We propose a new method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis （...We propose a new method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis （ICA）. Secondly, the most discriminant eigenassays extracted by ICA are selected by the sequential floating forward selection technique. Finally, support vector machine is used to classify the modeling data. To show the validity of the proposed method, we applied it to classify three DNA microarray datasets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible.展开更多
It is our great honor to announce the publication of this special section on AI and big data analytics in biology and medicine in the Journal of Computing Science and Technology(JCST).As more and more modern biologica...It is our great honor to announce the publication of this special section on AI and big data analytics in biology and medicine in the Journal of Computing Science and Technology(JCST).As more and more modern biological and medical data are produced,artificial intelligence(AI)and big data analytics are playing an increasingly important role in helping to draw meaningful and logical conclusions about biology and medicine.展开更多
基金the National Natural Sci-ence Foundation of China (No. 30700161)the Na-tional High-Tech Research and Development Program(863 Program) of China (No. 2007AA01Z167 and2006AA02Z309)+1 种基金China Postdoctoral Science Foun-dation (No. 20070410223)Doctor Scientific Re-search Startup Foundation of Qufu Normal University(No. Bsqd2007036).
文摘We propose a new method for tumor classification from gene expression data, which mainly contains three steps. Firstly, the original DNA microarray gene expression data are modeled by independent component analysis （ICA）. Secondly, the most discriminant eigenassays extracted by ICA are selected by the sequential floating forward selection technique. Finally, support vector machine is used to classify the modeling data. To show the validity of the proposed method, we applied it to classify three DNA microarray datasets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible.
文摘It is our great honor to announce the publication of this special section on AI and big data analytics in biology and medicine in the Journal of Computing Science and Technology(JCST).As more and more modern biological and medical data are produced,artificial intelligence(AI)and big data analytics are playing an increasingly important role in helping to draw meaningful and logical conclusions about biology and medicine.
