AIMC Topic: Gene Expression Regulation, Neoplastic

Clear Filters Showing 341 to 350 of 585 articles

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

Genes Aug 12, 2020
DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods use either differentially methylated CpG sites or combined CpG sites, namely differentially methylate...
Neoplasms Gene Expression Profiling Deep Learning ROC Curve Computational Biology Humans Algorithms Biomarkers, Tumor Linear Models Gene Ontology Epigenesis, Genetic Gene Expression Regulation, Neoplastic Databases, Genetic DNA Methylation Genetic Variation
View on PubMed DOI

A machine learning approach identified a diagnostic model for pancreatic cancer through using circulating microRNA signatures.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] Aug 9, 2020
Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approaches, causes many patients to miss the chance of surgery and consequently leads to a high mortality rate. Pivotal improvements in circulating microRNA e...
Humans Neural Networks, Computer Machine Learning Principal Component Analysis Gene Expression Regulation, Neoplastic Survival Analysis Algorithms Early Detection of Cancer Microarray Analysis Reproducibility of Results MicroRNAs Kaplan-Meier Estimate Sensitivity and Specificity Pancreatic Neoplasms Computational Biology Predictive Value of Tests Circulating MicroRNA
View on PubMed DOI

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Methods (San Diego, Calif.) Aug 5, 2020
Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovarian cancer patients can facilitate the therapeutics evaluation and treatment decision making. Multi-...
Epigenomics DNA Methylation DNA Copy Number Variations Ovarian Neoplasms Breast Neoplasms Genomics Computational Biology Gene Expression Regulation, Neoplastic Humans Neural Networks, Computer Machine Learning Female
View on PubMed DOI

A deep learning model to predict RNA-Seq expression of tumours from whole slide images.

Nature communications Aug 3, 2020
Deep learning methods for digital pathology analysis are an effective way to address multiple clinical questions, from diagnosis to prediction of treatment outcomes. These methods have also been used to predict gene mutations from pathology images, b...
Humans Image Processing, Computer-Assisted Computational Biology Gene Expression Regulation, Neoplastic Models, Genetic Microsatellite Instability Algorithms Neoplasms Gene Expression Profiling Deep Learning RNA-Seq
View on PubMed DOI

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.

Gut Jul 20, 2020
OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), hi...
Disease Progression Gene Expression Profiling Deep Learning Consensus Humans Gene Expression Regulation, Neoplastic Phenotype Predictive Value of Tests Prognosis Neoplasm Grading Colorectal Neoplasms Biopsy Biomarkers, Tumor RNA Datasets as Topic
View on PubMed DOI

Molecular docking and machine learning analysis of Abemaciclib in colon cancer.

BMC molecular and cell biology Jul 8, 2020
BACKGROUND: The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is personalised opens the doors to the design ...
Aminopyridines Databases, Protein Drug Repositioning Neoplasm Staging Colonic Neoplasms Survival Analysis Benzimidazoles Fatty Acid-Binding Proteins Gastrointestinal Hormones Epistasis, Genetic Molecular Docking Simulation Gene Expression Profiling Cell Line, Tumor Gene Expression Regulation, Neoplastic Adenocarcinoma Humans Machine Learning Algorithms Prognosis
View on PubMed DOI

Gene Expression Profile Prediction in Uveal Melanoma Using Deep Learning: A Pilot Study for the Development of an Alternative Survival Prediction Tool.

Ophthalmology. Retina Jun 18, 2020
Humans Melanoma Biomarkers, Tumor Transcriptome Deep Learning Pilot Projects Gene Expression Regulation, Neoplastic Anterior Eye Segment Uveal Neoplasms Uveal Melanoma
View on PubMed DOI

Beyond the limitation of targeted therapy: Improve the application of targeted drugs combining genomic data with machine learning.

Pharmacological research May 28, 2020
Precision oncology involves effectively selecting drugs for cancer patients and planning an effective treatment regimen. However, for Molecular targeted drug, using genomic state of the drug target to select drugs has limitations. Many patients who c...
Decision Support Techniques Molecular Targeted Therapy Precision Medicine Clinical Decision-Making Biomarkers, Tumor Neoplasms Humans Gene Expression Regulation, Neoplastic Machine Learning Antineoplastic Agents Signal Transduction Databases, Genetic Pharmacogenetics Models, Statistical Cell Line, Tumor Drug Screening Assays, Antitumor Genomics
View on PubMed DOI

Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks.

Scientific reports May 22, 2020
Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Due to the complexity of BC, the predi...
Gene Expression Regulation, Neoplastic RNA Neoplasm Metastasis Female Breast Neoplasms Biomarkers, Tumor Gene Expression Profiling Immunotherapy Humans Neural Networks, Computer Machine Learning
View on PubMed DOI

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...
Adenocarcinoma of Lung Diagnosis, Differential Cystatin A Transcriptome Cadherins Adenosine Triphosphatases Humans Lung Neoplasms Datasets as Topic Terminology as Topic Machine Learning Computational Biology Tumor Suppressor Proteins Carcinoma, Squamous Cell Gene Expression Regulation, Neoplastic Membrane Transport Proteins Gene Expression Profiling Transcription Factors Monte Carlo Method Serpins
View on PubMed DOI
Popular Topics
Recent Journals