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논문 기본 정보

자료유형
학술저널
저자정보
Lee, Min-Su (Department of Computer Science and Engineering, Ewha Womans University) Ahn, Jeong-Hyuck (Laboratory of Molecular and Cellular Neuroscience, Rockefeller University) Park, Woong-Yang (Human Genome Research Institute and Department of Biochemistry, Seoul National University College of Medicine)
저널정보
한국유전체학회 Genomics & informatics Genomics & informatics 제5권 제1호
발행연도
2007.1
수록면
1 - 5 (5page)

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Embryonic stem cells can be differentiated into various types of cells, requiring a tight regulation of transcription. Biomarkers related to each lineage of cells are used to guide the differentiation into neural or any other fates. In previous experiments, we reported the guided differentiation (GD)-specific genes by comparing profiles of random differentiation (RD). Interestingly 68% of differentially expressed genes in GD overlap with that of RD, which makes it difficult for us to separate the lineages by examining several markers. In this paper, we design a prediction model to identify the differentiation into neural fates from any other lineage. From the profiles of 11,376 genes, 203 differentially expressed genes between neural and random differentiation were selected by random variance T-test with 95% confidence and 5% false discovery rate. Based on support vector machine algorithm, we could select 79 marker genes from the 203 informative genes to construct the optimal prediction model. Here we propose a prediction model for the prediction of neural fates from random differentiation which is constructed with a perfect accuracy.

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