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...
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...
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...
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...
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...
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...
Neurons are very complicated computational devices, incorporating numerous non-linear processes, particularly in their dendrites. Biophysical models capture these processes directly by explicitly modelling physiological variables, such as ion channel...
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...
Recent advances in deep learning frameworks have established valuable tools for analyzing the long-timescale behavior of complex systems, such as proteins. In particular, the inclusion of physical constraints, e.g., time-reversibility, was a crucial ...