AIMC Topic: DNA
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iEnhancer-RD: Identification of enhancers and their strength using RKPK features and deep neural networks.
Analytical biochemistry
Aug 5, 2021
Enhancers are regulatory elements involved in gene expression.It is a part of DNA, which can enhance the transcription rate of gene. However, the identification of enhancer by biological experimental methods is time-consuming and expensive. Therefore...
Machine Learning Aids Classification and Discrimination of Noncanonical DNA Folding Motifs by an Arrayed Host:Guest Sensing System.
Journal of the American Chemical Society
Aug 4, 2021
An arrayed host:guest fluorescence sensor system can discriminate among and classify multiple different noncanonical DNA structures by exploiting selective molecular recognition. The sensor is highly selective and can discriminate between folds as si...
iDNA6mA-Rice-DL: A local web server for identifying DNA N6-methyladenine sites in rice genome by deep learning method.
Journal of bioinformatics and computational biology
Jul 21, 2021
Accurate detection of N6-methyladenine (6mA) sites by biochemical experiments will help to reveal their biological functions, still, these wet experiments are laborious and expensive. Therefore, it is necessary to introduce a powerful computational m...
A deep learning model for predicting next-generation sequencing depth from DNA sequence.
Nature communications
Jul 19, 2021
Targeted high-throughput DNA sequencing is a primary approach for genomics and molecular diagnostics, and more recently as a readout for DNA information storage. Oligonucleotide probes used to enrich gene loci of interest have different hybridization...
A machine learning approach for accurate and real-time DNA sequence identification.
BMC genomics
Jul 9, 2021
BACKGROUND: The all-electronic Single Molecule Break Junction (SMBJ) method is an emerging alternative to traditional polymerase chain reaction (PCR) techniques for genetic sequencing and identification. Existing work indicates that the current spect...
Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer-promoter contact.
Nature communications
Jun 8, 2021
Chromatin architecture plays an important role in gene regulation. Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. However, leveraging these comple...
FTIR spectroscopy with machine learning: A new approach to animal DNA polymorphism screening.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jun 1, 2021
Technological advances in recent decades, especially in molecular genetics, have enabled the detection of genetic DNA markers associated with productive characteristics in animals. However, the prospection of polymorphisms based on DNA sequencing is ...
i4mC-EL: Identifying DNA N4-Methylcytosine Sites in the Mouse Genome Using Ensemble Learning.
BioMed research international
May 29, 2021
As one of important epigenetic modifications, DNA N4-methylcytosine (4mC) plays a crucial role in controlling gene replication, expression, cell cycle, DNA replication, and differentiation. The accurate identification of 4mC sites is necessary to und...
Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics.
Molecular diversity
May 24, 2021
Convolutional neural networks (CNNs) have been used to extract information from various datasets of different dimensions. This approach has led to accurate interpretations in several subfields of biological research, like pharmacogenomics, addressing...
DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence.
International journal of molecular sciences
May 24, 2021
Predicting in vivo protein-DNA binding sites is a challenging but pressing task in a variety of fields like drug design and development. Most promoters contain a number of transcription factor (TF) binding sites, but only a small minority has been id...
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