Despite massive investments in drug research and development, the significant decline in
the number of new drugs approved or translated to clinical use raises the question, whether …

One of the central tasks of genome research is to predict phenotypes and discover some
important gene biomarkers. However, there are three main problems in analyzing genomics …

Feature selection is an important research area for big data analysis. In recent years, various
feature selection approaches have been developed, which can be divided into four …

Increasingly amounts of biological data promote the development of various penalized
regression models. This review discusses the recent advances in both linear and logistic …

Triple-negative breast cancer (TNBC) is a subtype of aggressive breast cancer with high
recurrence and poor survival. Emerging evidence has indicated that long non-coding RNAs …

Cancer classification and feature (gene) selection plays an important role in knowledge
discovery in genomic data. Although logistic regression is one of the most popular …

Multi-omics data integration is a promising field combining various types of omics data, such
as genomics, transcriptomics, and proteomics, to comprehensively understand the …

Feature selection on a network structure can not only discover interesting variables but also
mine out their intricate interactions. Regularization is often employed to ensure the sparsity …

Background The aim of this study was to develop an effective surgical site infection (SSI)
prediction model in patients receiving free-flap reconstruction after surgery for head and …

Background: Lung adenocarcinoma (LUAD) is a heterogeneous disease characterized by
high mortality and poor prognosis. Ferroptosis, a newly discovered iron-dependent type of …