This set of Bioinformatics Multiple Choice Questions & Answers (MCQs) focuses on “Character Based Methods”.
1. Which of the following is incorrect statement about Character-based methods?
a) They are also called discrete methods
b) They are based directly on the sequence characters rather than on pairwise distances
c) They doesn’t count mutational events accumulated on the sequences
d) They may avoid the loss of information when characters are converted to distances
Explanation: They count mutational events accumulated on the sequences. This preservation of character information means that evolutionary dynamics of each character can be studied. Ancestral sequences can also be inferred. The two most popular character-based approaches are the maximum parsimony (MP) and maximum likelihood (ML) methods.
2. Which of the following is incorrect statement about Maximum Parsimony Method?
a) By cutting off the unnecessary variables, model development may become difficult, and there may be more chances of introducing inconsistencies, ambiguities, and redundancies, hence, the name Occam’s razor
b) In dealing with problems that may have an infinite number of possible solutions, choosing the simplest model may help to ‘cut off’ those variables that are not really necessary to explain the phenomenon
c) This method chooses a tree that has the fewest evolutionary changes or shortest overall branch lengths
d) It is based on a principle related to a medieval philosophy called Occam’s razor
Explanation: The theory was formulated by William of Occam in the thirteenth century and states that the simplest explanation is probably the correct one. This is because the simplest explanation requires the fewest assumptions and the fewest leaps of logic.
3. Which of the following is incorrect statement about Building Work of MP tree?
a) It works by searching for all possible tree topologies and reconstructing ancestral sequences that require the minimum number of changes to evolve to the current sequences
b) Other than informative sites are non-informative, which are constant sites or sites that have changes occurring only once
c) Informative sites are the ones that can often be explained by a unique tree topology
d) Constant sites have the same state in all taxa and are quite useful in evaluating the various topologies
Explanation: Constant sites have the same state in all taxa and are obviously useless in evaluating the various topologies. The sites that have changes occurring only once are not very useful either for constructing parsimony trees because they can be explained by multiple tree topologies. The non-informative sites are thus discarded in parsimony tree construction.
4. Because these ancestral character states are not known directly, multiple possible solutions may exist. In this case, the parsimony principle applies to choose the character states that result in a minimum number of substitutions.
Explanation: The inference of an ancestral sequence is made by first going from the leaves to internal nodes and to the common root to determine all possible ancestral character states. Then it goes back from the common root to the leaves to assign ancestral sequences that require the minimum number of substitutions.
5. The unweighted method treats all mutations as equivalent.
Explanation: This may be an oversimplification; mutations of some sites are known to occur less frequently than others, for example, transversions versus transitions, functionally important sites versus neutral sites. Therefore, a weighting scheme that takes into account the different kinds of mutations helps to select tree topologies more accurately. The MP method that incorporates a weighting scheme is called weighted parsimony.
6. Which of the following is incorrect statement about Tree-Searching Methods?
a) The choice of the first three taxa can be random
b) Parsimony method examines all possible tree topologies to find the maximally parsimonious tree.
c) It starts by building a three taxa unrooted tree, for which only one topology is available
d) This is different than exhaustive search method
Explanation: This is an exhaustive search method. The next step is to add a fourth taxon to the existing branches, producing three possible topologies. The remaining taxa are progressively added to form all possible tree topologies .Obviously, this brute-force approach only works if there are relatively few sequences.
7. Which of the following is incorrect statement about branch-and-bound?
a) It uses a shortcut to find an MP tree
b) It establishes an upper limit (or upper bound) for the number of allowed sequence variations
c) It solely uses UPGMA method
d) It starts by building a distance tree for all taxa involved
Explanation: It starts by building a distance tree for all taxa involved using either NJ or UPGMA and then computing the minimum number of substitutions for this tree. The resulting number defines the upper bound to which any other trees are compared. The rationale is that a maximally parsimonious tree must be equal to or shorter than the distance-based tree.
8. The branch-and-bound method starts building trees in a similar way as in the exhaustive method.
Explanation: The difference is that the previously established upper bound limits the tree growth. Whenever the overall tree length at every single stage exceeds the upper bound, the topology search toward a particular direction aborts. By doing so, it dramatically reduces the number of trees considered hence the computing time while at the same time guaranteeing to find the most parsimonious tree.
9. When the number of taxa exceeds twenty, even the branch-and-bound method becomes computationally unfeasible.
Explanation: A more heuristic search method must be used. A computer heuristic procedure is an approximation strategy to find an empirical solution for a complicated problem. This strategy generates quick answers, but not necessarily the best answer.
10. In a heuristic tree search, only a small subset of all possible trees is examined.
Explanation: This method starts by carrying out a quick initial approximation, which is to build an NJ tree and subsequently modifying it slightly into a different topology to see whether that leads to a shorter tree.
Sanfoundry Global Education & Learning Series – Bioinformatics.
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