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DNA

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DIRECTION: a machine learning framework for predicting and characterizing DNA methylation and hydroxymethylation in mammalian genomes.

Bioinformatics (Oxford, England)
MOTIVATION: 5-Methylcytosine and 5-Hydroxymethylcytosine in DNA are major epigenetic modifications known to significantly alter mammalian gene expression. High-throughput assays to detect these modifications are expensive, labor-intensive, unfeasible...

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

Journal of the Optical Society of America. A, Optics, image science, and vision
This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DN...

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signa...

Primer on the Gene Ontology.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essent...

The Gene Ontology and the Meaning of Biological Function.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) provides a framework and set of concepts for describing the functions of gene products from all organisms. It is specifically designed for supporting the computational representation of biological systems. A GO annotation is an...

Convolutional neural network architectures for predicting DNA-protein binding.

Bioinformatics (Oxford, England)
MOTIVATION: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA-protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth...

High throughput preparation of fly genomic DNA in 96-well format using a paint-shaker.

Fly
Sample homogenization is an essential step for genomic DNA extraction, with multiple downstream applications in Molecular Biology. Genotyping hundreds or thousands of samples requires an automation of this homogenization step, and high throughput hom...