Efforts at finding potential biomarkers of tolerance after kidney transplantation have been hindered by limited sample size, as well as the complicated mechanisms underlying tolerance and the potential risk of rejection after immunosuppressant withdr...
We investigate the feasibility of molecular-level sample classification of sepsis using microarray gene expression data merged by in silico meta-analysis. Publicly available data series were extracted from NCBI Gene Expression Omnibus and EMBL-EBI Ar...
Computational and mathematical methods in medicine
33986823
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based...
BACKGROUND: Nowadays we are observing an explosion of gene expression data with phenotypes. It enables us to accurately identify genes responsible for certain medical condition as well as classify them for drug target. Like any other phenotype data i...
Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic appr...
The quantity of data required to give a valid analysis grows exponentially as machine learning dimensionality increases. In a single experiment, microarrays or gene expression profiling assesses and determines gene expression levels and patterns in v...
Microarrays are applications of electrical engineering and technology in biology that allow simultaneous measurement of expression of numerous genes, and they can be used to analyze specific diseases. This study undertakes classification analyses of ...
Malignancies and diseases of various genetic origins can be diagnosed and classified with microarray data. There are many obstacles to overcome due to the large size of the gene and the small number of samples in the microarray. A combination strateg...
Digital PCR (dPCR) has recently attracted great interest due to its high sensitivity and accuracy. However, the existing dPCR depends on multicolor fluorescent dyes and multiple fluorescent channels to achieve multiplex detection, resulting in increa...
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative "smart" engine. A suite of advanced optical microsco...