AIMC Topic: DNA

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Development of amino functionalized carbon coated magnetic nanoparticles and their application to electrochemical detection of hybridization of nucleic acids.

Talanta
In our study, the development of amino functionalized carbon coated magnetic nanoparticles (NH-CC-MNPs) and their usage for electrochemical detection of hybridization of nucleic acids have been aimed. Firstly, NH-CC-MNPs were prepared by coating of p...

Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Through sequence-based classification, this paper tries to accurately predict the DNA binding sites of transcription factors (TFs) in an unannotated cellular context. Related methods in the literature fail to perform such predictions accurately, sinc...

Restarting and recentering genetic algorithm variations for DNA fragment assembly: The necessity of a multi-strategy approach.

Bio Systems
DNA Fragment assembly - an NP-Hard problem - is one of the major steps in of DNA sequencing. Multiple strategies have been used for this problem, including greedy graph-based algorithms, deBruijn graphs, and the overlap-layout-consensus approach. Thi...

gDNA-Prot: Predict DNA-binding proteins by employing support vector machine and a novel numerical characterization of protein sequence.

Journal of theoretical biology
DNA-binding proteins are the functional proteins in cells, which play an important role in various essential biological activities. An effective and fast computational method gDNA-Prot is proposed to predict DNA-binding proteins in this paper, which ...

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences.

Nucleic acids research
Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of fun...

Classifying Force Spectroscopy of DNA Pulling Measurements Using Supervised and Unsupervised Machine Learning Methods.

Journal of chemical information and modeling
Dynamic force spectroscopy (DFS) measurements on biomolecules typically require classifying thousands of repeated force spectra prior to data analysis. Here, we study classification of atomic force microscope-based DFS measurements using machine-lear...

Recombination spot identification Based on gapped k-mers.

Scientific reports
Recombination is crucial for biological evolution, which provides many new combinations of genetic diversity. Accurate identification of recombination spots is useful for DNA function study. To improve the prediction accuracy, researchers have propos...

LS-GKM: a new gkm-SVM for large-scale datasets.

Bioinformatics (Oxford, England)
UNLABELLED: gkm-SVM is a sequence-based method for predicting and detecting the regulatory vocabulary encoded in functional DNA elements, and is a commonly used tool for studying gene regulatory mechanisms. Here we introduce new software, LS-GKM, whi...

Predicting transcription factor site occupancy using DNA sequence intrinsic and cell-type specific chromatin features.

BMC bioinformatics
BACKGROUND: Understanding the mechanisms by which transcription factors (TF) are recruited to their physiological target sites is crucial for understanding gene regulation. DNA sequence intrinsic features such as predicted binding affinity are often ...

On fuzzy semantic similarity measure for DNA coding.

Computers in biology and medicine
A coding measure scheme numerically translates the DNA sequence to a time domain signal for protein coding regions identification. A number of coding measure schemes based on numerology, geometry, fixed mapping, statistical characteristics and chemic...