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Integrative random forest for gene regulatory network inference
Motivation: Gene regulatory network (GRN) inference based on genomic data is one of the most actively pursued computational biological problems. Because different types of biological data usually provide complementary information regarding the underlying GRN, a model that integrates big data of dive...
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| Опубликовано в: : | Bioinformatics |
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| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Oxford University Press
2015
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4542785/ https://ncbi.nlm.nih.gov/pubmed/26072483 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btv268 |
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