AIMC Topic: Cell Line, Tumor
Clear Filters Showing 181 to 190 of 508 articles
Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment.
PLoS computational biology
May 3, 2024
Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Ye...
MMSyn: A New Multimodal Deep Learning Framework for Enhanced Prediction of Synergistic Drug Combinations.
Journal of chemical information and modeling
Apr 27, 2024
Combination therapy is a promising strategy for the successful treatment of cancer. The large number of possible combinations, however, mean that it is laborious and expensive to screen for synergistic drug combinations in vitro. Nevertheless, becaus...
Development and validation of AI/ML derived splice-switching oligonucleotides.
Molecular systems biology
Apr 25, 2024
Splice-switching oligonucleotides (SSOs) are antisense compounds that act directly on pre-mRNA to modulate alternative splicing (AS). This study demonstrates the value that artificial intelligence/machine learning (AI/ML) provides for the identificat...
Deep learning-enabled detection of rare circulating tumor cell clusters in whole blood using label-free, flow cytometry.
Lab on a chip
Apr 16, 2024
Metastatic tumors have poor prognoses for progression-free and overall survival for all cancer patients. Rare circulating tumor cells (CTCs) and rarer circulating tumor cell clusters (CTCCs) are potential biomarkers of metastatic growth, with CTCCs r...
DBDNMF: A Dual Branch Deep Neural Matrix Factorization method for drug response prediction.
PLoS computational biology
Apr 4, 2024
Anti-cancer response of cell lines to drugs is in urgent need for individualized precision medical decision-making in the era of precision medicine. Measurements with wet-experiments is time-consuming and expensive and it is almost impossible for wid...
Machine learning framework develops neutrophil extracellular traps model for clinical outcome and immunotherapy response in lung adenocarcinoma.
Apoptosis : an international journal on programmed cell death
Mar 22, 2024
Neutrophil extracellular traps (NETs) are novel inflammatory cell death in neutrophils. Emerging studies demonstrated NETs contributed to cancer progression and metastases in multiple ways. This study intends to provide a prognostic NETs signature an...
Robotic Actuation-Mediated Quantitative Mechanogenetics for Noninvasive and On-Demand Cancer Therapy.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 21, 2024
Cell mechanotransduction signals are important targets for physical therapy. However, current physiotherapy heavily relies on ultrasound, which is generated by high-power equipment or amplified by auxiliary drugs, potentially causing undesired side e...
SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.
Computational biology and chemistry
Mar 19, 2024
The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predi...
A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors.
Nature cancer
Mar 5, 2024
Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6is) have revolutionized breast cancer therapy. However, <50% of patients have an objective response, and nearly all patients develop resistance during therapy. To elucidate the underlying mechanisms, ...
Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network.
The Analyst
Feb 26, 2024
Reprogramming of cellular metabolism is a driving factor of tumour progression and radiation therapy resistance. Identifying biochemical signatures associated with tumour radioresistance may assist with the development of targeted treatment strategie...
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