AI Medical Compendium Journal:
Nucleic acids research

Showing 121 to 130 of 228 articles

CellDART: cell type inference by domain adaptation of single-cell and spatial transcriptomic data.

Nucleic acids research
Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a critical task to clarify the spatial context of cells in a tissue. In this study, we developed a method, CellDART, which estimates the spatial distributio...

Rapid and accurate identification of ribosomal RNA sequences via deep learning.

Nucleic acids research
Advances in transcriptomic and translatomic techniques enable in-depth studies of RNA activity profiles and RNA-based regulatory mechanisms. Ribosomal RNA (rRNA) sequences are highly abundant among cellular RNA, but if the target sequences do not inc...

AggMapNet: enhanced and explainable low-sample omics deep learning with feature-aggregated multi-channel networks.

Nucleic acids research
Omics-based biomedical learning frequently relies on data of high-dimensions (up to thousands) and low-sample sizes (dozens to hundreds), which challenges efficient deep learning (DL) algorithms, particularly for low-sample omics investigations. Here...

CRISPR-Cas9 gRNA efficiency prediction: an overview of predictive tools and the role of deep learning.

Nucleic acids research
The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system has become a successful and promising technology for gene-editing. To facilitate its effective application, various computational tools ha...

DNAcycP: a deep learning tool for DNA cyclizability prediction.

Nucleic acids research
DNA mechanical properties play a critical role in every aspect of DNA-dependent biological processes. Recently a high throughput assay named loop-seq has been developed to quantify the intrinsic bendability of a massive number of DNA fragments simult...

Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes.

Nucleic acids research
Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequenc...

UFold: fast and accurate RNA secondary structure prediction with deep learning.

Nucleic acids research
For many RNA molecules, the secondary structure is essential for the correct function of the RNA. Predicting RNA secondary structure from nucleotide sequences is a long-standing problem in genomics, but the prediction performance has reached a platea...

Uncertainty-aware and interpretable evaluation of Cas9-gRNA and Cas12a-gRNA specificity for fully matched and partially mismatched targets with Deep Kernel Learning.

Nucleic acids research
The choice of guide RNA (gRNA) for CRISPR-based gene targeting is an essential step in gene editing applications, but the prediction of gRNA specificity remains challenging. Lack of transparency and focus on point estimates of efficiency disregarding...

ECO: the Evidence and Conclusion Ontology, an update for 2022.

Nucleic acids research
The Evidence and Conclusion Ontology (ECO) is a community resource that provides an ontology of terms used to capture the type of evidence that supports biomedical annotations and assertions. Consistent capture of evidence information with ECO allows...

lncRNAfunc: a knowledgebase of lncRNA function in human cancer.

Nucleic acids research
The long non-coding RNAs associating with other molecules can coordinate several physiological processes and their dysfunction can impact diverse human diseases. To date, systematic and intensive annotations on diverse interaction regulations of lncR...