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The molecular machinery of life is largely created via self-organisation of individual molecules into functional assemblies. Minimal coarse-grained models, where a whole macromolecule is represented by a small number of particles, can be of…

Biological Physics · Physics 2019-06-25 Anne E. Hafner , Johannes Krausser , Anđela Šarić

Lasers based on biological materials are attracting an increasing interest in view of their use in integrated and transient photonics. DNA as optical biopolymer in combination with highly-emissive dyes has been reported to have excellent…

Carbon nanotubes are often seen as the only alternative technology to silicon transistors. While they are the most likely short-term one, other longer-term alternatives should be studied as well. While contemplating biological neurons as an…

Neurons and Cognition · Quantitative Biology 2007-05-23 Hugues Berry , Olivier Temam

Artificial intelligence (AI) models remain an emerging strategy to accelerate materials design and development. We demonstrate that convolutional neural network (CNN) models can characterize DNA origami nanostructures employed in…

Chemical Physics · Physics 2025-03-17 Xingfei Wei , Qiankun Mo , Chi Chen , Mark Bathe , Rigoberto Hernandez

The engineered control of cellular function through the design of synthetic genetic networks is becoming plausible. Here we show how a naturally occurring network can be used as a parts list for artificial network design, and how model…

Biological Physics · Physics 2009-11-07 Jeff Hasty , Farren Isaacs , Milos Dolnik , David McMillen , J. J. Collins

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired…

Bio-hybrid systems---close couplings of natural organisms with technology---are high potential and still underexplored. In existing work, robots have mostly influenced group behaviors of animals. We explore the possibilities of mixing…

Neural and Evolutionary Computing · Computer Science 2018-04-20 Mostafa Wahby , Mary Katherine Heinrich , Daniel Nicolas Hofstadler , Payam Zahadat , Sebastian Risi , Phil Ayres , Thomas Schmickl , Heiko Hamann

We propose a dynamical model for the secondary structure of DNA, which is based on the finite stacking enthalpies used in thermodynamics calculations. In this model, the two strands can separate and the bases are allowed to rotate…

Biological Physics · Physics 2016-08-16 Sahin Buyukdagli , Michaël Sanrey , Marc Joyeux

The control over DNA elongation in nanofluidic devices holds great potential for large-scale genomic analysis. So far, the manipulation of DNA in nanochannels has been mostly carried out with electrophoresis and seldom with hydrodynamics,…

Organization and maintenance of the chromosomal DNA in living cells strongly depends on the DNA interactions with a plethora of DNA-binding proteins. Single-molecule studies show that formation of nucleoprotein complexes on DNA by such…

Biomolecules · Quantitative Biology 2018-09-05 Artem K. Efremov , Jie Yan

We propose a mathematical model of DNA self-assembly using 2D tiles to form 3D nanostructures. This is the first work to combine studies in self-assembly and nanotechnology in 3D, just as Rothemund and Winfree did in the 2D case. Our model…

Computational Complexity · Computer Science 2007-05-23 Ming-Yang Kao , Vijay Ramachandran

Active materials with distinctive nonequilibrium properties have diverse materials science applications. Active systems are common in living matter, such as the filament network in the cell that is activated by molecular motors, and in…

Soft Condensed Matter · Physics 2022-09-14 Lilan Qiao , Raymond Kapral

Experiments have reached a monumental capacity for designing and synthesizing microscopic particles for self-assembly, making it possible to precisely control particle concentrations, shapes, and interactions. However, more physical insight…

Soft Condensed Matter · Physics 2026-02-19 Maximilian C. Hübl , Thomas E. Videbæk , Daichi Hayakawa , W. Benjamin Rogers , Carl P. Goodrich

A simple DNA-based data storage scheme is demonstrated in which information is written using "addressing" oligonucleotides. In contrast to other methods that allow arbitrary code to be stored, the resulting DNA is suitable for downstream…

Emerging Technologies · Computer Science 2017-11-15 Gary M. Skinner , Koen Visscher , Masud Mansuripur

The macromolecules that encode and translate information in living systems, DNA and RNA, exhibit distinctive structural asymmetries, including homochirality or mirror image asymmetry and $3' - 5'$ directionality, that are invariant across…

Biomolecules · Quantitative Biology 2017-03-10 Hemachander Subramanian , Robert A. Gatenby

Several abilities of biological systems, such as adaptation to natural environment, or of animals to learn patterns when appropriately trained, are features that are extremely useful, if emulated by electronic circuits, in applications…

Neurons and Cognition · Quantitative Biology 2011-12-22 M. Di Ventra , Y. V. Pershin

Molecular spiders are synthetic molecular motors based on DNA nanotechnology. While natural molecular motors have evolved towards very high efficiency, it remains a major challenge to develop efficient designs for man-made molecular motors.…

Biological Physics · Physics 2013-03-11 Matthias Rank , Louis Reese , Erwin Frey

At the cutting edge of materials science, matter is designed to self-organize into structures that perform a wide range of functions. The past two decades have witnessed major innovations in the versatility of building blocks, ranging from…

Soft Condensed Matter · Physics 2022-09-26 Angus McMullen , Maitane Muñoz Basagoiti , Zorana Zeravcic , Jasna Brujic

Deep Neural Networks (DNNs) are built using artificial neural networks. They are part of machine learning methods that are capable of learning from data that have been used in a wide range of applications. DNNs are mainly handcrafted and…

Neural and Evolutionary Computing · Computer Science 2023-04-12 Mohammed Al-Rawi

Learning in living organisms is typically associated with networks of neurons. The use of large numbers of adjustable units has also been a crucial factor in the continued success of artificial neural networks. In light of the complexity of…

Neurons and Cognition · Quantitative Biology 2024-05-10 Matthew Smart , Stanislav Y. Shvartsman , Martin Mönnigmann