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493
datasets available to search
ShareScore release 0.9.0
Dataset results
493 results for “Predictive factors”
Genome-wide prediction of topoisomerase IIB binding by architectural factors and chromatin accessibility
GEO Series GSE141528. Homo sapiens. 3 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth.
GEO Series GSE236775. Homo sapiens. 67 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing; Other.
Data from: Assimilating MODIS data-derived minimum input data set and water stress factors into CERES-Maize model improves regional corn yield predictions
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Data from: Mitotic chromosome binding predicts transcription factor properties in interphase
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Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score
GEO Series GSE172471. Human parainfluenza virus 4b; Influenza B virus; Human respirovirus 1; human metapneumovirus; Human respiratory syncytial virus B; Human adenovirus sp.; Human coronavirus OC43; Human coronavirus HKU1; Severe acute respiratory syndrome coronavirus 2; Homo sapiens; Human respiratory syncytial virus A; Dromedary camel coronavirus; Human orthorubulavirus 2; Human coronavirus 229E; Human respirovirus 3; Influenza A virus; Human coronavirus NL63; Severe acute respiratory syndrome-related coronavirus. 90 samples. Type: Protein profiling by protein array.
Expression profiling of migrated and invaded breast cancer cells predicts early metastatic relapse and reveals Krüppel-like factor 9 as a potential suppressor of invasive growth in breast cancer
GEO Series GSE54465. Homo sapiens. 24 samples. Type: Expression profiling by array.
Predicting Master Transcription Factors from Pan-Cancer Expression Data
GEO Series GSE150443. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.
Validated prediction of pro-invasive growth factors using a transcriptome-wide invasion signature derived from a complex 3-D invasion assay
GEO Series GSE55322. Mus musculus. 18 samples. Type: Expression profiling by array.
Gene Expression Patterns that Predict Sensitivity to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Lung Cancer Cell Lines and Human Lung Tumors
GEO Series GSE31625. Homo sapiens. 48 samples. Type: Expression profiling by array.
A gene signature predictive for outcome in advanced ovarian cancer identifies a novel survival factor: MAGP2
GEO Series GSE18521. Homo sapiens. 75 samples. Type: Expression profiling by array.
Predicting master transcription factors from pan-cancer expression data
GEO Series GSE152885. Homo sapiens. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Transforming Growth Factor β-Induced Epithelial-to-Mesenchymal Signature Predicts Metastasis-Free Survival in Non-Small Cell Lung Cancer.
GEO Series GSE114761. Homo sapiens. 42 samples. Type: Expression profiling by array.
Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth [ChIP-seq]
GEO Series GSE236771. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth [ATAC-seq]
GEO Series GSE236770. Homo sapiens. 14 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Identification of splicing factors signature predicting prognosis risk and the mechanistic roles of novel oncogenes in HNSCC
GEO Series GSE243085. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
Mitotic chromosome binding predicts transcription factor properties in interphase [ATAC-Seq]
GEO Series GSE119781. Mus musculus. 31 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Gastrointestinal Stromal Tumor Enhancers Support a Transcription Factor Network Predictive of Clinical Outcome
GEO Series GSE95864. Homo sapiens. 74 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Profiling of H3K9me3 levels predicts Transcription Factor Activity and Survival in Acute Myeloid Leukemia
GEO Series GSE20452. Homo sapiens. 172 samples. Type: Genome binding/occupancy profiling by genome tiling array.
Dataset related to article "The pattern of failure after Stereotactic Radiation Therapy (SRT) for oligo-metastases: predictive factors for poly-progression "
<p>This record contains raw data related to article "The pattern of failure after Stereotactic Radiation Therapy (SRT) for oligo-metastases: predictive factors for poly-progression"</p><p>Abstract</p><p><strong>Purpose: </strong>Patients with oligo-metastatic disease (OMD) can be safely treated with Stereotactic Radiation Therapy (SRT). Further disease progression is common in these patients. In most cases, patients relapse again with oligo-metastases, however some can experience a poly-progression after a local ablative treatment (LAT). The purpose of this study was to retrospectively identify factors associated with poly-progression in patients receiving SRT for OMD.</p><p><strong>Methods: </strong>Data from a monocentric database were retrospectively analyzed. Patients treated with SRT for OMD and who developed progression after LAT were selected. Patients were categorized as oligo- or poly-progressive according to the number of new/progressing metastases (≤ or > 5). Herein, we analyzed data about patients' characteristics, oligo-metastatic presentation and radiation treatment characteristics to evaluate their relationship with progression type.</p><p><strong>Results: </strong>From 2013 to 2021, data on 700 patients progressing after LAT were analyzed. Among them, 227 patients (32.4%) experienced a poly-progression; the median time to poly-progression was 7.72 months (range 1-79.6). Five variables associated with poly-progression were found to be statistically significant in the univariate analysis: performance status (p < 0.001), site of the primary tumor (p = 0.016), ablative dose (p = 0.002), treated site (p = 0.002), single or double organ (p = 0.03). Of those, all but the number of involved organs retained their significant predictive value on the multivariate analysis.</p><p><strong>Conclusion: </strong>Our study identified four independent factors associated with poly-progression in patients with OMD receiving SRT. Our data may support comprehensive characterization of OMD, better understanding of factors associated with progression.</p>
Biological Predictive Factors of Response to ESA in Low Risk MDS Patients
ClinicalTrials.gov study NCT03598582. IPD Sharing: Not stated. Countries: 0. Publications: 0.
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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.