Structural biology of CRISPR–Cas immunity and genome editing enzymes
CRISPR–Cas systems provide resistance against foreign mobile genetic elements and have
a wide range of genome editing and biotechnological applications. In this Review, we …
a wide range of genome editing and biotechnological applications. In this Review, we …
A survey on graph counterfactual explanations: definitions, methods, evaluation, and research challenges
Graph Neural Networks (GNNs) perform well in community detection and molecule
classification. Counterfactual Explanations (CE) provide counter-examples to overcome the …
classification. Counterfactual Explanations (CE) provide counter-examples to overcome the …
Dynamic characterization and interpretation for protein-RNA interactions across diverse cellular conditions using HDRNet
RNA-binding proteins play crucial roles in the regulation of gene expression, and
understanding the interactions between RNAs and RBPs in distinct cellular conditions forms …
understanding the interactions between RNAs and RBPs in distinct cellular conditions forms …
tRNA renovatio: rebirth through fragmentation
Summary tRNA function is based on unique structures that enable mRNA decoding using
anticodon trinucleotides. These structures interact with specific aminoacyl-tRNA synthetases …
anticodon trinucleotides. These structures interact with specific aminoacyl-tRNA synthetases …
Applications of deep learning in understanding gene regulation
Gene regulation is a central topic in cell biology. Advances in omics technologies and the
accumulation of omics data have provided better opportunities for gene regulation studies …
accumulation of omics data have provided better opportunities for gene regulation studies …
Interpretable RNA foundation model from unannotated data for highly accurate RNA structure and function predictions
Non-coding RNA structure and function are essential to understanding various biological
processes, such as cell signaling, gene expression, and post-transcriptional regulations …
processes, such as cell signaling, gene expression, and post-transcriptional regulations …
Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery
Computational analysis of RNA sequences constitutes a crucial step in the field of RNA
biology. As in other domains of the life sciences, the incorporation of artificial intelligence …
biology. As in other domains of the life sciences, the incorporation of artificial intelligence …
Enhancing protein function prediction performance by utilizing AlphaFold-predicted protein structures
The structure of a protein is of great importance in determining its functionality, and this
characteristic can be leveraged to train data-driven prediction models. However, the limited …
characteristic can be leveraged to train data-driven prediction models. However, the limited …
RPI-CapsuleGAN: Predicting RNA-protein interactions through an interpretable generative adversarial capsule network
ABSTRACT RNA-protein interactions (RPI) play a crucial regulatory role in cellular
physiological processes. The study and prediction of RPIs can be insightful for exploring …
physiological processes. The study and prediction of RPIs can be insightful for exploring …
Machine learning modeling of RNA structures: methods, challenges and future perspectives
The three-dimensional structure of RNA molecules plays a critical role in a wide range of
cellular processes encompassing functions from riboswitches to epigenetic regulation …
cellular processes encompassing functions from riboswitches to epigenetic regulation …