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comprna/reorientexpress: first release

angelrure; Akanksha2511; Eduardo Eyras


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3528433", 
  "title": "comprna/reorientexpress: first release", 
  "issued": {
    "date-parts": [
      [
        2019, 
        11, 
        5
      ]
    ]
  }, 
  "abstract": "<p>This is the first release of ReorientExpress,&nbsp;a program to create, test and apply models to predict the 5&#39;-to-3&#39; orientation of long-reads from cDNA sequencing with Nanopore or PacBio using deep neural networks for samples without a genome or a transcriptome reference.&nbsp;ReorientExpress implements two Deep Neural Network models: a Multi-Layer Perceptron (MLP) and a Convolutional Neural Network (CNN), and it uses as training input a transcriptome annotation from any species or any other fasta/fasq file of RNA/cDNA sequences for which the orientation is known. Training or testing data can thus be experimental data, annotation data or also mapped reads (providing the corresponding PAF file).</p>", 
  "author": [
    {
      "family": "angelrure"
    }, 
    {
      "family": "Akanksha2511"
    }, 
    {
      "family": "Eduardo Eyras"
    }
  ], 
  "version": "v1.0.0", 
  "type": "article", 
  "id": "3528433"
}
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