AIMC Topic: Cell Membrane
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Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes.
ACS sensors
Apr 4, 2025
Raman spectroscopy in biological applications faces challenges due to complex spectra, characterized by peaks of varying widths and significant biological background noise. Convolutional neural networks (CNNs) are widely used for spectrum classificat...
Translational nanorobotics breaking through biological membranes.
Chemical Society reviews
Feb 17, 2025
In the dynamic realm of translational nanorobotics, the endeavor to develop nanorobots carrying therapeutics in rational applications necessitates a profound understanding of the biological landscape of the human body and its complexity. Within this...
PREPRINT Machine Learning for the Sensitivity Analysis of a Model of the Cellular Uptake of Nanoparticles for the Treatment of Cancer.
International journal for numerical methods in biomedical engineering
Oct 29, 2024
Experimental studies on the cellular uptake of nanoparticles (NPs), useful for the investigation of NP-based drug delivery systems, are often difficult to interpret due to the large number of parameters that can contribute to the phenomenon. It is th...
Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity.
Nature biomedical engineering
Jul 31, 2024
Many antimicrobial peptides directly disrupt bacterial membranes yet can also damage mammalian membranes. It is therefore central to their therapeutic use that rules governing the membrane selectivity of antimicrobial peptides be deciphered. However,...
Application of Generative Artificial Intelligence in Predicting Membrane Partitioning of Drugs: Combining Denoising Diffusion Probabilistic Models and MD Simulations Reduces the Computational Cost to One-Third.
Journal of chemical theory and computation
Jun 28, 2024
The optimal interaction of drugs with plasma membranes and membranes of subcellular organelles is a prerequisite for desirable pharmacology. Importantly, for drugs targeting the transmembrane lipid-facing sites of integral membrane proteins, the rela...
An active machine learning discovery platform for membrane-disrupting and pore-forming peptides.
Physical chemistry chemical physics : PCCP
Jun 26, 2024
Membrane-disrupting and pore-forming peptides (PFPs) play a substantial role in bionanotechnology and can determine the life and death of cells. The control of chemical and ion transport through cell membranes is essential to maintaining concentratio...
Topological Learning Approach to Characterizing Biological Membranes.
Journal of chemical information and modeling
Jun 24, 2024
Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order pha...
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) ...
Nanoinformatics based insights into the interaction of blood plasma proteins with carbon based nanomaterials: Implications for biomedical applications.
Advances in protein chemistry and structural biology
Feb 19, 2024
In the past three decades, interest in using carbon-based nanomaterials (CBNs) in biomedical application has witnessed remarkable growth. Despite the rapid advancement, the translation of laboratory experimentation to clinical applications of nanomat...
Overlay databank unlocks data-driven analyses of biomolecules for all.
Nature communications
Feb 7, 2024
Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make...
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