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BGRMI: A method for inferring gene regulatory networks from time-course gene expression data and its application in breast cancer research
Reconstructing gene regulatory networks (GRNs) from gene expression data is a challenging problem. Existing GRN reconstruction algorithms can be broadly divided into model-free and model–based methods. Typically, model-free methods have high accuracy but are computation intensive whereas model-based...
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| 出版年: | Sci Rep |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Nature Publishing Group
2016
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5120305/ https://ncbi.nlm.nih.gov/pubmed/27876826 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/srep37140 |
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