摘要生物信息学是现代科技发展的一个重要的衍生学科，就是在目前的生物学研究中，依托先进的计算机技术，实现在生物数据领域的新突破。目前，人类对于基因的认识程度不断的深入，尤其是在人类基因测定完成以后，世界各地的科研组织都在不断的加强对于基因的认识，生物数据总量不断的增加，如何从这些纷杂的信息中找到对人类社会有用的信息，就是我们这个生物信息学的主要的研究目的。本文首先介绍了生物学中的研究对象，同时详细的阐述了关于核酸、蛋白质的基础知识。本文所探究的判别分析法通常被称为分辨法，是通过对研究对象的特征进行判定和归类，需要评判的特征是多样的，通过这多种形式的特征实现对于实现对象的准去的归类。这种分析方法普遍的应用在农业、商业和气象研究中。通过建立多个评判对象的函数关系，利用现有的数据库资料，对研究的对象进行深入的研究、判定和归类，是现在比较准确的归类方法。58203

本文主要研究判别分析法在生物数据中建模及其应用，主要内容如下：

第一章， 介绍和探究生物信息学的研究问题和主要的研究的方法。

第二章， 分类说明目前的判别分析的研究方法及主要的侧重点。

第三章， 依托现在的线性判别的方法，对PCR的扩增难易程度做详细的测定，并取得了比较理想的预测精度。

毕业论文关键词：生物信息学；数学建模；判别分析；预测

Abstract

Bioinformatics is an important derivative of the development of modern science and technology, which is a new breakthrough in the field of biological data, relying on advanced computer technology in the current biological research. At present, for human genetic knowledge degree deepening, especially after the finish of human genes to determine, scientific research organizations around the world are continues to strengthen the understanding of the gene, the amount of biological data continues to increase, these distracting information on how to find information useful to the human society that we as a bioinformatics the main objective. In this paper, the research object of biology is introduced at first, and the basic knowledge about nucleic acid and protein is described in detail. This paper explores the discriminant analysis method is often referred to as the resolution method is through the characteristics of the research object of judgment and classification, need evaluation feature is perse and by characteristics of the various forms for realizing object must go classification. This analytical method is widely used in agriculture, business and meteorological research. Through the establishment of a number of evaluation object function relationship, the use of existing database data, the study of the object of in-depth study, determination and classification, is now more accurate classification method.

Chapter 1:Basic knowledge of bioinformatics is briefly introduced.

Chapter 2:Several types of commonly used of discriminant analysis method are introduced.

Chapter 3:Based on linear discriminant method,  to predict the degree of the difficulty of PCR amplification , and achieve a satisfactory prediction accuracy.

Key word: Bioinformatics; Mathematical modeling; Discriminant analysis; Prediction 

目   录

1 绪   论 1

2 判别分析法介绍 12

2.1距离判别法 12

2.2多组距离判别法 14

2.3 费尔希判别法