# Bioinformatics Questions and Answers – Iterative Methods of Multiple Sequence Alignment

This set of Bioinformatics MCQs focuses on “Iterative Methods of Multiple Sequence Alignment”.

1. Iterative methods include repeatedly realigning subgroups of the sequences and then by aligning these subgroups into a local alignment of all of the sequences.
a) True
b) False

Explanation: Subgroups are aligned into a global alignment of all of the sequences. The objective is to improve the overall alignment score, such as a sum of pairs score. Selection of these groups may be based on the ordering of the sequences on a phylogenetic tree predicted in a manner similar to that of progressive alignment, separation of one or two of the sequences from the rest, or a random selection of the groups.

2. Which of the following is incorrect regarding PRRP?
a) The program PRRP uses iterative methods to produce an alignment
b) An initial pair-wise alignment is made to predict a tree
c) Only one cycle is performed
d) The whole process is repeated until there is no further increase in the alignment score

Explanation: As mentioned, an initial pair-wise alignment is made to predict a tree, the tree is used to produce weights for making alignments in the same manner as MSA except that the sequences are analyzed for the presence of aligned regions that include gaps rather than being globally aligned, and these regions are iteratively recalculated to improve the alignment score. The best scoring alignment is then used in a new cycle of calculations to predict a new tree, new weights, and new alignments.

3. In the program DIALIGN, pairs of sequences are aligned to locate aligned regions that do not include gaps, much like continuous diagonals in a dot matrix plot.
a) True
b) False

Explanation: The program DIALIGN finds an alignment by a different iterative method. Pairs of sequences are aligned to locate aligned regions that do not include gaps, much like continuous diagonals in a dot matrix plot. Diagonals of various lengths are identified. A consistent collection of weighted diagonals that provides an alignment which is a maximum sum of weights is then found.

4. The Genetic Algorithm method has been recently adapted for MSA(Multiple Sequence Alignment) by Corpet (1998).
a) True
b) False

Explanation: The genetic algorithm is a general type of machine-learning algorithm that has no direct relationship to biology and that was invented by computer scientists. The method has been recently adapted for MSA (Multiple Sequence Alignment) by Notredame and Higgins (1996) in a computer program package called SAGA (Sequence Alignment by Genetic Algorithm).

5. An approach for obtaining a higher-scoring MSA (Multiple Sequence Alignment) by rearranging an existing alignment uses a probability approach called simulated annealing.
a) True
b) False

Explanation: The program MSASA (Multiple Sequence Alignment by Simulated Annealing) starts with a heuristic MSA (Multiple Sequence Alignment). Further, it changes the alignment by following an algorithm designed to identify changes that increase the alignment score.
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6. The first step in Genetic Algorithm is arranging the sequences to be aligned in rows.
a) True
b) False

Explanation: The sequences to be aligned are written in rows, as on a page, except that they are made to overlap by a random amount of sequence, up to 50 residues long for sequences about 200 in length. The ends are then padded with gaps. A typical population of 100 of these MSAs is made, although other numbers may be set.

7. The second step in the Genetic Algorithm comprises of scoring of the 100 initial MSAs by the sum of pairs method.
a) True
b) False

Explanation: The 100 initial MSAs are scored by the sum of pairs method, except that both natural and quasi-natural gap-scoring schemes are used. Recall that the best SSP score for a MSA is the minimum one and the one that is closest to the sum of the pair-wise sequence alignment. Standard amino acid scoring matrices and gap opening and extension penalties are used.

8. In Genetic Algorithm, in the mutation process _______
a) sequence is changed
b) gaps are not inserted
c) sequence is not changed
d) gaps are not rearranged

Explanation: In the mutation process, the sequence is not changed (else it would no longer be an alignment), but gaps are inserted and rearranged in an attempt to create a better-scoring MSA. In the gap insertion process, the sequences in a given MSA are divided into two groups based on an estimated phylogenetic tree, and gaps of random length are inserted into random positions in the alignment.

9. The HMM is a statistical model that considers few combinations of matches and gaps to generate an alignment of a set of sequences.
a) True
b) False

Explanation: The HMM is a statistical model that considers all possible combinations of matches, mismatches, and gaps to generate an alignment of a set of sequences. A localized region of similarity, including insertions and deletions, may also be modeled by an HMM. Analysis of sequences by an HMM is discussed on page 185 along with other statistical methods.

10. Which of the following is not true about iterative methods?
a) Genetic Algorithm is method used for under this
b) Hidden Markov Models are used for Multiple Sequence Alignment
c) The objective is to improve the overall alignment score
d) MultAlin recalculates global scores

Explanation: MultAlin (Corpet 1988) recalculates pair-wise scores during the production of a progressive Alignment. In addition, it uses these scores to recalculate the tree, which is then used to refine the alignment in an effort to improve the score.

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