中文摘要：

目前,生物遗传学领域在区分复杂性状的研究上正面临着巨大挑战,许多方法都被用来应对这项挑战,其中分子标记法,QTL作图法和序列分析法等就是用来区分控制复杂性状基因的主要应对策略。测定生物复杂性状对于研究生物多样性具有重要意义,也是进一步研究基因控制性状作用机理的重要途径,但是,现有的方法并不成熟也不完善,因此给有效区分复杂性状带来了一定难度。近年来,由于生长曲线能够有效地描述复杂性状,基于生长曲线来区分复杂性状的方法是目前常用的方式,Functional Mapping（FM）就是其中具有代表性的一种方法。在过去的十年间,FM方法是复杂性状区分效果最好的,但不能有效处理非单调类型的生长曲线。Earliness index（E-index）方法的问世,解决了非单调类型的曲线不能有效识别的难题,它能够将任意生物类型的复杂性状发展过程描述为生长曲线并加以区分。基于E-index方法的原理,开发了一套Eindex Application（EIA）分析工具,该工具中集成了E-index方法,利用生物数据可视化技术动态绘制生长曲线,包含数据获取、数据处理和结果输出等功能,为遗传工作者的研究提供了良好平台。仿真实验的结果证明了EIA分析工具具有高效、实时和准确的性能,是区分复杂性状的有力工具。

英文摘要：

Currently,there are enormous challenges for the research on differentiating complex traits in the field of biogenetics,and many methods are employed to tackle these challenges,among which molecular marker,QTL mapping and sequence analysis are useful in targeting controlling genes for complex traits and thus serve as main coping strategies. To differentiate complex traits is of great importance for biodiversity research and studying genes,and is a key approach to understand the underlying mechanism of gene controlling. The existing methods,however,are not mature and perfect,which therefore have brought much difficulty in effectively differentiating complex traits in the field of biogenetics. Since complex traits can be effectively described as growth curves,methods based on growth curves in recent years are common way to differentiate complex traits,among which functional mapping（ FM） is a representative method. although FM method has been one of the best approaches for differentiating complex traits over the past decade,it has been so far confined to deal with those where growth curve is monotonic. Earliness index（ E-index） method emerges as required and successfully solves the nonmonotonicity situation. Moreover,it is able to deal with any type of biological complex developmental process.Based on the principle of E-index,E-index application（ EIA） analysis tool was developed,which provides a good platform for potential genetic researchers and scientists,helping them in several aspects,including data acquisition,drawing growth curves by dynamic data visualization technology,data processing and result retrieval.Results from simulation experiments show that EIA analysis tool is efficient,real-time and accurate,being a powerful tool to differentiate complex traits.