AIMC Topic: Oncogenes

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Evaluating machine learning methodologies for identification of cancer driver genes.

Scientific reports Jun 10, 2021
Cancer is driven by distinctive sorts of changes and basic variations in genes. Recognizing cancer driver genes is basic for accurate oncological analysis. Numerous methodologies to distinguish and identify drivers presently exist, but efficient tool...
Biomarkers, Tumor Neoplasms ROC Curve Machine Learning Algorithms Reproducibility of Results Databases, Genetic Web Browser Oncogenes Genomics Computational Biology Support Vector Machine Humans
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Integrating multi-omics data through deep learning for accurate cancer prognosis prediction.

Computers in biology and medicine May 9, 2021
BACKGROUND: Genomic information is nowadays widely used for precise cancer treatments. Since the individual type of omics data only represents a single view that suffers from data noise and bias, multiple types of omics data are required for accurate...
Humans Breast Neoplasms Genomics Female Gene Expression Profiling Oncogenes Deep Learning
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Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Computational and mathematical methods in medicine Apr 24, 2021
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based...
Support Vector Machine Databases, Genetic Decision Trees Computational Biology Gene Expression Regulation, Neoplastic Bayes Theorem Oligonucleotide Array Sequence Analysis Oncogenes Machine Learning Algorithms Female Male Neoplasms ROC Curve Humans Neural Networks, Computer
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An integrated deep learning and dynamic programming method for predicting tumor suppressor genes, oncogenes, and fusion from PDB structures.

Computers in biology and medicine Apr 5, 2021
Mutations in proto-oncogenes (ONGO) and the loss of regulatory function of tumor suppression genes (TSG) are the common underlying mechanism for uncontrolled tumor growth. While cancer is a heterogeneous complex of distinct diseases, finding the pote...
Humans Neural Networks, Computer Databases, Factual Oncogenes Deep Learning Genes, Tumor Suppressor
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SVFX: a machine learning framework to quantify the pathogenicity of structural variants.

Genome biology Nov 9, 2020
There is a lack of approaches for identifying pathogenic genomic structural variants (SVs) although they play a crucial role in many diseases. We present a mechanism-agnostic machine learning-based workflow, called SVFX, to assign pathogenicity score...
Humans Genomics Machine Learning Epigenomics Virulence Genome, Human Oncogenes Genomic Structural Variation
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Cancer classification based on chromatin accessibility profiles with deep adversarial learning model.

PLoS computational biology Nov 9, 2020
Given the complexity and diversity of the cancer genomics profiles, it is challenging to identify distinct clusters from different cancer types. Numerous analyses have been conducted for this propose. Still, the methods they used always do not direct...
Chromatin Immunoprecipitation Sequencing Chromatin Oncogenes RNA-Seq Genomics Computational Biology Multigene Family Normal Distribution Databases, Nucleic Acid Humans Neoplasms Deep Learning
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Identification of Latent Oncogenes with a Network Embedding Method and Random Forest.

BioMed research international Sep 23, 2020
Oncogene is a special type of genes, which can promote the tumor initiation. Good study on oncogenes is helpful for understanding the cause of cancers. Experimental techniques in early time are quite popular in detecting oncogenes. However, their def...
Machine Learning Algorithms Databases, Genetic Neoplasms Humans Cell Transformation, Neoplastic ROC Curve Oncogenes Protein Interaction Maps Computational Biology
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Application of Artificial Intelligence in Diabetes Education and Management: Present Status and Promising Prospect.

Frontiers in public health May 29, 2020
Despite the rapid development of science and technology in healthcare, diabetes remains an incurable lifelong illness. Diabetes education aiming to improve the self-management skills is an essential way to help patients enhance their metabolic contro...
Oncogenes Prospective Studies Quality of Life Diabetes Mellitus Humans Artificial Intelligence
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DEEPSEN: a convolutional neural network based method for super-enhancer prediction.

BMC bioinformatics Dec 24, 2019
BACKGROUND: Super-enhancers (SEs) are clusters of transcriptional active enhancers, which dictate the expression of genes defining cell identity and play an important role in the development and progression of tumors and other diseases. Many key canc...
Humans Oncogenes Neural Networks, Computer Neoplasms
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LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes.

PLoS computational biology Sep 30, 2019
Cancer driver genes, i.e., oncogenes and tumor suppressor genes, are involved in the acquisition of important functions in tumors, providing a selective growth advantage, allowing uncontrolled proliferation and avoiding apoptosis. It is therefore imp...
Computational Biology Models, Statistical Software Oncogenes Humans Algorithms Neoplasms Machine Learning
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