POJ 1080 Human Gene Functions

1050: Human Gene Functions -------------------------------------------------------------------------------- Result TIME Limit MEMORY Limit Run Times AC Times JUDGE 3s 8192K 378 217 Standard It is well known that a human gene can be considered as a sequence, consisting of four nucleotides, which are simply denoted by four letters, A, C, G, and T. Biologists have been interested in identifying human genes and determining their functions, because these can be used to diagnose human diseases and to design new drugs for them. A human gene can be identified through a series of time-consuming biological experiments, often with the help of computer programs. Once a sequence of a gene is obtained, the next job is to determine its function. One of the methods for biologists to use in determining the function of a new gene sequence that they have just identified is to search a database with the new gene as a query. The database to be searched stores many gene sequences and their functions – many researchers have been submitting their genes and functions to the database and the database is freely accessible through the Internet. A database search will return a list of gene sequences from the database that are similar to the query gene. Biologists assume that sequence similarity often implies functional similarity. So, the function of the new gene might be one of the functions that the genes from the list have. To exactly determine which one is the right one another series of biological experiments will be needed. Your job is to make a program that compares two genes and determines their similarity as explained below. Your program may be used as a part of the database search if you can provide an efficient one. Given two genes AGTGATG and GTTAG, how similar are they? One of the methods to measure the similarity of two genes is called alignment. In an alignment, spaces are inserted, if necessary, in appropriate positions of the genes to make them equally long and score the resulting genes according to a scoring matrix. For example, one space is inserted into AGTGATG to result in AGTGAT-G, and three spaces are inserted into GTTAG to result in –GT--TAG. A space is denoted by a minus sign (-). The two genes are now of equal length. These two strings are aligned: AGTGAT-G -GT--TAG In this alignment, there are four matches, namely, G in the second position, T in the third, T in the sixth, and G in the eighth. Each pair of aligned characters is assigned a score according to the following scoring matrix. * denotes that a space-space match is not allowed. The score of the alignment above is (-3)+5+5+(-2)+(-3)+5+(-3)+5=9. Of course, many other alignments are possible. One is shown below (a different number of spaces are inserted into different positions): AGTGATG -GTTA-G This alignment gives a score of (-3)+5+5+(-2)+5+(-1) +5=14. So, this one is better than the previous one. As a matter of fact, this one is optimal since no other alignment can have a higher score. So, it is said that the similarity of the two genes is 14. Input The input consists of T test cases. The number of test cases ) (T is given in the first line of the input. Each test case consists of two lines: each line contains an integer, the length of a gene, followed by a gene sequence. The length of each gene sequence is at least one and does not exceed 100. Output The output should print the similarity of each test case, one per line. Sample Input 2 7 AGTGATG 5 GTTAG 7 AGCTATT 9 AGCTTTAAA Sample Output 14 21 -------------------------------------------------------------------------------- This problem is used for contest: 36 148 ------------------

-------------------------------------------------------------- Submit / Problem List / Status / Discuss

        //由于S1序列的第I个没有匹配,所以在S1序列的前I个,
                      //和S2序列的前J个匹配中,他只能和-匹配了
        //a[i][j]是说S1序列的前I个,和S2序列的前J个匹配所得到的最大值

#include #include

int a[101][101];

int table[5][5]=

{ 5,-1,-2,-1,-3,

-1,5,-3,-2,-4, -2,-

3,5,-2,-2, -1,

-2,-2,5,-1, -3,

-4,-2,-1,0 }; int t(char ch) { if(ch=='A') return 0; if(ch=='C') return 1; if(ch=='G') return 2; if(ch=='T') return 3; return 4; } int max(int a,int b,int c) { int x=-1000000; if(a>x) x=a; if(b>x) x=b; if(c>x) x=c; return x; } int main() { int T; while(scanf("%d",&T)!=EOF) { while(T--) { memset(a,0,sizeof(a)); char s1[101],s2[101]; int l1,l2; scanf("%d%s",&l1,s1); scanf("%d%s",&l2,s2); a[0][0]=0; /*a[1][0]=a[1][0]+table[t(s1[1])][t('-')]; a[0][1]=a[0][1]+table[t('-')][t(s2[1])]; a[1][1]=a[0][0]+table[t(s1[0])][t(s2[0])];*/ for(int i=1;i<=l1;i++) a[i][0]=a[i-1][0]+table[t(s1[i-1])][4]; for(int i=1;i<=l2;i++) a[0][i]=a[0][i-1]+table[4][t(s2[i-1])]; for(int i=1;i<=l1;i++) for(int j=1;j<=l2;j++) a[i][j]=max(a[i-1][j-1]+table[t(s1[i-1])][t(s2[j-1])], a[i-1][j]+table[t(s1[i-1])][4], a[i][j-1]+table[4][t(s2[j-1])]); printf("%d/n",a[l1][l2]); } } return 0; }

资源下载链接为: https://pan.quark.cn/s/3d8e22c21839 随着 Web UI 框架(如 EasyUI、JqueryUI、Ext、DWZ 等)的不断发展与成熟,系统界面的统一化设计逐渐成为可能,同时代码生成器也能够生成符合统一规范的界面。在这种背景下,“代码生成 + 手工合并”的半智能开发模式正逐渐成为新的开发趋势。通过代码生成器,单表数据模型以及一对多数据模型的增删改查功能可以被直接生成并投入使用,这能够有效节省大约 80% 的开发工作量,从而显著提升开发效率。 JEECG(J2EE Code Generation)是一款基于代码生成器的智能开发平台。它引领了一种全新的开发模式,即从在线编码(Online Coding)到代码生成器生成代码,再到手工合并(Merge)的智能开发流程。该平台能够帮助开发者解决 Java 项目中大约 90% 的重复性工作,让开发者可以将更多的精力集中在业务逻辑的实现上。它不仅能够快速提高开发效率,帮助公司节省大量的人力成本,同时也保持了开发的灵活性。 JEECG 的核心宗旨是:对于简单的功能,可以通过在线编码配置来实现;对于复杂的功能,则利用代码生成器生成代码后,再进行手工合并;对于复杂的流程业务,采用表单自定义的方式进行处理,而业务流程则通过工作流来实现,并且可以扩展出任务接口,供开发者编写具体的业务逻辑。通过这种方式,JEECG 实现了流程任务节点和任务接口的灵活配置,既保证了开发的高效性,又兼顾了项目的灵活性和可扩展性。
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