-001 (also Known As GEN-1) with Neoadjuvant Chemo in Ovarian Cancer
ClinicalTrials.gov study NCT02480374. IPD Sharing: NO. Countries: 1. Publications: 2.
Evaluation of Multiple Biomarkers to Estimate Risk of Ovarian Cancer in Patients With a Pelvic Mass.
ClinicalTrials.gov study NCT02785731. IPD Sharing: NO. Countries: 2. Publications: 2.
Consolidation Whole Abdominal Intensity-Modulated Radiation Therapy (IMRT) in Advanced Ovarian Cancer
ClinicalTrials.gov study NCT01180504. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Niraparib as Maintenance Therapy in Patients With Platinum Sensitive Recurrent Ovarian Cancer
ClinicalTrials.gov study NCT04546373. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Intensive Intraperitoneal Therapy in Advanced Ovarian Cancer
ClinicalTrials.gov study NCT04282356. IPD Sharing: NO. Countries: 1. Publications: 4.
Quality-of-Life Assessment in Patients With Ovarian Cancer
ClinicalTrials.gov study NCT00003772. IPD Sharing: Not stated. Countries: 4. Publications: 2.
MITO 35B: Olaparib Beyond Progression Compared to Platinum Chemotherapy After Secondary Cytoreductive Surgery in Recurrent Ovarian Cancer Patients.
ClinicalTrials.gov study NCT05255471. IPD Sharing: Not stated. Countries: 1. Publications: 1.
New Prognostic Index for Neoadjuvant Chemotherapy Outcome in Patients With Advanced High-grade Serous Ovarian Cancer
ClinicalTrials.gov study NCT06120309. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
Intraoperative Hyperthermic Intraperitoneal Chemotherapy With Ovarian Cancer
ClinicalTrials.gov study NCT01091636. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
MiRNA-103/107 in primary high-grade serous ovarian cancer and its clinical significance
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Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations
<p>Data set linked to the paper, "Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations". Pre-print of the paper is here: <a href="https://doi.org/10.1101/2020.06.16.146803">https://doi.org/10.1101/2020.06.16.146803</a>.</p> <p> </p> <p>cross_cancer_sum_stats.txt.gz contains summary genome-wide association statistics for susceptibility to single cancers (breast (BR), prostate (PR), ovarian (OV), endometrial (EN), estrogen receptor (ER)-positive breast (POS), ER-negative breast (NEG), and high-grade serous ovarian (HGS) cancers) and from the cross-cancer meta-analysis (main [main] and subtype-focused [sub]). EA in the header refers to the effect allele, OA is the other allele, EAF is the effect allele frequency in the largest of the single cancer data sets (BR), IMPR2 is the imputation quality in the largest of the single cancer data sets (BR), SE is the standard error, PVAL is the P-value, RE2Cs1 is the RE2C statistic mean effect part, RE2Cs2 is the RE2C statistic heterogeneity part, RE2Cp* is the RE2C* P-value. More on RE2Cp* can be found here: <a href="http://software.buhmhan.com/RE2C/index.php?mid=contact&act=dispBoardWrite">http://software.buhmhan.com/RE2C/index.php?mid=contact&act=dispBoardWrite</a> and in <a href="https://academic.oup.com/bioinformatics/article/33/14/i379/3953957">https://academic.oup.com/bioinformatics/article/33/14/i379/3953957</a> SNP names in cross_cancer_sum_stats.txt.gz include the chromosome and build 37 position.</p> <p> </p> <p>main_tetrachoric_corr_matrix.txt and subtype_tetrachoric_corr_matrix.txt provide the tetrachoric correlation matrices used in the main and subtype-focused meta-analyses. These were also used to specify the cryptic.cor argument of the exh.abf function of MetABF. More on MetABF can be found here: <a href="https://github.com/trochet/metabf">https://github.com/trochet/metabf</a> and in <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/gepi.22202">https://onlinelibrary.wiley.com/doi/abs/10.1002/gepi.22202</a></p> <p> </p> <p>prior_sigmas_for_metabf.txt contains the values used to specify the prior.sigma argument of the exh.abf function in MetABF.</p> <p> </p> <p>The breast cancer data used are described in <a href="https://pubmed.ncbi.nlm.nih.gov/29059683/"><strong>PMID 29059683</strong></a> and can be downloaded from <a href="http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas- summary-results-breast-cancer-risk-2017/">http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas- summary-results-breast-cancer-risk-2017/</a> (this link also includes acknowledgements). The prostate cancer data are described in <a href="https://pubmed.ncbi.nlm.nih.gov/29892016/"><strong>PMID 29892016</strong></a> and can be downloaded from: <a href="http://practical.icr.ac.uk/blog/?page_id=8164">http://practical.icr.ac.uk/blog/?page_id=8164</a> (this link also includes acknowledgements). The ovarian cancer data used are described in <a href="https://pubmed.ncbi.nlm.nih.gov/28346442/"><strong>PMID 28346442</strong></a> and can be downloaded from <a href="https://www.ebi.ac.uk/gwas/studies/GCST004415">https://www.ebi.ac.uk/gwas/studies/GCST004415</a>. The endometrial cancer data are described in <a href="https://pubmed.ncbi.nlm.nih.gov/30093612/"><strong>PMID 30093612</strong></a> and can be downloaded from <a href="https://www.ebi.ac.uk/gwas/studies/GCST006464">https://www.ebi.ac.uk/gwas/studies/GCST006464</a>. These links point to the same data that form the basis of the cross_cancer_sum_stats.txt.gz file.</p> <p> </p> <p><strong>The sample size and precision of the data presented should preclude identification of any individual study participant. However, in downloading these data, you undertake not to attempt to identify individual study participant and not to re-post these data to a third-party website. Please cite the PMIDs highlighted above along with the appropriate acknowledements if you use the cross_cancer_sum_stats.txt.gz file.</strong></p> <p> </p> <p>If you have any questions about this repository, please email Siddhartha Kar at siddhartha dot kar at bristol dot ac dot uk</p>
BRCA1- and BRCA2- mutation associated transcriptome landscapes in breast and ovarian cancers: ml-SOM results
<p>This is the submission accompanying raw result files for multiple-layer SOM (ml-SOM) analysis for the paper "Transcriptome patterns of BRCA1- and BRCA2- mutated breast and ovarian cancers".</p> <p>The dataset contains the results of the ml-SOM analysis of RNA-sequencing data from TCGA-OV (ovarian cancer) and TCGA-BRCA (breast cancer) projects. </p> <p>The dataset is organized as follows:</p> <ul> <li>Folder <strong>"12.BC.40 - Results" </strong>- ml-SOM analysis of TCGA-BRCA (breast cancer) dataset</li> <li>Folder <strong>"12.OV.40 - Results"</strong> - ml-SOM analysis of TCGA-OV (ovarian cancer) dataset</li> <li>File <strong>"12.BC.40.RData"</strong> - R data file that contains ml-SOM environment for breast cancer</li> <li>File <strong>"12.OV.40.RData"</strong> - R data file that contains ml-SOM environment for breast cancer</li> </ul> <p>For detailed instructions on browsing the results and their interpretation please refer to the oposSOM package manual [1], as well as original publications [2-4]. </p> <p><strong>References</strong></p> <ol> <li>Henry Loeffler-Wirth, Hoang Thanh Le and Martin Kalcheropos. SOM.Comprehensive analysis of transcriptome data. DOI: <a href="https://doi.org/doi:10.18129/B9.bioc.oposSOM">10.18129/B9.bioc.oposSOM</a> </li> <li>Löffler-Wirth H, Kalcher M, Binder H. oposSOM: R-package for high-dimensional portraying of genome-wide expression landscapes on Bioconductor. Bioinformatics. 2015 Oct 1;31(19):3225-7. DOI: 10.1093/bioinformatics/btv342. Epub 2015 Jun 10.</li> <li>Wirth H, von Bergen M, Binder H. Mining SOM expression portraits: feature selection and integrating concepts of molecular function. BioData Min. 2012 Oct 8;5(1):18. DOI: 10.1186/1756-0381-5-18.</li> <li>Wirth H, Löffler M, von Bergen M, Binder H. Expression cartography of human tissues using self-organizing maps. BMC Bioinformatics. 2011 Jul 27;12:306. DOI: 10.1186/1471-2105-12-306.</li> </ol>
Six versus more than six cycles of chemotherapy in advanced ovarian cancer a joint analysis of three MITO trials.
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Network pharmacology combined with gene chip to explore the targets of sanguinarine in ovarian cancer
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The use of the Prognostic Nutritional Index to predict chemotherapy toxicities in patients with ovarian cancer: Long-term experience of a tertiary center
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Investigation of Ubamatamab Combination Therapy in Adult Participants With Platinum-Resistant Ovarian Cancer
ClinicalTrials.gov study NCT06787612. IPD Sharing: YES. Countries: 4. Publications: 0.
Atezolizumab With Neoadjuvant Chemotherapy for Patients With Newly-Diagnosed Advanced-Stage Ovarian Cancer
ClinicalTrials.gov study NCT03394885. IPD Sharing: NO. Countries: 1. Publications: 0.
A Trial of Intravenous Denileukin Diftitox in Stage III or IV Ovarian Cancer
ClinicalTrials.gov study NCT00880360. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Genetic Testing for Breast, Ovarian, Pancreatic, and Prostate Cancers
ClinicalTrials.gov study NCT04330716. IPD Sharing: YES. Countries: 1. Publications: 0.
ScienceDex guides
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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.