One of the most important and challenging problems in biomedicine and genomics is how to
identify the disease genes. In this study, we developed a computational method to identify …

Hepatocellular carcinoma (HCC) is the most common type of liver cancer worldwide and
one of the deadliest cancers in Asia. But at present, effective targets for HCC clinical therapy …

Identifying candidate disease genes is important to improve medical care. However, this task
is challenging in the post-genomic era. Several computational approaches have been …

One key issue in the post-genomic era is how to systematically describe the associations
between small molecule transcripts or translations inside cells. With the rapid development …

This study was designed to identify the potential key protein interaction networks, genes,
and correlated pathways in early-onset colorectal cancer (CRC) via bioinformatics methods …

Colorectal cancer (CRC) is one of the most common malignancies worldwide. Biomarker
discovery is critical to improve CRC diagnosis, however, machine learning offers a new …

Background The purpose of this study was using bioinformatics tools to identify biomarkers
and molecular factors involved in the diagnosis of colorectal cancer, which are effective for …

Here we intend to identify key genes and pathways in the pathogenesis of colorectal cancer
(CRC) through analyzing microarray data with bioinformatic tools. The gene expression …

Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics
research has generated a large amount of data; however, only a very small amount has …

Background Cancer is a complex disease. So far, many genes have been reported to
involve in the development of cancer. Rather than the traditional approach to studying …