You can view the full text of this article for free using the link below.

Title: Scientific Review: A new insight on predicting tumour malignancies using synergistic computational intelligence and bioinformatics approaches

Authors: Jack Y. Yang, Andrzej Niemierko, Zuojie Luo, Mary Qu Yang

Addresses: Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, Massachusetts 02114, USA. ' Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, Massachusetts 02114, USA. ' Office of the University Provost and Dean of Academic Affairs, Guangxi Medical University and the First Affiliated Hospital, Nanning, Guangxi 530021, China. ' National Human Genome Research Institute, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD 20852 USA; Oak Ridge, D.O.E., USA

Abstract: 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.

Keywords: computational intelligence; bioinformatics; parallel paradigm; benign tumours; malignant transformation; tumour malignancies; cancer genome atlas; genetic changes; gene mutation; gene expressions; regulatory networks; cancer development; neuroendocrine tumours.

DOI: 10.1504/IJCIBSB.2009.024040

International Journal of Computational Intelligence in Bioinformatics and Systems Biology, 2009 Vol.1 No.1, pp.4 - 14

Available online: 24 Mar 2009

Full-text access for editors Access for subscribers Free access Comment on this article