pVR uses a bi-filtration combining p-adic and compositional distances to generate topological features that improve classification accuracy on several low-sample genomic benchmarks.
Cakl: Commutative algebra k-mer learning of genomics,
2 Pith papers cite this work. Polarity classification is still indexing.
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CAL applies commutative algebra to build multi-scale localized descriptors for protein B-factor prediction, claiming 34.5% improvement over GNM on 364 proteins.
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$p$-adic Bi-Filtrations for Topological Machine Learning on Genomic Sequences
pVR uses a bi-filtration combining p-adic and compositional distances to generate topological features that improve classification accuracy on several low-sample genomic benchmarks.
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Commutative Algebra Learning for Protein Flexibility Analysis
CAL applies commutative algebra to build multi-scale localized descriptors for protein B-factor prediction, claiming 34.5% improvement over GNM on 364 proteins.