计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 219-221.doi: 10.11896/j.issn.1002-137X.2016.6A.053
赵婧,魏彬,张瑾
ZHAO Jing, WEI Bin and ZHANG Jin
摘要: 作为第三代遗传标记的单核苷酸多态性(SNP)具有数量众多、分布广泛且遗传稳定性等特点,其是疾病-基因相关性以及药物设计等研究的基础所在。这类研究多采用基于计算的方法,因此如何对SNP进行适当的编码进而提升算法的性能是其中十分关键的一个环节,然而目前专门针对SNP编码问题的研究还相对较少。在常用SNP表示方式的基础上,根据疾病易感性研究的特点,并结合SNP之间的关联性,提出了几种新的编码方法。大量实验表明,编码方式对疾病易感性分析算法的性能有着较大的影响,基于分布信息的编码方法能获得更好的结果,即其能更好地对SNP序列进行描述,在最大程度上保留原有生物序列所携带的丰富信息,更适合于疾病易感性研究。
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