AIMC Topic: Cell Line, Tumor
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Predicting drug synergy using a network propagation inspired machine learning framework.
Briefings in functional genomics
Jul 19, 2024
Combination therapy is a promising strategy for cancers, increasing therapeutic options and reducing drug resistance. Yet, systematic identification of efficacious drug combinations is limited by the combinatorial explosion caused by a large number o...
TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning.
Genomics, proteomics & bioinformatics
Jul 3, 2024
Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, including those derived from underrepresented groups, is no...
Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.
Journal of cellular and molecular medicine
Jul 1, 2024
Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogeneity, yet research on this aspect in cutaneous melanoma remains limited. In this study, we utilized single-cell data from 92,521 cells to explore the tu...
Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature.
Journal of cellular and molecular medicine
Jul 1, 2024
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intellig...
CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbations.
Bioinformatics (Oxford, England)
Jun 28, 2024
MOTIVATION: High-throughput screens (HTS) provide a powerful tool to decipher the causal effects of chemical and genetic perturbations on cancer cell lines. Their ability to evaluate a wide spectrum of interventions, from single drugs to intricate dr...
Integration of autoencoder and graph convolutional network for predicting breast cancer drug response.
Journal of bioinformatics and computational biology
Jun 1, 2024
Breast cancer is the most prevalent type of cancer among women. The effectiveness of anticancer pharmacological therapy may get adversely affected by tumor heterogeneity that includes genetic and transcriptomic features. This leads to clinical varia...
Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism.
Experimental dermatology
Jun 1, 2024
This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutaneous melanoma (SKCM). Bulk-transcriptome data from The Cancer Genome Atlas (TCGA) and GSE19234, GSE2...
Validating linalool as a potential drug for breast cancer treatment based on machine learning and molecular docking.
Drug development research
Jun 1, 2024
Breast cancer (BC) is a common cancer for women. This study aims to construct a prognostic risk model of BC and identify prognostic biomarkers through machine learning approaches, and clarify the mechanism by which linalool exerts tumor-suppressive f...
A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity prediction.
Briefings in bioinformatics
May 23, 2024
A major challenge of precision oncology is the identification and prioritization of suitable treatment options based on molecular biomarkers of the considered tumor. In pursuit of this goal, large cancer cell line panels have successfully been studie...
Eravacycline, an antibacterial drug, repurposed for pancreatic cancer therapy: insights from a molecular-based deep learning model.
Briefings in bioinformatics
Mar 27, 2024
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a serious threat to health, with limited effective therapeutic options, especially due to advanced stage at diagnosis and its inherent resistance to chemotherapy, making it one of the leadin...
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