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MKL-GRNI: A parallel multiple kernel learning approach for supervised inference of large-scale gene regulatory networks
High throughput multi-omics data generation coupled with heterogeneous genomic data fusion are defining new ways to build computational inference models. These models are scalable and can support very large genome sizes with the added advantage of exploiting additional biological knowledge from the...
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| Vydáno v: | PeerJ Comput Sci |
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| Hlavní autoři: | , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
PeerJ Inc.
2021
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7924726/ https://ncbi.nlm.nih.gov/pubmed/33817013 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.363 |
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