390 papers
Biophysics sits at the fascinating intersection where the laws of physics meet the complexity of living systems. This field uses tools like light, electricity, and mechanical forces to decode how cells move, how proteins fold, and how our senses translate the world around us. Rather than just observing biology, biophysicists measure and model life to understand the fundamental machinery that powers every organism.
On Gist.Science, we make these discoveries accessible by curating the latest preprints directly from bioRxiv. Our team processes every new submission in this category, providing both clear, plain-language overviews and detailed technical summaries so readers of all backgrounds can grasp the cutting-edge science. Below are the most recent biophysics papers from bioRxiv, ready for you to explore.
The paper introduces AI-BioMech, a deep learning framework utilizing transfer learning with architectures like DeepLabv3 to directly predict the mechanical behavior of aperiodic biological cellular materials from 2D images with 99% accuracy, thereby eliminating the need for manual geometry definition and traditional finite element simulations.
This study demonstrates that gastruloid symmetry breaking and axis formation are driven by a mechanochemical mechanism where collective cell fate decisions, mediated by Brachyury expression, regulate differentiation timing and induce radial cell sorting through differential tissue surface tension.
This study demonstrates that DNA origami structures equipped with repeat-domain docking strands enable effective drift correction for extended 3D MINFLUX imaging, achieving ~2 nm localization precision and facilitating the direct application of this technique to biological samples like cardiac ryanodine receptors without requiring complex sample preparation.
The authors present cryoJAX, a flexible cryo-electron microscopy image simulation library built on the JAX framework to enable efficient, differentiable, and scalable data analysis for complex biological applications.
This study presents validated MARTINI 3 coarse-grained models of the *Mycobacterium tuberculosis* outer membrane that reveal how membrane fluidity and lipid composition critically regulate the localization, diffusion, and aggregation of PDIM lipids.
This study presents a standardized, open-source framework that integrates time-resolved fluorescence imaging with molecular brightness analysis to quantitatively map and monitor protein oligomerization and association constants in living cells, overcoming expression heterogeneity to achieve in vitro-quality data for physiological research and drug discovery.
This paper introduces a framework using Fisher information to demonstrate that single-cell state transitions are governed by pronounced sloppiness and a principle of least action, where dynamics are constrained to a low-dimensional manifold of "stiff" parameters while remaining robust to numerous "sloppy" ones.
This paper demonstrates that a hybrid photonic entropy computing platform (Dirac-3) can efficiently solve fixed-backbone protein design problems with near-optimal energy solutions and favorable scaling, offering a practical alternative to classical methods for large-scale instances where exact solvers become time-prohibitive.
This study reveals that *Bacillus subtilis* biofilms undergo a sol-gel phase transition driven by the complementary roles of hydrophilic poly-γ-glutamate (which swells the colony via water absorption) and exopolysaccharides (which act as cross-linkers), a mechanism that generates internal strain to sculpt complex macroscopic morphologies like wrinkles.
This paper identifies a new class of local minima called "density misfit barrier traps" that hinder the accuracy of macromolecular ensemble models, and addresses this challenge through a synthetic data-driven competition that has spurred the development of new algorithms to improve structural refinement.