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| 1 | Identification of SNP-containing regulatory motifs in the myelodysplastic syndromes model using SNP arrays and gene expression arrays显示文摘Myelodysplastic syndromes have increased in frequency and incidence in the American population, but patient prognosis has not significantly improved over the last decade. Such improvements could be realized if biomarkers for accurate diagnosis and prognostic stratification were successfully identified. In this study, we propose a method that associates two state-of-the-art array technologies-single nucleotide polymorphism (SNP) array and gene expression array-with gene motifs considered transcription factor -binding sites (TFBS). We are particularly interested in SNP-containing motifs introduced by genetic variation and mutation as TFBS. The potential regulation of SNP-containing motifs affects only when certain mutations occur. These motifs can be identified from a group of co-expressed genes with copy number variation. Then, we used a sliding window to identify motif candidates near SNPs on gene sequences. The candidates were filtered by coarse thresholding and fine statistical testing. Using the regression-based LARS-EN algorithm and a level-wise sequence combination procedure, we identified 28 SNP-containing motifs as candidate TFBS. We confirmed 21 of the 28 motifs with ChIP-chip fragments in the TRANSFAC database. Another six motifs were validated by TRANSFAC via searching binding fragments on coregulated genes. The identified motifs and their location genes can be considered potential biomarkers for myelodysplastic syndromes. Thus, our proposed method, a novel strategy for associating two data categories, is capable of integrating information from different sources to identify reliable candidate regulatory SNP-containing motifs introduced by genetic variation and mutation. | Jing Fan Jennifer G. Dy Chung-Che Chang Xiaobo Zhou | 2013 | Chinese Journal of Cancer2013，32，4： | 2 |
| 2 | 2004年~2013年肺癌患病风险基因相关临床研究文献的计量学分析显示文摘目的掌握近10年来国内外肺癌患病风险基因相关临床研究动态。方法以Embase、Pubmed为文献检索数据库(2004年1月至2013年12月),分别对纳入文献的出版年、国家、期刊、研究机构、作者及所研究基因进行计量学分析。结果该领域年发文量一直较多,2004年到2008年缓慢增长,2008年后则趋向平缓;发文量最多的国家、期刊、机构及作者分别为美国、《Lung Cancer》(肺癌)、MD Anderson Cancer Center(美国MD安德森癌症中心)、Park JY;该领域共统计出相关基因312个,其中以p53和CDKN1A基因研究最多。结论肺癌患病风险基因相关临床研究仍受广大研究员关注,且涉及基因种类繁多,寻找有特异性和敏感性的基因至关重要。 | 邹建军 苏珊 张贤兰 黄惠怡 岑文昌 | 2015 | 分子诊断与治疗杂志2015，7，4： | 2 |
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