AIMC Topic: Antineoplastic Agents
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Big Data and Artificial Intelligence in Drug Discovery for Gastric Cancer: Current Applications and Future Perspectives.
Current medicinal chemistry
Jan 1, 2025
Gastric cancer (GC) represents a significant global health burden, ranking as the fifth most common malignancy and the fourth leading cause of cancer-related death worldwide. Despite recent advancements in GC treatment, the five-year survival rate fo...
Predicting transcriptional changes induced by molecules with MiTCP.
Briefings in bioinformatics
Nov 22, 2024
Studying the changes in cellular transcriptional profiles induced by small molecules can significantly advance our understanding of cellular state alterations and response mechanisms under chemical perturbations, which plays a crucial role in drug di...
Leveraging Cancer Therapy Peptide Data: A Case Study on Machine Learning Application in Accelerating Cancer Research.
Studies in health technology and informatics
Nov 22, 2024
This study leverages the DCTPep database, a comprehensive repository of cancer therapy peptides, to explore the application of machine learning in accelerating cancer research. We applied Principal Component Analysis (PCA) and K-means clustering to c...
CACER: Clinical concept Annotations for Cancer Events and Relations.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2024
OBJECTIVE: Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationship between cancer drugs and their associated symptom burden...
Model ensembling as a tool to form interpretable multi-omic predictors of cancer pharmacosensitivity.
Briefings in bioinformatics
Sep 23, 2024
Stratification of patients diagnosed with cancer has become a major goal in personalized oncology. One important aspect is the accurate prediction of the response to various drugs. It is expected that the molecular characteristics of the cancer cells...
Tailored chemotherapy: Innovative deep-learning model customizing chemotherapy for high-grade serous ovarian carcinoma.
Clinical and translational medicine
Sep 1, 2024
Multi-task deep latent spaces for cancer survival and drug sensitivity prediction.
Bioinformatics (Oxford, England)
Sep 1, 2024
MOTIVATION: Cancer is a very heterogeneous disease that can be difficult to treat without addressing the specific mechanisms driving tumour progression in a given patient. High-throughput screening and sequencing data from cancer cell-lines has drive...
Explainable machine learning prediction of edema adverse events in patients treated with tepotinib.
Clinical and translational science
Sep 1, 2024
Tepotinib is approved for the treatment of patients with non-small-cell lung cancer harboring MET exon 14 skipping alterations. While edema is the most prevalent adverse event (AE) and a known class effect of MET inhibitors including tepotinib, there...
ACP-CapsPred: an explainable computational framework for identification and functional prediction of anticancer peptides based on capsule network.
Briefings in bioinformatics
Jul 25, 2024
Cancer is a severe illness that significantly threatens human life and health. Anticancer peptides (ACPs) represent a promising therapeutic strategy for combating cancer. In silico methods enable rapid and accurate identification of ACPs without exte...
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