AIMC Topic: Biophysics

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Invited Review for 20th Anniversary Special Issue of PLRev "AI for Mechanomedicine".

Physics of life reviews Oct 24, 2024
Mechanomedicine is an interdisciplinary field that combines different areas including biomechanics, mechanobiology, and clinical applications like mechanodiagnosis and mechanotherapy. The emergence of artificial intelligence (AI) has revolutionized m...
Humans Artificial Intelligence Biophysics Mechanotransduction, Cellular Anniversaries and Special Events Biomechanical Phenomena
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Machine learning tools advance biophysics.

Biophysical journal Aug 21, 2024
Biophysics Machine Learning
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Deep learning based CETSA feature prediction cross multiple cell lines with latent space representation.

Scientific reports Jan 22, 2024
Mass spectrometry-coupled cellular thermal shift assay (MS-CETSA), a biophysical principle-based technique that measures the thermal stability of proteins at the proteome level inside the cell, has contributed significantly to the understanding of dr...
Dissection Mass Spectrometry Biophysics Cell Line Deep Learning
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Energy controls wave propagation in a neural network with spatial stimuli.

Neural networks : the official journal of the International Neural Network Society Nov 30, 2023
Nervous system has distinct anisotropy and some intrinsic biophysical properties enable neurons present various firing modes in neural activities. In presence of realistic electromagnetic fields, non-uniform radiation activates these neurons with ene...
Neural Networks, Computer Electromagnetic Fields Biophysics Neurons Models, Neurological
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An advanced approach for the electrical responses of discrete fractional-order biophysical neural network models and their dynamical responses.

Scientific reports Oct 24, 2023
The multiple activities of neurons frequently generate several spiking-bursting variations observed within the neurological mechanism. We show that a discrete fractional-order activated nerve cell framework incorporating a Caputo-type fractional diff...
Biophysics Neurons Neural Networks, Computer Computer Simulation Algorithms
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Application of Artificial Intelligence to In Vitro Tumor Modeling and Characterization of the Tumor Microenvironment.

Advanced healthcare materials Apr 26, 2023
In vitro tumor models have played vital roles in enhancing the understanding of the cellular and molecular composition of tumors, as well as their biochemical and biophysical characteristics. Advances in technology have enabled the evolution of tumor...
Cell Culture Techniques Biophysics Neoplasms Humans Tumor Microenvironment Artificial Intelligence
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Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space.

Nature communications Jul 1, 2022
Therapeutic antibody development requires selection and engineering of molecules with high affinity and other drug-like biophysical properties. Co-optimization of multiple antibody properties remains a difficult and time-consuming process that impede...
Machine Learning Complementarity Determining Regions Antibody Affinity Biophysics Benchmarking
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Soft pneumatic actuators for mimicking multi-axial femoropopliteal artery mechanobiology.

Biofabrication Apr 20, 2022
Tissue biomanufacturing aims to produce lab-grown stem cell grafts and biomimetic drug testing platforms but remains limited in its ability to recapitulate native tissue mechanics. The emerging field of soft robotics aims to emulate dynamic physiolog...
Arteries Biophysics Biomechanical Phenomena Humans Robotics
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Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms.

Nature methods Oct 4, 2021
Deep learning using neural networks relies on a class of machine-learnable models constructed using 'differentiable programs'. These programs can combine mathematical equations specific to a particular domain of natural science with general-purpose, ...
Deep Learning Proteins Neural Networks, Computer Biophysics Models, Chemical Computational Chemistry Pattern Recognition, Automated Computational Biology Protein Conformation
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Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory.

Frontiers in neural circuits Sep 20, 2021
Working memory function is severely limited. One key limitation that constrains the ability to maintain multiple items in working memory simultaneously is so-called swap errors. These errors occur when an inaccurate response is in fact accurate relat...
Biophysics Memory, Short-Term Neural Networks, Computer Neurophysiology
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