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Essential gene prediction using limited gene essentiality information–An integrative semi-supervised machine learning strategy
Essential gene prediction helps to find minimal genes indispensable for the survival of any organism. Machine learning (ML) algorithms have been useful for the prediction of gene essentiality. However, currently available ML pipelines perform poorly for organisms with limited experimental data. The...
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| 出版年: | PLoS One |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7703937/ https://ncbi.nlm.nih.gov/pubmed/33253254 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0242943 |
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