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Tumor Suppressor Proteins

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Multi-label Inductive Matrix Completion for Joint MGMT and IDH1 Status Prediction for Glioma Patients.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which is...

Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The O-methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes in patients with glioblastoma (GBM) and may be a predictive marker of sensitivity to chemotherapy. ...

Regulation of demethylation and re-expression of RASSF1A gene in hepatocellular carcinoma cell lines treated with NCTD in vitro.

Journal of cancer research and therapeutics
BACKGROUND: Hepatocellular carcinoma, a lethal malignant neoplasm with poor prognosis, has dismal results of surgical resection and chemoradiotherapy. Norcantharidin (NCTD), the demethylated analog of cantharidin derived from a traditional Chinese me...

Integrative modeling of multi-omics data to identify cancer drivers and infer patient-specific gene activity.

BMC systems biology
BACKGROUND: High throughput technologies have been used to profile genes in multiple different dimensions, such as genetic variation, copy number, gene and protein expression, epigenetics, metabolomics. Computational analyses often treat these differ...

Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.

Scientific reports
Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differ...

Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision.

Nucleic acids research
Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety...

MRI to MGMT: predicting methylation status in glioblastoma patients using convolutional recurrent neural networks.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Glioblastoma Multiforme (GBM), a malignant brain tumor, is among the most lethal of all cancers. Temozolomide is the primary chemotherapy treatment for patients diagnosed with GBM. The methylation status of the promoter or the enhancer regions of the...

Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: The World Health Organization has recently placed new emphasis on the integration of genetic information for gliomas. While tissue sampling remains the criterion standard, noninvasive imaging techniques may provide complimenta...

Setting Up a Surface-Enhanced Raman Scattering Database for Artificial-Intelligence-Based Label-Free Discrimination of Tumor Suppressor Genes.

Analytical chemistry
The quality of input data in deep learning is tightly associated with the ultimate performance of the machine learner. Taking advantage of the unique merits of surface-enhanced Raman scattering (SERS) methodology in the collection and construction of...