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Athena: Automated Tuning of k-mer based Genomic Error Correction Algorithms using Language Models
The performance of most error-correction (EC) algorithms that operate on genomics reads is dependent on the proper choice of its configuration parameters, such as the value of k in k-mer based techniques. In this work, we target the problem of finding the best values of these configuration parameter...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834855/ https://www.ncbi.nlm.nih.gov/pubmed/31695060 http://dx.doi.org/10.1038/s41598-019-52196-4 |