AIMC Topic: Cell Line, Tumor
Clear Filters Showing 171 to 180 of 508 articles
Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.
Journal of chemical information and modeling
Jun 7, 2024
The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell development and activation. Dysregulation of LCK signaling has been demonstrated to drive the oncogenesis of T-cell acute lymphoblastic leukemia (T-ALL), thus p...
Application of molecular dynamics-based pharmacophore and machine learning approaches to identify novel Mcl1 inhibitors through drug repurposing and mechanics research.
Physical chemistry chemical physics : PCCP
Jun 6, 2024
Myeloid cell leukemia 1 (Mcl1), a critical protein that regulates apoptosis, has been considered as a promising target for antitumor drugs. The conventional pharmacophore screening approach has limitations in conformation sampling and data mining. He...
TumFlow: An AI Model for Predicting New Anticancer Molecules.
International journal of molecular sciences
Jun 4, 2024
Melanoma is the fifth most common cancer in the United States. Conventional drug discovery methods are inherently time-consuming and costly, which imposes significant limitations. However, the advent of Artificial Intelligence (AI) has opened up new ...
Particle uptake in cancer cells can predict malignancy and drug resistance using machine learning.
Science advances
May 29, 2024
Tumor heterogeneity is a primary factor that contributes to treatment failure. Predictive tools, capable of classifying cancer cells based on their functions, may substantially enhance therapy and extend patient life span. The connection between cell...
Machine learning identifies the role of SMAD6 in the prognosis and drug susceptibility in bladder cancer.
Journal of cancer research and clinical oncology
May 20, 2024
BACKGROUND: Bladder cancer (BCa) is among the most prevalent malignant tumors affecting the urinary system. Due to its highly recurrent nature, standard treatments such as surgery often fail to significantly improve patient prognosis. Our research ai...
Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures.
Analytical chemistry
May 14, 2024
The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analys...
Improving Anticancer Drug Selection and Prioritization via Neural Learning to Rank.
Journal of chemical information and modeling
May 13, 2024
Personalized cancer treatment requires a thorough understanding of complex interactions between drugs and cancer cell lines in varying genetic and molecular contexts. To address this, high-throughput screening has been used to generate large-scale dr...
A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations.
Cell reports methods
May 13, 2024
Predicting cellular responses to perturbations requires interpretable insights into molecular regulatory dynamics to perform reliable cell fate control, despite the confounding non-linearity of the underlying interactions. There is a growing interest...
Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning.
BMC bioinformatics
May 9, 2024
BACKGROUND: The prediction of drug sensitivity plays a crucial role in improving the therapeutic effect of drugs. However, testing the effectiveness of drugs is challenging due to the complex mechanism of drug reactions and the lack of interpretabili...
Biomimetic piezoelectric nanomaterial-modified oral microrobots for targeted catalytic and immunotherapy of colorectal cancer.
Science advances
May 8, 2024
Lactic acid (LA) accumulation in the tumor microenvironment poses notable challenges to effective tumor immunotherapy. Here, an intelligent tumor treatment microrobot based on the unique physiological structure and metabolic characteristics of (VA) ...
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