## All Weeks Finding Hidden Messages in DNA (Bioinformatics I)

### Finding Hidden Messages in DNA (Bioinformatics I) Week 01 Quiz Answers

Q1. True or False: The Finding *oriC* Problem is a well-defined computational problem.

**True**- False

Q2. Compute *Count*(ACTGTACGATGATGTGTGTCAAAG, TGT).

**Comment Answer below if you know the answers**

Q3. What is the most frequent 3-mer of CGCCTAAATAGCCTCGCGGAGCCTTATGTCATACTCGTCCT?

**Comment Answer below if you know the answers**

Q4. What is the reverse complement of TTGTGTC?

**Comment Answer below if you know the answers**

Q5. Solve the Pattern Matching Problem with Text = ATGACTTCGCTGTTACGCGC and Pattern = CGC to find all starting positions of Pattern in Text. Return the starting positions in increasing order (make sure to use 0-based indexing!)

Enter your answer as a collection of space-separated integers. (e.g., 4 7 14)

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### Finding Hidden Messages in DNA (Bioinformatics I) Week 02 Quiz Answers

Q1. True or False: Deamination is more likely to occur when DNA is single-stranded than when it is double-stranded.

**True**- False

Q2. Compute the Hamming distance between CTACAGCAATACGATCATATGCGGATCCGCAGTGGCCGGTAGACACACGT and

CTACCCCGCTGCTCAATGACCGGGACTAAAGAGGCGAAGATTATGGTGTG.

**Comment Answer below if you know the answers**

Q3. Identify the value of *i* for which *Skew*_{i }(CATTCCAGTACTTCGATGATGGCGTGAAGA) attains a minimum value.

**Comment Answer below if you know the answers**

Q4. Compute *Count*_{2}(CATGCCATTCGCATTGTCCCAGTGA, CCC).

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Q5. The *d*-neighborhood of the *k*-mer *Pattern* is the collection of all *k*-mers that are at most Hamming distance *d* from *Pattern*.

How many 10-mers are in the 1-neighborhood of *Pattern* = CCAGTCAATG?

Note that the *d*-neighborhood of *Pattern* includes *Pattern*.

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### Finding Hidden Messages in DNA (Bioinformatics I) Week 03 Quiz Answers

Q1. Which type of algorithm selects the most attractive choice at each step?

- Dynamic programming algorithm
- Greedy algorithm
- Randomized algorithm
- Brute force search
- Combinatorial algorithm
- Machine learning algorithm

Q2. True or false: a motif of lowest score with respect to a collection of strings does not need to appear as a substring of one of the strings.

- True
- False

Q3. Order the following probability distributions from lowest to highest entropy:

A: (0.5, 0, 0, 0.5)

B: (0.25, 0.25, 0.25, 0.25)

C: (0, 0, 0, 1)

D: (0.25, 0, 0.5, 0.25)

- C, A, D, B
- D, C, A, B
- B, C, A, D
- B, A, D, C
- C, A, B, D

Q4. Consider the following profile matrix:

- A: 0.4 0.3 0.0 0.1 0.0 0.9
- C: 0.2 0.3 0.0 0.4 0.0 0.1
- G: 0.1 0.3 1.0 0.1 0.5 0.0
- T: 0.3 0.1 0.0 0.4 0.5 0.0

Q4. Which of the following strings is a consensus string for this profile matrix? (Select all that apply.)

- TCGCGA
- ACGCGA
- ACGTTA
- AGGTCA
- AAGCTA
- AAGAGA

Q5. Consider the following motif matrix:

CTCGATGAGTAGGAAAGTAGTTTCACTGGGCGAACCACCCCGGCGCTAATCCTAGTGCCC

GCAATCCTACCCGAGGCCACATATCAGTAGGAACTAGAACCACCACGGGTGGCTAGTTTC

GGTGTTGAACCACGGGGTTAGTTTCATCTATTGTAGGAATCGGCTTCAAATCCTACACAG

Which of the following 7-mers is a median string for this motif matrix? (Select all that apply.)

- AACGCTG
- ATAACGG
- GAACCAC
- GGTTACT
- AATCCTA
- CGTGTAA

Q6. Consider the following profile matrix *Profile*:

- A: 0.4 0.3 0.0 0.1 0.0 0.9
- C: 0.2 0.3 0.0 0.4 0.0 0.1
- G: 0.1 0.3 1.0 0.1 0.5 0.0
- T: 0.3 0.1 0.0 0.4 0.5 0.0

Compute Pr(TCGGTA|*Profile*). (Express your answer as a decimal and do not round your answer.)

#### Finding Hidden Messages in DNA (Bioinformatics I) Week 04 Quiz Answers

Q1. True or False: **RandomizedMotifSearch** performs well when given a uniform profile matrix.

- True
- False

Q2. True or False: **RandomizedMotifSearch** and **GibbsSampler** are usually run on many choices of initial *k*-mers.

- True
- False

Q3. True or False: it is possible for **GibbsSampler** to move from a collection of motifs with lower score to a collection of motifs with higher score.

- True
- False

Q4. Which of the following motif-finding algorithms is guaranteed to find an optimum solution? In other words, which of the following are *not* heuristics? (Select all that apply.)

**RandomizedMotifSearch****GreedyMotifSearch**(without pseudocounts)**GreedyMotifSearch**(with pseudocounts)**MedianString**

Q5. Assume we are given the following strings *Dna*:

TGACGTTC

TAAGAGTT

GGACGAAA

CTGTTCGC

Then, assume that **RandomizedMotifSearch** begins by randomly choosing the following 3-mers *Motifs* of *Dna*:

- TGA
- GTT
- GAA
- TGT

What are the 3-mers after one iteration of **RandomizedMotifSearch**? In other words, what are the 3-mers *Motifs*(*Profile*(*Motifs*), *Dna*)? Please enter your answer as four space-separated strings.

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