AIMC Topic: Oncogenes

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Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non-Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score.

JCO clinical cancer informatics Dec 11, 2024
PURPOSE: Precision oncology in non-small cell lung cancer (NSCLC) relies on biomarker testing for clinical decision making. Despite its importance, challenges like the lack of genomic oncology training, nonstandardized biomarker reporting, and a rapi...
Humans Artificial Intelligence Carcinoma, Non-Small-Cell Lung High-Throughput Nucleotide Sequencing Oncogenes Precision Medicine Biomarkers, Tumor Lung Neoplasms
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AEmiGAP: AutoEncoder-Based miRNA-Gene Association Prediction Using Deep Learning Method.

International journal of molecular sciences Dec 5, 2024
MicroRNAs (miRNAs) play a crucial role in gene regulation and are strongly linked to various diseases, including cancer. This study presents AEmiGAP, an advanced deep learning model that integrates autoencoders with long short-term memory (LSTM) netw...
Oncogenes Humans Deep Learning Neoplasms Computational Biology MicroRNAs
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SSCI: Self-Supervised Deep Learning Improves Network Structure for Cancer Driver Gene Identification.

International journal of molecular sciences Sep 26, 2024
The pathogenesis of cancer is complex, involving abnormalities in some genes in organisms. Accurately identifying cancer genes is crucial for the early detection of cancer and personalized treatment, among other applications. Recent studies have used...
Humans Computational Biology Gene Expression Regulation, Neoplastic Deep Learning Supervised Machine Learning ROC Curve Oncogenes Neural Networks, Computer Gene Regulatory Networks Neoplasms
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Machine learning-based discovery of UPP1 as a key oncogene in tumorigenesis and immune escape in gliomas.

Frontiers in immunology Sep 24, 2024
INTRODUCTION: Gliomas are the most common and aggressive type of primary brain tumor, with a poor prognosis despite current treatment approaches. Understanding the molecular mechanisms underlying glioma development and progression is critical for imp...
Animals Cell Line, Tumor Mice Biomarkers, Tumor Brain Neoplasms Oncogenes Tumor Escape Gene Expression Regulation, Neoplastic Glioma Carcinogenesis Humans Machine Learning Prognosis
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Preliminary evaluation of deep learning for first-line diagnostic prediction of tumor mutational status.

Scientific reports Apr 28, 2023
The detection of tumour gene mutations by DNA or RNA sequencing is crucial for the prescription of effective targeted therapies. Recent developments showed promising results for tumoral mutational status prediction using new deep learning based metho...
Deep Learning Mutation Oncogenes Humans Neural Networks, Computer Retrospective Studies
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Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.

Genes Apr 19, 2022
Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaningful cancer drivers is an important and challenging task. Most studies have detected cancer drivers with mutated traits, while few studies consider mul...
Genomics Oncogenes Humans Machine Learning Algorithms Neoplasms
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Machine learning random forest for predicting oncosomatic variant NGS analysis.

Scientific reports Nov 8, 2021
Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analyzing variants at each run requires considerable time, and we are still struggling with some variants that appear correct on the metrics at first, but ...
Polymorphism, Single Nucleotide Computational Biology Databases, Genetic Models, Statistical Genetic Variation High-Throughput Nucleotide Sequencing Neoplasms Deep Learning ROC Curve Algorithms Biomarkers, Tumor Humans Neural Networks, Computer Machine Learning INDEL Mutation Oncogenes
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PrognosiT: Pathway/gene set-based tumour volume prediction using multiple kernel learning.

BMC bioinformatics Nov 2, 2021
BACKGROUND: Identification of molecular mechanisms that determine tumour progression in cancer patients is a prerequisite for developing new disease treatment guidelines. Even though the predictive performance of current machine learning models is pr...
Tumor Burden Oncogenes Machine Learning Algorithms Neoplasms Humans
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Deep learning for cancer type classification and driver gene identification.

BMC bioinformatics Oct 25, 2021
BACKGROUND: Genetic information is becoming more readily available and is increasingly being used to predict patient cancer types as well as their subtypes. Most classification methods thus far utilize somatic mutations as independent features for cl...
Humans Neoplasms Deep Learning Sequence Analysis, DNA Exome Sequencing Oncogenes
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In silico saturation mutagenesis of cancer genes.

Nature Jul 28, 2021
Despite the existence of good catalogues of cancer genes, identifying the specific mutations of those genes that drive tumorigenesis across tumour types is still a largely unsolved problem. As a result, most mutations identified in cancer genes acros...
Organ Specificity Neoplasms Oncogenes Computer Simulation Humans Models, Genetic Cell Transformation, Neoplastic Precision Medicine Machine Learning Mutation Probability Reproducibility of Results Mutagenesis
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