Image segmentation: a competitive approach
Image segmentation: a competitive approach
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Predicting protein structure and function using machine learning methods
Predicting protein structure and function using machine learning methods
Invited talk: a computational study of bidirectional promoters in the human genome
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
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Recently, the National Human Genome Research Institute and National Cancer Institute, both part of NIH, US Department of Health and Human Services, have launched The Cancer Genome Atlas (TCGA). Based on the mission of TCGA, we have proposed a further parallel paradigm on cancer: it is not only the genetic changes (i.e., mutations of genes) but also changes of gene expressions and regulatory networks that are ultimately responsible for cancer development. Under this parallel paradigm, un-mutated genes with differential expressions and alternative splicing may also induce changes in the differential regulatory networks that also cause cancer when cells are subjected to unusual environments. We developed a novel synergistic computational intelligence and bioinformatics approach to predict malignancies of neuroendocrine tumours that are particularly important to discover the mechanisms of human genome mechanisms relating malignant transformation.