This set of Bioinformatics online test focuses on “Database Searching with the Smith – Waterman Method”.
1. The rigorous dynamic programming method is normally not used for database searching because it is slow and computationally expensive.
a) True
b) False
View Answer
Explanation: Heuristics such as BLAST and FASTA are developed for faster speed. However, the heuristic methods are limited in sensitivity and are not guaranteed to find the optimal alignment. They often fail to find alignment for distantly related sequences.
2. FASTA and BLAST are __________ but __________ for larger datasets.
a) faster, more sensitive
b) faster, less sensitive
c) slower, less sensitive
d) slower, more sensitive
View Answer
Explanation: Empirical tests have indeed shown that the exhaustive method produces superior results over the heuristic methods like BLAST and FASTA. But heuristic methods are better and practical when it comes to assess larger datasets with comparatively low sensitivity.
3. Scan PS is a web-based program that implements a modified version of the Needleman-Wunsch algorithm.
a) True
b) False
View Answer
Explanation: ScanPS (Scan Protein Sequence) is a web-based program that implements a modified version of the Smith–Waterman algorithm optimized for parallel processing. The major feature is that the program allows iterative searching similar to PSI-BLAST, which builds profiles from one round of search results and uses them for the second round of database searching. Full dynamic programming is used in each cycle for added sensitivity.
4. Par Align is a web-based server that uses parallel processors to perform exhaustive sequence comparisons using either a parallelized version of the Smith–Waterman algorithm or a heuristic program for further speed gains.
a) True
b) False
View Answer
Explanation: The heuristic subprogram first finds exact ungapped alignments and uses them as anchors for extension into gapped alignments by combining the scores of several diagonals in the alignment matrix. The search speed of ParAlign approaches to that of BLAST, but with higher sensitivity.
5. In Smith–Waterman algorithm, in initialization Step, the _________ row and ________ column are subject to gap penalty.
a) first, first
b) first, second
c) second, First
d) first, last
View Answer
Explanation: In Smith–Waterman algorithm, first row and first column are set to 0. In the Needleman Wunsch algorithm, First row and first column are subject to gap penalty.
6. Local sequence alignments are necessary for many cases out of which one is repeated.
a) True
b) False
View Answer
Explanation: It can also be used for modular organization of genes and proteins (exons, domains, etc.) Also it can be used in cases of sequences diverged so that similarity was retained, or can be detected, just in some sub-regions.
7. In SW algorithm, to align two sequences of lengths of m and n _________ time is required.
a) O(mn)
b) O(m2n)
c) O(m2n3)
d) O(mn2)
View Answer
Explanation: The Smith–Waterman algorithm is quite demanding of time. Hence if two sequences of lengths of m and n have to be aligned, the required time is O(m2n). It requires O(mn) calculation steps.
8. One of the challenges in SWA is obtaining correct alignments in regions of low similarity between distantly related biological sequences.
a) True
b) False
View Answer
Explanation: It is because mutations have added too much ‘noise’ over evolutionary time to allow for a meaningful comparison of those regions. Local alignment avoids such regions altogether and focuses on those with a positive score, i.e. those with an evolutionarily conserved signal of similarity.
9. Score can be negative in Smith–Waterman algorithm.
a) True
b) False
View Answer
Explanation: Negative score is set to 0. In Needleman–Wunsch algorithm, the Score can be negative. Also, in Smith–Waterman algorithm, in tracing back step, it begins with the highest score, ends when 0 is encountered.
10. The function of the scoring matrix is to conduct one-to-one comparisons between all components in two sequences and record the optimal alignment results.
a) True
b) False
View Answer
Explanation: The scoring process reflects the concept of dynamic programming. The final optimal alignment is found by iteratively expanding the growing optimal alignment.
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