Publications by authors named "Jeanette A I Johnson"
Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we introduce a suite of computational tools that implement NMF and provide methods for accurate and clear biological interpretation and analysis.
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- The paper presents a conceptual framework called "cell behavior hypothesis grammar," which translates biological knowledge into natural language statements to create computational models.
- This approach enables researchers to conduct virtual experiments that enhance understanding of complex multicellular systems, particularly in areas like tumor biology and immunotherapy, while fostering collaboration across various biological research fields.