RNA Structure Prediction MCQs

Welcome to our comprehensive collection of Multiple Choice Questions (MCQs) on RNA Structure Prediction, a fundamental topic in the field of Bioinformatics. Whether you're preparing for competitive exams, honing your problem-solving skills, or simply looking to enhance your abilities in this field, our RNA Structure Prediction MCQs are designed to help you grasp the core concepts and excel in solving problems.

In this section, you'll find a wide range of RNA Structure Prediction mcq questions that explore various aspects of RNA Structure Prediction problems. Each MCQ is crafted to challenge your understanding of RNA Structure Prediction principles, enabling you to refine your problem-solving techniques. Whether you're a student aiming to ace Bioinformatics tests, a job seeker preparing for interviews, or someone simply interested in sharpening their skills, our RNA Structure Prediction MCQs are your pathway to success in mastering this essential Bioinformatics topic.

Note: Each of the following question comes with multiple answer choices. Select the most appropriate option and test your understanding of RNA Structure Prediction. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

So, are you ready to put your RNA Structure Prediction knowledge to the test? Let's get started with our carefully curated MCQs!

RNA Structure Prediction MCQs | Page 3 of 9

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Q21.
In dot matrix in ab initio methods, the diagonals _____________ to the main diagonal represent regions that can self hybridize.

a.

parallel

b.

cutting in random fashion

c.

perpendicular

d.

adjacent parallel

Discuss
Answer: (c).perpendicular
Q22.
In dot matrix in ab initio methods, one way to reduce the noise in the matrix is to select an appropriate window size of a maximum number of contiguous base matches.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (b).False
Q23.
In dynamic programming, in ab initio methods, the use of a dot plot can be effective in finding a ____ secondary structure in a ________ molecule.

a.

multiple, large

b.

single, large

c.

single, small

d.

multiple, small

Discuss
Answer: (c).single, small
Q24.
In ab initio methods, a quantitative approach such as dynamic programming can be used to assemble a final structure with optimal base-paired regions.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (a).True
Q25.
In dynamic programming, in ab initio methods, Often ________ base pairing and energy terms of the base pairing _____ incorporated into the scoring process.

a.

G-C, are

b.

G–U, are not

c.

G–U, are also

d.

G-C, are not

Discuss
Answer: (c).G–U, are also
Q26.
The dynamic programming method produces ____ structure with _____ score.

a.

one, single best

b.

multiple, single best

c.

multiple, multiple

d.

single, multiple

Discuss
Answer: (a).one, single best
Q27.
The problem of dynamic programming to select one single structure can be complemented by adding a probability distribution function, known as the _________ which calculates a mathematical distribution of probable base pairs in thermodynamic equilibrium.

a.

partition function

b.

division function

c.

increment function

d.

fold function

Discuss
Answer: (a).partition function
Q28.
Which of the following is correct about MFOLD?

a.

It uses the dynamic programming only

b.

It uses the thermodynamic calculations only

c.

It uses the both dynamic programming and thermodynamic calculations as well

d.

It doesn’t take into account the themoststablility of the secondary structures

Discuss
Answer: (b).It uses the thermodynamic calculations only
Q29.
Like Mfold, RNAfold only examines the energy terms of the optimal alignment in a dot plot.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (b).False
Q30.
Which of the following about the RNAFold is incorrect?

a.

It extends the sequence alignment to the vicinity of the optimal diagonals to calculate thermodynamic stability of alternative structures

b.

It incorporates a partition function

c.

It doesn’t necessarily use a partition function

d.

It aims to select a number of statistically most probable structures in one of its steps

Discuss
Answer: (c).It doesn’t necessarily use a partition function
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