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Sequence Analysis, DNA

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Genome-wide pre-miRNA discovery from few labeled examples.

Bioinformatics (Oxford, England)
MOTIVATION: Although many machine learning techniques have been proposed for distinguishing miRNA hairpins from other stem-loop sequences, most of the current methods use supervised learning, which requires a very good set of positive and negative ex...

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...

Genotyping of Giardia duodenalis in vegetables cultivated with organic and chemical fertilizer from street markets and community vegetable gardens in a region of Southern Brazil.

Transactions of the Royal Society of Tropical Medicine and Hygiene
BACKGROUND: In order to investigate the occurrence of Giardia duodenalis and its genotypes in vegetables that are consumed raw, we analyzed samples cultivated with organic or chemical fertilizer, sold in street markets and from community vegetable ga...

DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

Bioinformatics (Oxford, England)
MOTIVATION: Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of ...

MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive.

Bioinformatics (Oxford, England)
MOTIVATION: The NCBI's Sequence Read Archive (SRA) promises great biological insight if one could analyze the data in the aggregate; however, the data remain largely underutilized, in part, due to the poor structure of the metadata associated with ea...

Denoising genome-wide histone ChIP-seq with convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Chromatin immune-precipitation sequencing (ChIP-seq) experiments are commonly used to obtain genome-wide profiles of histone modifications associated with different types of functional genomic elements. However, the quality of histone ChI...

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...

HIPred: an integrative approach to predicting haploinsufficient genes.

Bioinformatics (Oxford, England)
MOTIVATION: A major cause of autosomal dominant disease is haploinsufficiency, whereby a single copy of a gene is not sufficient to maintain the normal function of the gene. A large proportion of existing methods for predicting haploinsufficiency inc...

TSSPlant: a new tool for prediction of plant Pol II promoters.

Nucleic acids research
Our current knowledge of eukaryotic promoters indicates their complex architecture that is often composed of numerous functional motifs. Most of known promoters include multiple and in some cases mutually exclusive transcription start sites (TSSs). M...

Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily l...