利用条件随机场实现DNA剪接位点的预测

为解决传统的基因识别算法主要关注编码区的整体特性,而并不着重考虑个别位点的信息,因此难以准确地识别出剪接位点的缺点,提出了基于条件随机场的剪接位点预测方法,条件随机场能够更好的处理标记数据之间的依赖关系,并且能够避免数据标记偏置的问题。实验结果表明基于条件随机场的剪接位点预测方法是一种合适的方法,能够取得更好的效果。

Predicting the DNA splice sites with conditional random field

Predicting the DNA splice sites has become the most attractive and important issue in the field of genome information research due to its great help to find gene coding area.Current gene recognition algorithms mainly consider the global features of the coding area,instead of the specific information of the splicing sites,which are usually unable to recognize the splicing sites accurately.A new method based on the conditional random fields (CRFs) is proposed for splice sites prediction.CRFs can capture long distance dependent relationships between labels and avoid label bias.Experimental results show that CRFs is suitable for splice sites prediction and can improve performance.