… To offset this limit, we applied pathway2vec (Basher and Hallam, 2020) by using the
RUST-norm (or “crt”) module to obtain pathway and EC features, indicated by and , respectively, …

The discovery of subtypes is pivotal for disease diagnosis and targeted therapy, considering
the diverse responses of different cells or patients to specific treatments. Exploring the …

Metabolic pathway prediction from genomic sequence information is an essential step in
determining the capacity of living things to transform matter and energy at different levels of …

Metabolic pathways are composed of reaction sequences catalyzed by enzymes. The set of
reactions within and between cells comprises a reactome. Pathways and reactomes can be …

… Basher and colleagues developed mlLGPR [12], a multi-label classification method that
uses logistic regression and feature vectors inspired by the work of Dale and colleagues [3] to …

Abstract Machine learning methods show great promise in predicting metabolic pathways at
different levels of biological organization. However, several complications remain that can …

We present reMap (relabeling multi-label pathway data based on bag approach), a simple,
and yet, generic framework, that performs relabeling examples to a different set of labels, …

Metabolic pathway reconstruction from genomic sequence information is a key step in predicting
regulatory and functional potential of cells at the individual, population and community …

Given a set of ECs with abundance information, we define the following four sets of features:
i)-reactions evidence features, ii)-pathways evidence features, iii)-pathway common features…

We outline the process of deriving the objective cost function. The target function in our
proposed model is the logistic regression, which represents the conditional probabilities through …