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cancer subtype classification leveraging multi omics data (Omics Data Automation)

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Omics Data Automation cancer subtype classification leveraging multi omics data
Cancer Subtype Classification Leveraging Multi Omics Data, supplied by Omics Data Automation, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/multi+omics+data/cancer+data+multi+omics+pan/pm42300227-445-12-16
Average 86 stars, based on 1 article reviews

cancer subtype classification leveraging multi omics data - by Bioz Stars, 2026-09

86/100 stars

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Article Title: A TRIM Family-Based Strategy for TRIMCIV Target Prediction in a Pan-Cancer Context with Multi-Omics Data and Protein Docking Integration.
Article Snippet: For example, Chen et al. investigated co-expression patterns between E3 ligases and their interacting substrates using pan-cancer multi-omics data and subsequently incorporated these features into their predictive model [44].

Article Title: A TRIM Family-Based Strategy for TRIMCIV Target Prediction in a Pan-Cancer Context with Multi-Omics Data and Protein Docking Integration.
Article Snippet: Received: 27 April 2025 Revised: 9 June 2025 Accepted: 20 June 2025 Published: 22 June 2025 Citation: Huang, Y.; Xuan, J.; Liang, J.; Liu, X.; Luo, Y.; Gao, X.; Liu, W. A TRIM Family-Based Strategy for TRIMCIV Target Prediction in a Pan-Cancer Context with Multi-Omics Data and Protein Docking Integration.

Expressing:

Article Title: A pan-cancer analysis revealed SKP2 as an inhibitor of the tumor immune microenvironment and a promising therapeutic target for immunotherapy
Article Snippet: .. Furthermore, these studies focused on SKP2 expression patterns in a restricted number of cancer types, whereas systematic pan-cancer investigations integrating multi-omics data remain limited. ..

Plasmid Preparation:

Article Title: Enhanced stroke risk prediction in hypertensive patients through deep learning integration of imaging and clinical data.
Article Snippet: .. Optimized cancer subtype classification and clustering using cat swarm optimization and support vector machine approach for Multi-Omics data. ..

Comparison:

Article Title: Anomaly Detection in Liquid Sodium Cold Trap Operation with Multisensory Data Fusion Using Long Short-Term Memory Autoencoder
Article Snippet: .. ; Ghosh, P. Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data. ..

Software:

Article Title: Systematic Multi-Target QSAR Benchmarking: Machine Learning Algorithms, Molecular Descriptors, and Validation.
Article Snippet: Quantitative structure−activity relationship (QSAR) modeling underpins computational drug discovery, yet the factors governing model generalizability across structurally novel compounds, and across protein families, remain incompletely understood.. This study addresses that gap through systematic 2D-QSAR benchmarking across four therapeutically diverse ChEMBL targets, EGFR (kinase, n = 10, 036), DRD2 (GPCR, n = 7, 558), BACE-1 (protease, n = 8, 080), and hERG (ion channel, n = 8, 077), totaling 33,751 compounds under identical experimental conditions.. Three principal findings emerge.