Given below are three algorithms for the motif finding problem. Identify which figure belongs to which algorithm. ████████ randomly select k-mers Motifs = (Motif_1, ..., Motif_t) in each string from Dna BestMotifs ← Motifs for j ← 1 to N i ← RANDOM(t) Profile ← profile matrix formed from all strings in Motifs except for Motif_i Motif_i ← Profile-randomly generated k-mer in the i-th sequence if SCORE(Motifs) < SCORE(BestMotifs) BestMotifs ← Motifs return BestMotifs (a) Figure I ████████ BestMotifs ← motif matrix formed by first k-mers in each string from Dna for each k-mer Motif in the first string from Dna Motif_1 ← Motif for i = 2 to t form Profile from motifs Motif_1, ..., Motif_{i-1} Motif_i ← Profile-most probable k-mer in the i-th string in Dna Motifs ← (Motif_1, ..., Motif_t) if SCORE(Motifs) < SCORE(BestMotifs) BestMotifs ← Motifs return BestMotifs (b) Figure II ████████ randomly select k-mers Motifs = (Motif_1, ..., Motif_t) in each string from Dna BestMotifs ← Motifs while forever Profile ← PROFILE(Motifs) Motifs ← MOTIFS(Profile, Dna) if SCORE(Motifs) < SCORE(BestMotifs) BestMotifs ← Motifs else return BestMotifs (c) Figure III

(B) Figure I: Gibbs Sampling; Figure II: Greedy Motif Search; Figure III: Randomized Motif Search

(A) Figure I: Gibbs Sampling; Figure II: Randomized Motif Search; Figure III: Greedy Motif Search

(C) Figure I: Greedy Motif Search; Figure II: Randomized Motif Search; Figure III: Gibbs Sampling

(D) Figure I: Randomized Motif Search; Figure II: Gibbs Sampling; Figure III: Greedy Motif Search

Algorithmic Thinking in Bioinformatics · Quiz 2 · 3 Aug 2025 · May 2025 term

Question 1: Given below are three algorithms for the motif finding pr…

Question 1

+5 marksOne correct option

Given below are three algorithms for the motif finding problem. Identify which figure belongs to which algorithm.

text

1████████
2randomly select k-mers Motifs = (Motif_1, ..., Motif_t) in each string from Dna
3BestMotifs ← Motifs
4for j ← 1 to N
5  i ← RANDOM(t)
6  Profile ← profile matrix formed from all strings in Motifs except for Motif_i
7  Motif_i ← Profile-randomly generated k-mer in the i-th sequence
8  if SCORE(Motifs) < SCORE(BestMotifs)
9    BestMotifs ← Motifs
10return BestMotifs

(a) Figure I

text

1████████
2BestMotifs ← motif matrix formed by first k-mers in each string from Dna
3for each k-mer Motif in the first string from Dna
4  Motif_1 ← Motif
5  for i = 2 to t
6    form Profile from motifs Motif_1, ..., Motif_{i-1}
7    Motif_i ← Profile-most probable k-mer in the i-th string in Dna
8  Motifs ← (Motif_1, ..., Motif_t)
9  if SCORE(Motifs) < SCORE(BestMotifs)
10    BestMotifs ← Motifs
11return BestMotifs

(b) Figure II

text

1████████
2randomly select k-mers Motifs = (Motif_1, ..., Motif_t) in each string from Dna
3BestMotifs ← Motifs
4while forever
5  Profile ← PROFILE(Motifs)
6  Motifs ← MOTIFS(Profile, Dna)
7  if SCORE(Motifs) < SCORE(BestMotifs)
8    BestMotifs ← Motifs
9  else
10    return BestMotifs

A
Figure I: Gibbs Sampling; Figure II: Randomized Motif Search; Figure III: Greedy Motif Search
B
Figure I: Gibbs Sampling; Figure II: Greedy Motif Search; Figure III: Randomized Motif Search
C
Figure I: Greedy Motif Search; Figure II: Randomized Motif Search; Figure III: Gibbs Sampling
D
Figure I: Randomized Motif Search; Figure II: Gibbs Sampling; Figure III: Greedy Motif Search

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Correct answer

B
Figure I: Gibbs Sampling; Figure II: Greedy Motif Search; Figure III: Randomized Motif Search

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Question 1 of 18 in the IIT Madras BS Algorithmic Thinking in Bioinformatics (Algorithmic Thinking in Bioinformatics) Quiz 2 paper sat on 3 Aug 2025, in the May 2025 term (IIT M IMPROVEMENT AN EXAM QIA2 03 Aug 2025). It carries 5 marks.

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