Abstract Multi-Label Classification (MLC) is an extension of the standard single-label
classification where each data instance is associated with several labels simultaneously …

Many molecular biosystems and biomedical systems belong to the multi-label systems in
which each of their constituent molecules possesses one or more than one function or …

The purpose of this paper is to analyze the imbalanced learning task in the multilabel
scenario, aiming to accomplish two different goals. The first one is to present specialized …

Learning from imbalanced data is a problem which arises in many real-world scenarios, so
does the need to build classifiers able to predict more than one class label simultaneously …

Identifying the location of proteins in a cell plays an important role in understanding their
functions, such as drug design, therapeutic target discovery and biological research …

Predicting protein subcellular localization is a challenging problem, particularly when query
proteins have multi-label features meaning that they may simultaneously exist at, or move …

Motivation A cell contains numerous protein molecules. One of the fundamental goals in cell
biology is to determine their subcellular locations, which can provide useful clues about their …

Early detection of retinal diseases is one of the most important means of preventing partial or
permanent blindness in patients. In this research, a novel multi-label classification system is …

In traditional wet experiments, fluorescent proteins are generally used to detect subcellular
localization of protein. However, it is time consuming and expensive for detecting large …

Background Although many computational methods have been developed to predict protein
subcellular localization, most of the methods are limited to the prediction of single-location …