AIMC Topic: Nucleic Acids

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Protein-protein and protein-nucleic acid binding site prediction via interpretable hierarchical geometric deep learning.

GigaScience
Identification of protein-protein and protein-nucleic acid binding sites provides insights into biological processes related to protein functions and technical guidance for disease diagnosis and drug design. However, accurate predictions by computati...

GeoBind: segmentation of nucleic acid binding interface on protein surface with geometric deep learning.

Nucleic acids research
Unveiling the nucleic acid binding sites of a protein helps reveal its regulatory functions in vivo. Current methods encode protein sites from the handcrafted features of their local neighbors and recognize them via a classification, which are limite...

Computational Methods and Deep Learning for Elucidating Protein Interaction Networks.

Methods in molecular biology (Clifton, N.J.)
Protein interactions play a critical role in all biological processes, but experimental identification of protein interactions is a time- and resource-intensive process. The advances in next-generation sequencing and multi-omics technologies have gre...

DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.

Briefings in bioinformatics
Proteins with intrinsically disordered regions (IDRs) are common among eukaryotes. Many IDRs interact with nucleic acids and proteins. Annotation of these interactions is supported by computational predictors, but to date, only one tool that predicts...

Mechanical Gripper Design and Force Analysis of Microplates for Automated High-Throughput Nucleic Acid Detection System.

Journal of nanoscience and nanotechnology
In the automated high-throughput nucleic acid detection system, we need to grip and transfer consumables frequently when carrying out multichannel nucleic acid detection. In order to ensure the efficiency of experiments and solve problems of the defl...