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Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities.

Bioinformatics (Oxford, England)
MOTIVATION: Deep learning architectures have recently demonstrated their power in predicting DNA- and RNA-binding specificity. Existing methods fall into three classes: Some are based on convolutional neural networks (CNNs), others use recurrent neur...

Deep learning: new computational modelling techniques for genomics.

Nature reviews. Genetics
As a data-driven science, genomics largely utilizes machine learning to capture dependencies in data and derive novel biological hypotheses. However, the ability to extract new insights from the exponentially increasing volume of genomics data requir...

Deep repeat resolution-the assembly of the Drosophila Histone Complex.

Nucleic acids research
Though the advent of long-read sequencing technologies has led to a leap in contiguity of de novo genome assemblies, current reference genomes of higher organisms still do not provide unbroken sequences of complete chromosomes. Despite reads in exces...

A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential.

Nucleic acids research
The current deluge of newly identified RNA transcripts presents a singular opportunity for improved assessment of coding potential, a cornerstone of genome annotation, and for machine-driven discovery of biological knowledge. While traditional, featu...

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning.

GigaScience
Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex elec...

MetaVW: Large-Scale Machine Learning for Metagenomics Sequence Classification.

Methods in molecular biology (Clifton, N.J.)
Metagenomics is the study of microbial community diversity, especially the uncultured microorganisms by shotgun sequencing environmental samples. As the sequencers throughput and the data volume increase, it becomes challenging to develop scalable bi...

Estimation of hydraulic jump characteristics of channels with sudden diverging side walls via SVM.

Water science and technology : a journal of the International Association on Water Pollution Research
Sudden diverging channels are one of the energy dissipaters which can dissipate most of the kinetic energy of the flow through a hydraulic jump. An accurate prediction of hydraulic jump characteristics is an important step in designing hydraulic stru...

A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data.

Nucleic acids research
Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-s...