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Smart computational exploration of stochastic gene regulatory network models using human-in-the-loop semi-supervised learning
MOTIVATION: Discrete stochastic models of gene regulatory network models are indispensable tools for biological inquiry since they allow the modeler to predict how molecular interactions give rise to nonlinear system output. Model exploration with the objective of generating qualitative hypotheses a...
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| Publicado no: | Bioinformatics |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6954658/ https://ncbi.nlm.nih.gov/pubmed/31141124 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btz420 |
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