Gene set analysis methods are widely used to provide insight into high-throughput gene
expression data. There are many gene set analysis methods available. These methods rely …

With growing interest in machine learning (ML), it is essential to understand the
methodologies used for evaluating ML models to achieve reproducible solutions that can be …

Artificial intelligence (AI) is revolutionizing many industries by performing tasks that typically
require human intelligence to solve. AI contributes to complex scientific and engineering …

Similarities and differences in the associations of biological entities among species can
provide us with a better understanding of evolutionary relationships. Often the evolution of …

Purpose To investigate the impact of the following three methodological pitfalls on model
generalizability:(a) violation of the independence assumption,(b) model evaluation with an …

As health data and computer power become increasingly available, the main challenge is to
gain actionable insight from these data. Machine learning (ML) methods have proved to be a …

Background Gene set analysis is a well-established approach for interpretation of data from
high-throughput gene expression studies. Achieving reproducible results is an essential …

Introduction: Delta checks use two specimen test results taken in succession in order to
detect test result changes greater than expected physiological variation. One of the most …

Background Gene co-expression networks (GCNs) are not easily comparable due to their
complex structure. In this paper, we propose a tool, Juxtapose, together with similarity …

During endochondral ossification, chondrocytes secrete a proteoglycan (PG)-rich
extracellular matrix that can inhibit the process of cartilage maturation, including expression …