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Sequencing by hybridization. One experimental procedure for identifying a new DNA sequence repeatedly probes it to determine which k-mers(substrings of length ) it contains. Based on these, the full sequence must then be reconstructed.Let’s now formulate this as a combinatorial problem. For any string x (the DNA sequence), let Γ(x)denote the multiset of all of its localid="1658905204605" k-mers. In particular, localid="1658904556515" Γ(x)contains exactly |x|-k+1elements.The reconstruction problem is now easy to state: given a multiset of strings, find a string x such that Γ(x)is exactly this multiset.

(a)Show that the reconstruction problem reduces to RUDRATA PATH. (Hint: Construct a directed graph with one node for each localid="1658904858295" k-mers, and with an edge from a to b if the last k-1characters of match the first localid="1658905395287" k-1characters of b.)

(b)But in fact, there is much better news. Show that the same problem also reduces to EULER PATH. (Hint: This time, use one directed edge for each k-mer.)

Short Answer

Expert verified

a) TheSequencingbyHybridizationproblemcanbereducedtoHamiltonianPath.b) TheSequencingbyHybridizationproblemcanbereducedtoEulerPath.

Step by step solution

01

Explain the given information

Consider the information:

The objective is to prove that the reconstruction problem can be reduced to Hamiltonian Path.

The Hamiltonian path or Hamilton path is a path between the any two vertices of the graph that contains all the other vertices exactly once.

02

Reconstructing problem to RUDRATA PATH

(a)

Proof:

This reconstruction problem is reduced to a Hamiltonian Path using a directed graph construction. In a directed graph, each substring of length k or k-mersis represented as the vertices of the graph. In a multiset, if anyk-mersappears more than once then they are represented using multiple vertices.

The edges in the directed graph are constructed such that for each edgea,b, k-1suffix of should be similar tok-1 prefix of b .

Therefore, the Sequencing by Hybridization problem can be reduced to Hamiltonian Path.

03

Reconstructing problem to EULER PATH

(b)

Consider the information:

The objective is to prove that the reconstruction problem can be reduced to Euler Path.

The Euler path of a graph contains all the edges of the graph exactly once but the vertices can be visited multiple times.

Proof:

The reduction of the reconstruction problem to the Euler path gives a linear-time algorithm for the problem. The idea of the reduction is to make the edges of the graph the substrings of length k . Then the path containing every edge only once can be found.

The vertices in this graph are the set of k-1mers..

The vertex is connected to a vertex with a directed edge if the multiset contains such that k-1mers.suffix is same as andk-1 prefix is same as b .The parallel edges are used to represent therole="math" localid="1658905546336" k-mers.appearing more than once.

Therefore, the Sequencing by Hybridization problem can be reduced to Euler Path.

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Most popular questions from this chapter

Show that if P=NP then the RSA cryptosystem (Section 1.4.2) can be broken in polynomial time.

Search versus decision. Suppose you have a procedure which runs in polynomial time and tells you whether or not a graph has a Rudrata path. Show that you can use it to develop a polynomial-time algorithm for RUDRATA PATH (which returns the actual path, if it exists).

In the EXACT-4SAT problem, the input is a set of clauses, each of which is a disjunction of exactly four literals, and such that each variable occurs at most once in each clause. The goal is to find a satisfying assignment, if one exists. Prove that EXACT-4SAT is NP-complete.

Optimization versus search.Recall the traveling salesman problem:

TSP

Input: A matrix of distances; a budget b

Output: A tour which passes through all the cities and has lengthb, if such a tour exists.

The optimization version of this problem asks directly for the shortest tour.

TSP-OPT

Input:A matrix of distances

Output:The shortest tour which passes through all the cities.

Show that if TSP can be solved in polynomial time, then so can TSP-OPT.

Consider the CLIQUE problem restricted to graphs in which every vertex has degree at most v. Call this problem CLIQUE-3 .

(a) Prove that CLIQUE-3 is in NP .

(b) What is wrong with the following proof of NP-completeness for CLIQUE-3 ? We know that the CLIQUE problem in general graphs is NP-complete, so it is enough to present a reduction from CLIQUE-3 to CLIQUE . Given a graph G with vertices of degree 3, and a parameter g, the reduction leaves the graph and the parameter unchanged: clearly the output of the reduction is a possible input for the CLIQUE problem. Furthermore, the answer to both problems is identical. This proves the correctness of the reduction and, therefore, the NP-completeness of CLIQUE-3 .

(c) It is true that the VERTEX COVER problem remains NP-complete even when restricted to graphs in which every vertex has degree at most 3 . Call this problem VC-3 . What is wrong with the following proof of NP-completeness for CLIQUE ? We present a reduction from VC-3 to CLIQUE-3 . Given a graph G=(V,E) with node degrees bounded by 3 , and a parameter b , we create an instance of CLIQUE-3 by leaving the graph unchanged and switching the parameter to |V|-b. Now, a subset CVis a vertex cover in G if and only if the complementary set V-C is a clique in G. Therefore G has a vertex cover of sizebif and only if it has a clique of size |V|-b. This proves the correctness of the reduction and, consequently, the NP-completeness of CLIQUE-3 .

(4)Describe an O(V)algorithm for CLIQUE-3 .

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