# Biology Meets Programming: Bioinformatics for Beginners Quiz Answers

## All Weeks Biology Meets Programming: Bioinformatics for Beginners Quiz Answers

### Biology Meets Programming: Bioinformatics for Beginners Week 01 Quiz Answers

Q1. Before you begin this quiz, please note the following.

1. Quizzes in this course are taken from the interactive text.

2. Quiz questions do not require that you do any programming to solve them.

True or False: The Hidden Message Problem is a well-defined computational problem.

• True
• False

Q2. A variable that can have only two values – True or False – is called what?

• Integer
• Floating Point
• String
• Boolean

Q3. Compute PatternCount(“CGCG”, “CGCGATACGTTACATACATGATAGACCGCGCGCGATCATATCGCGATTATC”)

Q4. The expression “True and not (False or False)” returns what?

• True
• False

Q5. What is the most frequent 3-mer of “CGGAGGACTCTAGGTAACGCTTATCAGGTCCATAGGACATTCA” ?

Q6. Which data structure in Python consists of a set of key-value pairs?

• Array
• String
• List
• Dictionary

Q7. What is the reverse complement of “CCAGATC” ?

Q8. In Python, how do we initialize an empty list named items?

• items = {}
• items = \\//
• items = <>
• items = []
• items = ||

#### Biology Meets Programming: Bioinformatics for Beginners 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. The position of the E. coli genome at which the skew attains a maximum value is most likely near which of the following?

• the replication terminus
• the middle of the reverse strand
• the middle of the forward strand
• the origin of replication

Q3. In Python, the expression 8.7//4 is equal to what?

Q4. Identify the value of i for which the skew array of “GATACACTTCCCGAGTAGGTACTG” attains a maximum value.

Report the position of the first occurrence only, with 1-based numeration (i.e. Skew[1] corresponds to “G” here)

Q5. Compute the Hamming distance between “TGACCCGTTATGCTCGAGTTCGGTCAGAGCGTCATTGCGAGTAGTCGTTTGCTTTCTCAAACTCC” and

“GAGCGATTAAGCGTGACAGCCCCAGGGAACCCACAAAACGTGATCGCAGTCCATCCGATCATACA”.

Q6. True or False: DnaA can bind only to “perfect” DnaA boxes.

• True
• False

### Biology Meets Programming: Bioinformatics for Beginners Week 03 Quiz Answers

Q1. Which type of algorithm simulates tossing coins in order to solve problems?

• Combinatorial algorithm
• Randomized algorithm
• Heuristic
• Machine learning algorithm
• Greedy algorithm

Q2. True or false: a motif of lowest score with respect to a collection of strings must appear as a substring of one of the strings.

• True
• False

Q3. Which of the following RNA strings could translate into the amino acid string PRTEIN? (Select all that apply.)

• CCCCGUACGGAGAUGAAA
• CCGAGGACCGAAAUCAAC
• CCAAGAACAGAUAUCAAU
• CCACGUACUGAAAUUAAC

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

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

• AAGTGA
• TCGCGA
• AGGTGA
• AGGTCA
• AAGCTA
• AAGCCA

Q5. 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

Q6. (Fill in the blank) When an RNA strand is translated into protein, the RNA strand is partitioned into contiguous blocks of three nucleotides called ___.

### Biology Meets Programming: Bioinformatics for Beginners Week 04 Quiz Answers

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

• True
• False

Q2. 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.)

• GreedyMotifSearch (without pseudocounts)
• RandomizedMotifSearch
• BruteForceMotifSearch
• GreedyMotifSearch (with pseudocounts)
• GibbsSampler

Q5. (Fill in the blank)

Randomized algorithms that are not guaranteed to return exact solutions, but do quickly find approximate solutions, are named after the city of ___.

Q6. Given the following “un-normalized” set of probabilities (i.e., that do not necessarily sum to 1):

0.15 0.6 0.225 0.225 0.3

What is the normalized set of probabilities? (Enter your answer as a sequence of space-separated numbers.)

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