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Identifying Relevant Data for a Biological Database: Handcrafted Rules Versus Machine Learning
With well over one thousand specialized biological databases in use today, the task of automatically identifying novel, relevant data for such databases is increasingly important. In this paper, we describe practical machine learning approaches for identifying MEDLINE documents and Swiss-Prot/TrEMBL...
Gorde:
| Egile Nagusiak: | , , , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2011
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3980937/ https://ncbi.nlm.nih.gov/pubmed/21393656 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TCBB.2009.83 |
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