AIMC Topic: DNA

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PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine.

BMC bioinformatics
BACKGROUND: Identifying specific residues for protein-DNA interactions are of considerable importance to better recognize the binding mechanism of protein-DNA complexes. Despite the fact that many computational DNA-binding residue prediction approach...

Prediction of DNA-Binding Residues in Local Segments of Protein Sequences with Fuzzy Cognitive Maps.

IEEE/ACM transactions on computational biology and bioinformatics
While protein-DNA interactions are crucial for a wide range of cellular functions, only a small fraction of these interactions was annotated to date. One solution to close this annotation gap is to employ computational methods that accurately predict...

Physicochemical property based computational scheme for classifying DNA sequence elements of Saccharomyces cerevisiae.

Computational biology and chemistry
GenerationE of huge "omics" data necessitates the development and application of computational methods to annotate the data in terms of biological features. In the context of DNA sequence, it is important to unravel the hidden physicochemical signatu...

Unlocking the hidden talent of DNA: Unexpected catalytic activity for colorimetric assay of alkaline phosphatase.

Analytica chimica acta
Carboxylic acids have been efficiently used to activate HO to form even more potent oxidant-peroxy acids through enzyme-catalyzed processes. By employing acetic acid as the activator, herein we report for the first time that cofactor-free DNA display...

An SVM-based method for assessment of transcription factor-DNA complex models.

BMC bioinformatics
BACKGROUND: Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex struc...

Setting Up a Surface-Enhanced Raman Scattering Database for Artificial-Intelligence-Based Label-Free Discrimination of Tumor Suppressor Genes.

Analytical chemistry
The quality of input data in deep learning is tightly associated with the ultimate performance of the machine learner. Taking advantage of the unique merits of surface-enhanced Raman scattering (SERS) methodology in the collection and construction of...

Porcine single nucleotide polymorphisms and their functional effect: an update.

BMC research notes
OBJECTIVE: To aid in the development of a comprehensive list of functional variants in the swine genome, single nucleotide polymorphisms (SNP) were identified from whole genome sequence of 240 pigs. Interim data from 72 animals in this study was publ...

Deep learning identifies genome-wide DNA binding sites of long noncoding RNAs.

RNA biology
Long noncoding RNAs (lncRNAs) can exert their function by interacting with the DNA via triplex structure formation. Even though this has been validated with a handful of experiments, a genome-wide analysis of lncRNA-DNA binding is needed. In this pap...

Sensitive detection of uracil-DNA glycosylase (UDG) activity based on terminal deoxynucleotidyl transferase-assisted formation of fluorescent copper nanoclusters (CuNCs).

Talanta
As an important base excision repair (BER) enzyme, uracil-DNA glycosylase (UDG) can repair the uracil-induced DNA lesion and maintain the genomic integrity. Herein, we have proposed a sensitive UDG assay based on the terminal deoxynucleotidyl transfe...

Deepbinner: Demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks.

PLoS computational biology
Multiplexing, the simultaneous sequencing of multiple barcoded DNA samples on a single flow cell, has made Oxford Nanopore sequencing cost-effective for small genomes. However, it depends on the ability to sort the resulting sequencing reads by barco...