The discovery of novel cancer genes is one of the main goals in cancer research.
Bioinformatics methods can be used to accelerate cancer gene discovery, which may help in …

The distinctive nature of cancer as a disease prompts an exploration of the special
characteristics the genes implicated in cancer exhibit. The identification of cancer …

Background Identification of novel cancer-causing genes is one of the main goals in cancer
research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in …

Machine learning techniques are of great importance in the analysis of microarray
expression data, and provide a systematic and promising way to predict core cancer genes …

Background Extensive biomedical studies have shown that clinical and environmental risk
factors may not have sufficient predictive power for cancer prognosis. The development of …

Motivation: Diagnosis and prognosis of cancer and understanding oncogenesis within the
context of biological pathways is one of the most important research areas in bioinformatics …

Triple-negative breast cancer (TNBC), colon adenocarcinoma (COAD), ovarian cancer (OV),
and glioblastoma multiforme (GBM) are common malignant tumors, in which significant …

Disease gene prediction is an essential issue in biomedical research. In the early days,
annotation-based approaches were proposed for this problem. With the development of high …

Developing a biomedical-explainable and validatable text mining pipeline can help in
cancer gene panel discovery. We create a pipeline that can contextualize genes by using …

With the advances in gene sequencing technologies, millions of somatic mutations have
been reported in the past decades, but mining cancer driver genes with oncogenic …