AIMC Topic: Nucleic Acid Conformation

Clear Filters Showing 1 to 10 of 121 articles

Spring-loaded DNA origami arrays as energy-supplied hardware for modular nanorobots.

Science robotics
DNA origami nanorobots allow for the rational design of nanomachines that respond to environmental stimuli with preprogrammed tasks. To date, this mostly is achieved by constructing two-state switches that, upon activation, change their conformation,...

DNA Nanostructures Characterized via Dual Nanopore Resensing.

ACS nano
DNA nanotechnology uses predictable interactions of nucleic acids to precisely engineer complex nanostructures. Characterizing these self-assembled structures at the single-structure level is crucial for validating their design and functionality. Nan...

Predicting chromatin conformation contact maps.

PloS one
Over the past 15 years, a variety of next-generation sequencing assays have been developed for measuring the 3D conformation of DNA in the nucleus. Each of these assays gives, for a particular cell or tissue type, a distinct picture of 3D chromatin a...

Graph Learning-Based Scoring of RNA-Protein Complex Structures.

Journal of chemical theory and computation
Development of suitable scoring functions is essential for the prediction of RNA-protein complex structures. Conventional statistical potential-based scoring functions suffered from deficiencies in handling conformational flexibility. The recent appl...

How large is the universe of RNA-like motifs? A clustering analysis of RNA graph motifs using topological descriptors.

PLoS computational biology
Identifying novel and functional RNA structures remains a significant challenge in RNA motif design and is crucial for developing RNA-based therapeutics. Here we introduce a computational topology-based approach with unsupervised machine-learning alg...

Predicting RNA Structure Utilizing Attention from Pretrained Language Models.

Journal of chemical information and modeling
RNA possesses functional significance that extends beyond the transport of genetic information. The functional roles of noncoding RNA can be mediated through their tertiary and secondary structure, and thus, predicting RNA structure holds great promi...

Predict the degree of secondary structures of the encoding sequences in DNA storage by deep learning model.

Scientific reports
DNA storage has been widely considered as a promising alternative for exponentially growing data. However, the inherent complex secondary structures severely compromise the processes of synthesis, PCR amplification, and sequencing, interfering with r...

Comprehensive datasets for RNA design, machine learning, and beyond.

Scientific reports
RNA molecules are essential in regulating biological processes such as gene expression, cellular differentiation, and development. Accurately predicting RNA secondary structures and designing sequences that fold into specific configurations remain si...

RiNALMo: general-purpose RNA language models can generalize well on structure prediction tasks.

Nature communications
While RNA has recently been recognized as an interesting small-molecule drug target, many challenges remain to be addressed before we take full advantage of it. This emphasizes the necessity to improve our understanding of its structures and function...

Quantifying complexity in DNA structures with high resolution Atomic Force Microscopy.

Nature communications
DNA topology is essential for regulating cellular processes and maintaining genome stability, yet it is challenging to quantify due to the size and complexity of topologically constrained DNA molecules. By combining high-resolution Atomic Force Micro...