Biclustering is an unsupervised machine-learning technique that simultaneously clusters
rows and columns in a data matrix. Over the past two decades, the field of biclustering has …

Gene co-expression networks can be used to associate genes of unknown function with
biological processes, to prioritize candidate disease genes or to discern transcriptional …

Biclustering is a powerful data mining technique that allows clustering of rows and columns,
simultaneously, in a matrix-format data set. It was first applied to gene expression data in …

Chemotherapy is the preferred treatment for advanced ovarian cancer, but the 5-year
survival rate remains low partly because of the development of drug resistance. Although it …

Lymphovascular invasion (LVI), the presence of malignant cells within lymphovascular
channels, is a crucial step in the invasion-metastasis cascade. LVI, when identified …

Analysis of gene expression data is widely used in transcriptomic studies to understand
functions of molecules inside a cell and interactions among molecules. Differential co …

Increasing evidence has shown that microRNAs played an important role in regulating
carcinogenesis. However, the role of miR-29a in breast cancer is still unclear. Herein, we …

Background This study aimed to draw a series of scientific maps to quantitatively and
qualitatively evaluate hot spots and trends in postmenopausal osteoporosis research using …

Purpose Individualization of therapeutic outcomes in NSCLC radiotherapy is likely to be
compromised by the lack of proper balance of biophysical factors affecting both tumor local …

The purpose of this paper is to demonstrate that a Bayesian network (BN) approach can
explore hierarchical biophysical relationships that influence tumor response and predict …