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The liquid-liquid phase separation of biomolecules is an important process for intracellular organization. Biomolecular sequence combinatorics leads to a large variety of proteins and nucleic acids which can interact to form a diversity of…
DNA strand displacement (DSD) reactions have been used to construct chemical reaction networks in which species act catalytically at the level of the overall stoichiometry of reactions. These effective catalytic reactions are typically…
DNA strand displacement (SD) reactions are central to the operation of many synthetic nucleic acid systems, including molecular circuits, sensors, and machines. Over the years, a broad set of design frameworks has emerged to accommodate…
Although the diffusion model has achieved remarkable performance in the field of image generation, its high inference delay hinders its wide application in edge devices with scarce computing resources. Therefore, many training-free sampling…
Distribution Matching Distillation (DMD) distills score-based generative models into efficient one-step generators, without requiring a one-to-one correspondence with the sampling trajectories of their teachers. Yet, the limited capacity of…
By means of the Brownian dynamics (BD) method of simulations we have developed, we study dynamics of individual DNA undergoing constant field gel electrophoresis (CFGE), focusing on the relevance of the `defect' concept due to de Gennes in…
Many industrial soft materials often include oil-in-water (O/W) emulsions at the core of their formulations. By using tuneable interface stabilizing agents, such emulsions can self-assemble into complex structures. DNA has been used for…
Edge devices operate in constrained and varying resource settings, requiring dynamic architectures that can adapt to limitations of the available resources. To meet such demands, layer dropping ($\mathcal{LD}$) approach is typically used to…
The modeling of solid-state transformations, such as polymorphic transitions and chemical reactions in molecular crystals, is vital for many applications including drug design or the development of new synthesis methods. However, a…
Predicting the binding structure of a small molecule ligand to a protein -- a task known as molecular docking -- is critical to drug design. Recent deep learning methods that treat docking as a regression problem have decreased runtime…
The dielectrophoresis method for trapping and attaching nanoscale double-stranded DNA between nanoelectrodes was developed. The method gives a high yield of trapping single or a few molecules only which enables transport measurements at the…
The accuracy of the information that can be extracted from electron diffraction patterns is often limited by the presence of optical distortions. Existing distortion characterization techniques typically require knowledge of the reciprocal…
Due to their sequential nature, traditional DNA synthesis methods are expensive in terms of time and resources. They also fabricate multiple copies of the same strand, introducing redundancy. This redundancy can be leveraged to enhance the…
Recent experiments at SLAC [1,2] and CERN [3] have revealed evidence of significant deformation in the form of "pitting" of the cells of the 1.8m series of structures DDS/RDDS (Damped Detuned Structure/Rounded Damped Detuned Structure).…
Generating chemically valid 3D molecular conformations is critical for computational drug discovery. Classical diffusion-based models like GeoLDM perform well but require hundreds of steps, making large-scale in silico screening…
Short blunt-ended DNA duplexes comprising 6 to 20 base pairs self-assemble into polydisperse semi-flexible chains due to hydrophobic stacking interactions between terminal base pairs. Above a critical concentration, which depends on…
Deoxyribonucleic acid (DNA) has shown great promise in enabling computational applications, most notably in the fields of DNA digital data storage and DNA computing. Information is encoded as DNA strands, which will naturally bind in…
Understanding elementary mechanisms behind solid-state phase transformations and reactions is the key to optimizing desired functional properties of many technologically relevant materials. Recent advances in scanning transmission electron…
The challenge of synthesizing graphene nanoribbons (GNRs) with atomic precision is currently being pursued along a one-way road, based on the synthesis of adequate molecular precursors that react in predefined ways through self-assembly…
In the field of Structure-based Drug Design (SBDD), deep learning-based generative models have achieved outstanding performance in terms of docking score. However, further study shows that the existing molecular generative methods and…