Bioinformatics Multiple Choice Questions on “Dynamic Programming Algorithm for Sequence Alignment”.
1. Use of the dynamic programming method requires a scoring system for the comparison of symbol pairs, and a scheme for GAP penalties. Answer: A 2. After the derivation, the outputs of the dynamic programming are the ratios are called even scores. Answer: B 3. The matrices PAM250 and BLOSUM62 contain _______ Answer: A 4. The higher is the score in the alignment _________ Answer: A 5. Gaps are added to the alignment because it ______ Answer: A 6. Which of the following is not a description of dynamic programming algorithm? Answer: D 7. Which of the following is not a site on internet for alignment of sequence pairs? Answer: A 8. Dayhoff PAM matrices, are based on an evolutionary model of protein change, whereas, BLOSUM matrices, are designed to identify members of the same family. Answer: A 9. A feature of the dynamic programming algorithm is that the alignments obtained depend on the choice of a scoring system for comparing character pairs and penalty scores for gaps. Answer: A 10. Which of the following is untrue regarding dynamic programming algorithm? Answer: D
A. True
B. False
Explanation: Once those parameters have been set, the resulting alignment for two sequences should always be the same. Hence, the use of the dynamic programming method requires a scoring system for the comparison of symbol pairs (nucleotides for DNA sequences and amino acids for protein sequences), and a scheme for insertion/deletion (GAP) penalties.
A. True
B. False
Explanation: After the derivation, the outputs of the dynamic programming are the ratios are called odd scores. The ratios are transformed to logarithms of odds scores, called log odds scores, so that scores of sequential pairs may be added to reflect the overall odds of a real to chance alignment of an alignment. This happens in Dayhoff PAM250 and BLOSUM62.
A. positive and negative values
B. positive values only
C. negative values only
D. neither positive nor negative values, just the percentage
Explanation: These matrices contain positive and negative values, reflecting the likelihood of each amino acid substitution in related proteins. Using these tables, an alignment of a sequential set of amino acid pairs with no gaps receives an overall score that is the sum of the positive and negative log odds scores for each individual amino acid pair in the alignment.
A. the more significant is the alignment
B. or the less it resembles alignments in related proteins
C. the less significant is the alignment
D. the less it aligns with the related protein sequence
Explanation: In the scoring system, the higher this score, the more significant is the alignment, or the more it resembles alignments in related proteins. Also, the score given for gaps in aligned sequences is negative, because such misaligned regions should be uncommon in sequences of related proteins. Such a score will reduce the score obtained from an adjacent, matching region upstream in the sequences.
A. increases the matching of identical amino acids at subsequent portions in the alignment
B. increases the matching of or dissimilar amino acids at subsequent portions in the alignment
C. reduces the overall score
D. enhances the area of the sequences
Explanation: In the alignment process, gaps are added to the alignment in a manner that increases the matching of identical or similar amino acids at subsequent portions in the alignment. Ideally, when two similar protein sequences are aligned, the alignment should have long regions of identical or related amino acid pairs and very few gaps. As the sequences become more distant, more mismatched amino acid pairs and gaps should appear.
A. A method of sequence alignment
B. A method that can take gaps into account
C. A method that requires a manageable number of comparisons
D. This method doesn’t provide an optimal (highest scoring) alignment
Explanation: The method of sequence alignment by dynamic programming provides an optimal (highest scoring) alignment as an output. The quality of the alignment between two sequences is calculated using a scoring system that favors the matching of related or identical amino acids and penalizes for poorly matched amino acids and gaps.
A. BLASTX
B. BLASTN
C. SIM
D. BCM Search Launcher
Explanation: BLASTP is used under BLAST 2 sequence alignment. Also, The BLAST algorithm normally used for database similarity searches can also be used to align two sequences. SIM is known as Local similarity program for finding alternative alignments.
A. True
B. False
Explanation: There is a very large number amino acid scoring matrices in use, some much more popular than others, and these scoring matrices are designed for different purposes. Some, such as the Dayhoff PAM matrices, are based on an evolutionary model of protein change, whereas others, such as the BLOSUM matrices, are designed to identify members of the same family. Alignments between DNA sequences require similar kinds of considerations.
A. True
B. False
Explanation: For an algorithm, the output depends on the choice of a scoring system. For protein sequences, the simplest system of comparison is one based on identity. A match in an alignment is only scored if the two aligned amino acids are identical. However, one can also examine related protein sequences that can be aligned easily and find which amino acids are commonly substituted for each other.
A. The method compares every pair of characters in the two sequences and generates an alignment
B. The output alignment will include matched and mismatched characters and gaps in the two sequences that are positioned so that the number of matches between identical or related characters is the maximum possible
C. The dynamic programming algorithm provides a reliable computational method for aligning DNA and protein sequences
D. This doesn’t allow making evolutionary predictions on the basis of sequence alignments
Explanation: Optimal alignments provide useful information to biologists concerning sequence relationships by giving the best possible information as to which characters in a sequence should be in the same column in an alignment, and which are insertions in one of the sequences (or deletions on the other). This information is important for making functional, structural, and evolutionary predictions on the basis of sequence alignments.