AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

DNA

Showing 121 to 130 of 429 articles

Clear Filters

SENIES: DNA Shape Enhanced Two-Layer Deep Learning Predictor for the Identification of Enhancers and Their Strength.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying enhancers is a critical task in bioinformatics due to their primary role in regulating gene expression. For this reason, various computational algorithms devoted to enhancer identification have been put forward over the years. More featur...

iDRBP-EL: Identifying DNA- and RNA- Binding Proteins Based on Hierarchical Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Identification of DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) from the primary sequences is essential for further exploring protein-nucleic acid interactions. Previous studies have shown that machine-learning-based methods can efficie...

Laplacian Regularized Sparse Representation Based Classifier for Identifying DNA N4-Methylcytosine Sites via L-Matrix Norm.

IEEE/ACM transactions on computational biology and bioinformatics
N4-methylcytosine (4mC) is one of important epigenetic modifications in DNA sequences. Detecting 4mC sites is time-consuming. The computational method based on machine learning has provided effective help for identifying 4mC. To further improve the p...

I-DNAN6mA: Accurate Identification of DNA N-Methyladenine Sites Using the Base-Pairing Map and Deep Learning.

Journal of chemical information and modeling
The recent discovery of numerous DNA N-methyladenine (6mA) sites has transformed our perception about the roles of 6mA in living organisms. However, our ability to understand them is hampered by our inability to identify 6mA sites rapidly and cost-ef...

Molecular Computation for Molecular Classification.

Advanced biology
DNA as an informational polymer has, for the past 30 years, progressively become an essential molecule to rationally build chemical reaction networks endowed with powerful signal-processing capabilities. Whether influenced by the silicon world or ins...

A universal deep-learning model for zinc finger design enables transcription factor reprogramming.

Nature biotechnology
CysHis zinc finger (ZF) domains engineered to bind specific target sequences in the genome provide an effective strategy for programmable regulation of gene expression, with many potential therapeutic applications. However, the structurally intricate...

DNA Origami Nanostructure Detection and Yield Estimation Using Deep Learning.

ACS synthetic biology
DNA origami is a milestone in DNA nanotechnology. It is robust and efficient in constructing arbitrary two- and three-dimensional nanostructures. The shape and size of origami structures vary. To characterize them, an atomic force microscope, a trans...

MultiScale-CNN-4mCPred: a multi-scale CNN and adaptive embedding-based method for mouse genome DNA N4-methylcytosine prediction.

BMC bioinformatics
N4-methylcytosine (4mC) is an important epigenetic mechanism, which regulates many cellular processes such as cell differentiation and gene expression. The knowledge about the 4mC sites is a key foundation to exploring its roles. Due to the limitatio...

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigation.

Computers in biology and medicine
BACKGROUND: The O6-methylguanine-DNA methyltransferase (MGMT) is a deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential clinical brain tumor biomarker for Glioblastoma Multiforme (GBM). Knowing the status of MGMT met...

Prediction of designer-recombinases for DNA editing with generative deep learning.

Nature communications
Site-specific tyrosine-type recombinases are effective tools for genome engineering, with the first engineered variants having demonstrated therapeutic potential. So far, adaptation to new DNA target site selectivity of designer-recombinases has been...