Leveraging Heterogeneous Network Embedding for Metabolic Pathway Prediction
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Updated
Jul 8, 2021 - Python
Leveraging Heterogeneous Network Embedding for Metabolic Pathway Prediction
Metabolic pathway inference using multi-label classification with rich pathway features
reMap: relabeling metabolic pathway data with groups to improve prediction outcomes
prepBioCyc: Preprocess BioCyc files
Metabolic pathway inference using non-negative matrix factorization with community detection
Metagenomic functional profiling pipeline for reconstructing metabolic pathway abundances and gene families from shotgun sequencing reads. Automates marker-based taxonomic profiling and translated search to quantify community-wide metabolic potential and taxonomically attribute metabolic functions.
CHAP: Modeling Metabolic Pathways as Groups (with Augmentation)
leADS: improved metabolic pathway inference based on active dataset subsampling
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