Engineering of PDMS surfaces for use in microsystems for capture and isolation of complex and biomedically important proteins: Epidermal growth factor receptor as a model system [PDF]
, 2008 Aaron Lowe +4 more
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Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Advanced Engineering Materials, EarlyView.Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani +2 more
wiley +1 more source
Fundamentals and Applications of Fluid Mechanics and Acoustics in Biomedical Engineering. [PDF]
Bioengineering (Basel)Little I, Gutmark E.
europepmc +1 more source
Advanced Engineering Materials, EarlyView.Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Biomedical engineering approaches for the delivery of JAGGED1 as a potential tissue regenerative therapy. [PDF]
Front Bioeng Biotechnol, 2023 Kaimari S, Kamalakar A, Goudy SL.
europepmc +1 more source
Computational Science and Technology Applied to Biomedical Engineering
, 2004 Takami Yamaguchi
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How Do Engineering Scientists Think? Model‐Based Simulation in Biomedical Engineering Research Laboratories [PDF]
, 2009 Nancy J. Nersessian
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Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source