AIMC Topic: Tumor Suppressor Proteins
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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.
Biochimica et biophysica acta. Molecular basis of disease
Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Tumor Suppressor Proteins
Adenosine Triphosphatases
Terminology as Topic
Membrane Transport Proteins
Monte Carlo Method
Gene Expression Regulation, Neoplastic
Transcription Factors
Diagnosis, Differential
Cadherins
Humans
Datasets as Topic
Machine Learning
Carcinoma, Squamous Cell
Gene Expression Profiling
Transcriptome
Serpins
Lung Neoplasms
Adenocarcinoma of Lung
Computational Biology
Cystatin A
Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
Mar 9, 2020
INTRODUCTION: Histologic subtypes of malignant pleural mesothelioma are a major prognostic indicator and decision denominator for all therapeutic strategies. In an ambiguous case, a rare transitional mesothelioma (TM) pattern may be diagnosed by path...
A 21‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer.
Molecular medicine reports
Nov 21, 2019
Gastric cancer (GC) ranks fifth in terms of incidence and third in terms of tumor mortality worldwide. The present study was designed to construct a Support Vector Machine (SVM) classifier and risk score system for GC. The GSE62254 (training set) and...
Risk Factors
Aged
Stomach Neoplasms
Male
Middle Aged
Humans
Angiopoietin-like Proteins
Gene Expression Profiling
Cytokines
A Kinase Anchor Proteins
Prognosis
Angiopoietin-Like Protein 1
Female
Carrier Proteins
Nerve Tissue Proteins
Gene Regulatory Networks
Neoplasm Recurrence, Local
Gene Expression Regulation, Neoplastic
Tumor Suppressor Proteins
Membrane Proteins
Kaplan-Meier Estimate
Support Vector Machine
Databases, Genetic
Novel approaches for glioblastoma treatment: Focus on tumor heterogeneity, treatment resistance, and computational tools.
Cancer reports (Hoboken, N.J.)
Nov 11, 2019
BACKGROUND: Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide, a DNA alkylating agent. However, the a...
Drug Resistance, Neoplasm
Models, Genetic
Tumor Microenvironment
Humans
Chemoradiotherapy, Adjuvant
Microtubules
Clonal Evolution
Antineoplastic Combined Chemotherapy Protocols
Tumor Suppressor Protein p53
DNA Modification Methylases
Glioblastoma
Tumor Suppressor Proteins
Brain Neoplasms
Machine Learning
DNA Mutational Analysis
Mutation
Brain
DNA Repair Enzymes
Immune Checkpoint Inhibitors
Genetic Heterogeneity
Precision Medicine
Computational Biology
Prognosis
Cancer Vaccines
Setting Up a Surface-Enhanced Raman Scattering Database for Artificial-Intelligence-Based Label-Free Discrimination of Tumor Suppressor Genes.
Analytical chemistry
Dec 4, 2018
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...
Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas.
AJNR. American journal of neuroradiology
May 10, 2018
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...
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
Sep 4, 2017
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...
Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.
Scientific reports
Apr 25, 2017
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...
Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma.
Computer methods and programs in biomedicine
Dec 30, 2016
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. ...
Integrative modeling of multi-omics data to identify cancer drivers and infer patient-specific gene activity.
BMC systems biology
Feb 11, 2016
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...
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