AIMC Topic: Gene Expression Regulation, Neoplastic

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Insights into a Machine Learning-Based Palmitoylation-Related Gene Model for Predicting the Prognosis and Treatment Response of Breast Cancer Patients.

Technology in cancer research & treatment Jan 1, 2024
BACKGROUND: Breast cancer is a prevalent public health concern affecting numerous women globally and is associated with palmitoylation, a post-translational protein modification. Despite increasing focus on palmitoylation, its specific implications f...
Breast Neoplasms Biomarkers, Tumor Gene Expression Profiling Transcriptome Humans Machine Learning Prognosis Female Nomograms Treatment Outcome Lipoylation Gene Regulatory Networks Computational Biology Immunotherapy Gene Expression Regulation, Neoplastic
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Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia.

Technology in cancer research & treatment Jan 1, 2024
BACKGROUND: Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new type of programmed cell death, which may be involved in the process of GIM. The purpose of this stud...
Support Vector Machine Ferroptosis Metaplasia Stomach Neoplasms ROC Curve Biomarkers, Tumor Gene Expression Profiling Transcriptome Protein Interaction Maps Computational Biology Gene Expression Regulation, Neoplastic Humans Machine Learning
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Patterns of Gene Expression Profiles Associated with Colorectal Cancer in Colorectal Mucosa by Using Machine Learning Methods.

Combinatorial chemistry & high throughput screening Jan 1, 2024
BACKGROUND: Colorectal cancer (CRC) has a very high incidence and lethality rate and is one of the most dangerous cancer types. Timely diagnosis can effectively reduce the incidence of colorectal cancer. Changes in para-cancerous tissues may serve as...
Antigens, CD Cadherins Transcriptome Gene Expression Regulation, Neoplastic Support Vector Machine Intestinal Mucosa Humans Machine Learning Algorithms Colorectal Neoplasms Gene Expression Profiling
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Machine Learning Algorithms Identify Target Genes and the Molecular Mechanism of Matrine against Diffuse Large B-cell Lymphoma.

Current computer-aided drug design Jan 1, 2024
BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin's lymphoma worldwide. Novel treatment strategies are still needed for this disease.
Algorithms Gene Expression Regulation, Neoplastic Lymphoma, Large B-Cell, Diffuse Alkaloids Signal Transduction Molecular Docking Simulation Quinolizines Gene Regulatory Networks Matrines Humans Machine Learning
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Machine learning on thyroid disease: a review.

Frontiers in bioscience (Landmark edition) Mar 16, 2022
This study reviews the recent progress of machine learning for the early diagnosis of thyroid disease. Based on the results of this review, different machine learning methods would be appropriate for different types of data for the early diagnosis of...
Humans Machine Learning Infant Quality of Life Thyroid Neoplasms Gene Expression Regulation, Neoplastic MicroRNAs Thyroid Cancer, Papillary
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Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

Bioscience reports Dec 22, 2021
BACKGROUND: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patien...
Humans Prognosis Breast Neoplasms Female Machine Learning Biomarkers, Tumor Gene Expression Profiling Transcriptome Gene Expression Regulation, Neoplastic Case-Control Studies Signal Transduction Protein Interaction Maps Databases, Genetic Gene Regulatory Networks Predictive Value of Tests
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An artificial neural network model based on DNA damage response genes to predict outcomes of lower-grade glioma patients.

Briefings in bioinformatics Nov 5, 2021
Although the prognosis of lower-grade glioma (LGG) patients is better than others, outcomes are highly heterogeneous. Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status can identify patient subsets with different prognosis. However,...
Brain Neoplasms Computational Biology Gene Expression Regulation, Neoplastic Glioma Databases, Genetic DNA Damage Neoplasm Grading Proportional Hazards Models Humans Neural Networks, Computer Prognosis Biomarkers, Tumor Web Browser
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Integration and interplay of machine learning and bioinformatics approach to identify genetic interaction related to ovarian cancer chemoresistance.

Briefings in bioinformatics Nov 5, 2021
Although chemotherapy is the first-line treatment for ovarian cancer (OCa) patients, chemoresistance (CR) decreases their progression-free survival. This paper investigates the genetic interaction (GI) related to OCa-CR. To decrease the complexity of...
Drug Resistance, Neoplasm Databases, Nucleic Acid Gene Expression Profiling Gene Regulatory Networks Gene Expression Regulation, Neoplastic Ovarian Neoplasms Humans Machine Learning Female
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Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning.

Briefings in bioinformatics Sep 2, 2021
Gene expression profiling has played a significant role in the identification and classification of tumor molecules. In gene expression data, only a few feature genes are closely related to tumors. It is a challenging task to select highly discrimina...
Computational Biology Mutation Reproducibility of Results Gene Expression Regulation, Neoplastic Internet Animals Models, Genetic Neoplasms Humans Cluster Analysis Gene Expression Profiling Machine Learning Algorithms Databases, Factual
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Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients.

Briefings in bioinformatics Sep 2, 2021
Glioblastoma (GBM) is the most malignant and lethal intracranial tumor, with extremely limited treatment options. Immunotherapy has been widely studied in GBM, but none can significantly prolong the overall survival (OS) of patients without selection...
Survival Analysis Temozolomide Antineoplastic Agents, Alkylating Atlases as Topic Tumor Microenvironment Brain Neoplasms Male Middle Aged Humans Prognosis Machine Learning Female Aged Adult Treatment Outcome Neoplastic Stem Cells Gene Expression Profiling Glioblastoma Transcriptome Patient Selection Immunotherapy Programmed Cell Death 1 Receptor Gene Expression Regulation, Neoplastic
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