ACM题目:Motif Finding

本文介绍了一种用于生物信息学中的Motif查找算法。该算法旨在从一组DNA序列中寻找保守的序列模式(Motif),这对于理解基因调控机制至关重要。通过定义Hamming距离,算法能够找出即使略有差异但仍被认为是Motif实例的序列片段。
Motif Finding
Input File: D.in
Cell differentiation and development are fundamentally controlled by gene regulation. Only a subset of
genes in the genome is expressed in a cell at a given time under given conditions. Regulatory sites on
DNA sequence normally correspond to shared conservative sequence patterns among the regulatory
regions of correlated genes. We call these conserved sequence motifs. The actual regulatory DNA sites
corresponding to a motif are called the instances of that motif. Identifying motifs and corresponding
instances are very important, so biologists can investigate the interactions between DNA and proteins,
gene regulation, cell development and cell reaction.
Given two equal-length strings, the Hamming Distance is the number of positions in which the
corresponding characters are different. For example, the Hamming Distance between “ACTG” and
ATCG” is 2 because they differ at the 2
nd
and 3
rd
positions.
Your task is to find a motif for a few DNA sequences. Every DNA sequence consists of only A, C, G, T.
If a substring of DNA sequence S has the same length with motif P and their Hamming Distance is not
more than d, we say that S includes an instance of P. Given n DNA sequences with length of l. Among
them, m sequences are “key sequences”. You need to find out the motif P whose length is w, so that
every key sequence includes an instance of motif P. What’s more, the number of DNA sequences which
include an instance of P should be as large as possible.
For example, n=7, m =7, l=40, w =8, d =2. The sequences are as follows (they are all key sequences):
CGGGGCTATCCAGCTGGGTCGTCACATTCCCCTTTCGATA
TTTGAGGGTGCCCAATAAGGGCAACTCCAAAGCGGACAAA
GGATGGATCTGATGCCGTTTGACGACCTAAATCAACGGCC
AAGGAAGCAACCCCAGGAGCGCCTTTGCTGGTTCTACCTG
AATTTTCTAAAAAGATTATAATGTCGGTCCTTGGAACTTC
CTGCTGACAACTGAGATCATGCTGCATGCCATTTTCAACT
TACATGATCTTTTGATGGCACTTGGATGAGGGAATGATGC
The motif P is ATGCAACT.
Input
The input contains several cases. The first line of each case contains three integers n (1 ≤ n ≤ 15), m (0 ≤
m n) and l (1 ≤ l ≤ 10,000). The second line contains two integers w (1 ≤ w ≤ 8) and d (0 ≤ d w). The
third line contains m unique integers ranging from 0 to n-1, indicating the key sequences. Then followed
by n lines, in which each line contains one sequence. The input is terminated by three zeros.
Output
For each case, output the motif P in one line. If the solution is not unique, then output the
lexicographically smallest one. If there is no answer, you should output “No solution”.
31
st
ACM/ICPC (Asia - Xian) Preliminary Contest hosted by XiDian University
Page 7 (total 13 pages for 8 problems)
Sample Input
3 2 4
3 1
0 2
ACTT
CGTG
CCCC
3 2 4
3 0
0 2
ACTT
CGTG
CCCC
0 0 0
Output for Sample Input
CCT
No solution
Motif Finding
Input File: D.in
Cell differentiation and development are fundamentally controlled by gene regulation. Only a subset of
genes in the genome is expressed in a cell at a given time under given conditions. Regulatory sites on
DNA sequence normally correspond to shared conservative sequence patterns among the regulatory
regions of correlated genes. We call these conserved sequence motifs. The actual regulatory DNA sites
corresponding to a motif are called the instances of that motif. Identifying motifs and corresponding
instances are very important, so biologists can investigate the interactions between DNA and proteins,
gene regulation, cell development and cell reaction.
Given two equal-length strings, the Hamming Distance is the number of positions in which the
corresponding characters are different. For example, the Hamming Distance between “ACTG” and
ATCG” is 2 because they differ at the 2
nd
and 3
rd
positions.
Your task is to find a motif for a few DNA sequences. Every DNA sequence consists of only A, C, G, T.
If a substring of DNA sequence S has the same length with motif P and their Hamming Distance is not
more than d, we say that S includes an instance of P. Given n DNA sequences with length of l. Among
them, m sequences are “key sequences”. You need to find out the motif P whose length is w, so that
every key sequence includes an instance of motif P. What’s more, the number of DNA sequences which
include an instance of P should be as large as possible.
For example, n=7, m =7, l=40, w =8, d =2. The sequences are as follows (they are all key sequences):
CGGGGCTATCCAGCTGGGTCGTCACATTCCCCTTTCGATA
TTTGAGGGTGCCCAATAAGGGCAACTCCAAAGCGGACAAA
GGATGGATCTGATGCCGTTTGACGACCTAAATCAACGGCC
AAGGAAGCAACCCCAGGAGCGCCTTTGCTGGTTCTACCTG
AATTTTCTAAAAAGATTATAATGTCGGTCCTTGGAACTTC
CTGCTGACAACTGAGATCATGCTGCATGCCATTTTCAACT
TACATGATCTTTTGATGGCACTTGGATGAGGGAATGATGC
The motif P is ATGCAACT.
Input
The input contains several cases. The first line of each case contains three integers n (1 ≤ n ≤ 15), m (0 ≤
m n) and l (1 ≤ l ≤ 10,000). The second line contains two integers w (1 ≤ w ≤ 8) and d (0 ≤ d w). The
third line contains m unique integers ranging from 0 to n-1, indicating the key sequences. Then followed
by n lines, in which each line contains one sequence. The input is terminated by three zeros.
Output
For each case, output the motif P in one line. If the solution is not unique, then output the
lexicographically smallest one. If there is no answer, you should output “No solution”.

Page 7
31
st
ACM/ICPC (Asia - Xian) Preliminary Contest hosted by XiDian University
Page 7 (total 13 pages for 8 problems)
Sample Input
3 2 4
3 1
0 2
ACTT
CGTG
CCCC
3 2 4
3 0
0 2
ACTT
CGTG
CCCC
0 0 0
Output for Sample Input
CCT
No solution

Motif Finding<?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" />

 

Cell differentiation and development are fundamentally controlled by gene regulation. Only a subset of genes in the genome is expressed in a cell at a given time under given conditions. Regulatory sites on DNA sequence normally correspond to shared conservative sequence patterns among the regulatory regions of correlated genes. We call these conserved sequence motifs. The actual regulatory DNA sites corresponding to a motif are called the instances of that motif. Identifying motifs and corresponding instances are very important, so biologists can investigate the interactions between DNA and proteins, gene regulation, cell development and cell reaction.

 

Given two equal-length strings, the Hamming Distance is the number of positions in which the corresponding characters are different. For example, the Hamming Distance between “ACTG” and “ATCG” is 2 because they differ at the 2nd and 3rd positions.

 

Your task is to find a motif for a few DNA sequences. Every DNA sequence consists of only A, C, G, T. If a substring of DNA sequence S has the same length with motif P and their Hamming Distance is not more than d, we say that S includes an instance of P. Given n DNA sequences with length of l. Among them, m sequences are “key sequences”. You need to find out the motif P whose length is w, so that every key sequence includes an instance of motif P. What’s more, the number of DNA sequences which include an instance of P should be as large as possible.

 

For example, n=7, m =7, l=40, w =8, d =2. The sequences are as follows (they are all key sequences):

CGGGGCTATCCAGCTGGGTCGTCACATTCCCCTTTCGATA

TTTGAGGGTGCCCAATAAGGGCAACTCCAAAGCGGACAAA

GGATGGATCTGATGCCGTTTGACGACCTAAATCAACGGCC

AAGGAAGCAACCCCAGGAGCGCCTTTGCTGGTTCTACCTG

AATTTTCTAAAAAGATTATAATGTCGGTCCTTGGAACTTC

CTGCTGACAACTGAGATCATGCTGCATGCCATTTTCAACT

TACATGATCTTTTGATGGCACTTGGATGAGGGAATGATGC

The motif P is ATGCAACT.

Input

The input contains several cases. The first line of each case contains three integers n (1 ≤ n ≤ 15), m (0 ≤ m n) and l (1 ≤ l ≤ 10,000). The second line contains two integers w (1 ≤ w ≤ 8) and d (0 ≤ d w). The third line contains m unique integers ranging from 0 to n-1, indicating the key sequences. Then followed by n lines, in which each line contains one sequence. The input is terminated by three zeros.

Output

For each case, output the motif P in one line. If the solution is not unique, then output the lexicographically smallest one. If there is no answer, you should output “No solution”.

Sample Input

3 2 4

3 1

0 2

ACTT

CGTG

CCCC

3 2 4

3 0

0 2

ACTT

CGTG

CCCC

0 0 0

Output for Sample Input

CCT

No solution

转载于:https://www.cnblogs.com/anf/archive/2008/11/27/1342469.html

内容概要:本文系统介绍了算术优化算法(AOA)的基本原理、核心思想及Python实现方法,并通过图像分割的实际案例展示了其应用价值。AOA是一种基于种群的元启发式算法,其核心思想来源于四则运算,利用乘除运算进行全局勘探,加减运算进行局部开发,通过数学优化器加速函数(MOA)和数学优化概率(MOP)动态控制搜索过程,在全局探索与局部开发之间实现平衡。文章详细解析了算法的初始化、勘探与开发阶段的更新策略,并提供了完整的Python代码实现,结合Rastrigin函数进行测试验证。进一步地,以Flask框架搭建前后端分离系统,将AOA应用于图像分割任务,展示了其在实际工程中的可行性与高效性。最后,通过收敛速度、寻优精度等指标评估算法性能,并提出自适应参数调整、模型优化和并行计算等改进策略。; 适合人群:具备一定Python编程基础和优化算法基础知识的高校学生、科研人员及工程技术人员,尤其适合从事人工智能、图像处理、智能优化等领域的从业者;; 使用场景及目标:①理解元启发式算法的设计思想与实现机制;②掌握AOA在函数优化、图像分割等实际问题中的建模与求解方法;③学习如何将优化算法集成到Web系统中实现工程化应用;④为算法性能评估与改进提供实践参考; 阅读建议:建议读者结合代码逐行调试,深入理解算法流程中MOA与MOP的作用机制,尝试在不同测试函数上运行算法以观察性能差异,并可进一步扩展图像分割模块,引入更复杂的预处理或后处理技术以提升分割效果。
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