AIMC Topic: DNA

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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...

Mechano-fluorescence actuation in single synaptic vesicles with a DNA framework nanomachine.

Science robotics
Biomimetic machines that can convert mechanical actuation to adaptive coloration in a manner analogous to cephalopods have found widespread applications at various length scales. At the nanoscale, a transmutable nanomachine with adaptive colors that ...

Protein-DNA Binding Residue Prediction via Bagging Strategy and Sequence-Based Cube-Format Feature.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-DNA interactions play an important role in diverse biological processes. Accurately identifying protein-DNA binding residues is a critical but challenging task for protein function annotations and drug design. Although wet-lab experimental me...

CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networks.

Gene
DNA-binding proteins play a vital role in biological activity including DNA replication, DNA packing, and DNA reparation. DNA-binding proteins can be classified into single-stranded DNA-binding proteins (SSBs) or double-stranded DNA-binding proteins ...

iEnhancer-DCLA: using the original sequence to identify enhancers and their strength based on a deep learning framework.

BMC bioinformatics
Enhancers are small regions of DNA that bind to proteins, which enhance the transcription of genes. The enhancer may be located upstream or downstream of the gene. It is not necessarily close to the gene to be acted on, because the entanglement struc...