A partially function-to-topic model for protein function prediction

Prescription Function Prediction Using Topic Model and Multilabel Classifiers

Determining a prescription's function is one of the challenging problems in Traditional Chinese Medicine (TCM). In past decades, TCM has been widely researched through various methods in computer science, but none concentrates on the prediction method for a new prescription's function. In this study, two methods are presented concerning this issue. The first method is based on a novel supervise...

A review of text mining approaches and their function in discovering and extracting a topic

Background and aim: Four text mining methods are examined and focused on understanding and identifying their properties and limitations in subject discovery. Methodology: The study is an analytical review of the literature of text mining and topic modeling.  Findings: LSA could be used to classify specific and unique topics in documents that address only a single topic. The other three text min...

Hierarchical Ensemble Methods for Protein Function Prediction

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relations...

Integrating Information for Protein Function Prediction

Mining Phenotypes for Protein Function Prediction

Until very recently, phenotypes only very rarely were studied in a systematic manner. While ontologies for describing gene functions now have a 10 year long tradition, similar vocabularies for describing the phenotype of genes are only emerging now; similarly, the techniques for determining phenotypes on a large scale (especially RNAi) are available only for a few years, while genomic sequencin...