Identifying effective biomarkers to battle complex diseases is an important but challenging
task in biomedical research today. Molecular data of complex diseases is increasingly …

Background Finding reliable gene markers for accurate disease classification is very
challenging due to a number of reasons, including the small sample size of typical clinical …

Background Discovering robust markers for cancer prognosis based on gene expression
data is an important yet challenging problem in translational bioinformatics. By integrating …

Biomarkers play an important role in the field of medicine. Over the past decade, a
significant amount of data has been generated by high-throughput analysis, such as …

Biomarkers with high reproducibility and accurate prediction performance can contribute to
comprehending the underlying pathogenesis of related complex diseases and further …

Background Identification of protein interaction network is a very important step for
understanding the molecular mechanisms in cancer. Several methods have been …

Background Identifying biomarkers for accurate diagnosis and prognosis of diseases is
important for the prevention of disease development. The molecular networks that describe …

Rapid progress in high-throughput-omics technologies moves us one step closer to the
datacalypse in life sciences. In spite of the already generated volumes of data, our …

Networks-based approaches are often used to analyze gene expression data or protein–
protein interactions but are not usually applied to study the relationships between different …

Due to technological advances the quality and availability of biological data has increased
dramatically in the last decade. Analysing protein-protein interaction networks (PPINs) in an …