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Bioinformatics Practice Test Questions: Database Similarity Searching
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Database similarity search is based upon sequence alignment methods also used in pairwise sequence comparison. Sequence alignment can be global (whole sequence alignment) or local (partial sequence alignment) and there are algorithms to find the optimal alignment given particular comparison criteria.

Topics include: Heuristic Database Searching, FASTA, Comparison of FASTA and BLAST, & Database Searching with the Smith – Waterman Method.

Bioinformatics Practice Test Questions: Database Similarity Searching
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25 Questions

1. BLASTX uses protein sequences as queries to search against a protein sequence database.
2. The use of low-complexity masking in the BLAST procedure means that it may have higher specificity than FASTA because potential false positives are reduced.
3. In SW algorithm, to align two sequences of lengths of m and n _________ time is required.
4. The BLAST program was developed in _______
5. 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.
6. The initiation of FASTA format has ____ symbol.
7. Which of the following is not correct about BLAST?
8. The rigorous dynamic programming method is normally not used for database searching because it is slow and computationally expensive.
9. Score can be negative in Smith–Waterman algorithm.
10. Currently, there are two major heuristic algorithms for performing database searches: BLAST and FASTA.
11. Local sequence alignments are necessary for many cases out of which one is repeated.
12. Which of the following is not a benefit or a factual of FASTA over BLAST?
13. Scan PS is a web-based program that implements a modified version of the Needleman-Wunsch algorithm.
14. Z-score describes the number of standard deviations from the mean score for the database search.
15. FASTA is derived from logic of the dot plot.
16. One of the challenges in SWA is obtaining correct alignments in regions of low similarity between distantly related biological sequences.
17. In FASTA, neighboring high-scoring segments along the same diagonal are selected and joined to form a single alignment.
18. The second step in FASTA is to narrow down the high similarity regions between the two sequences.
19. The positional difference for each word between the two sequences is obtained by ________ the position of the ______ sequence from that of the _______ sequence and is expressed as the offset.
20. BLAST might not find matches for very short sequences.
21. The specificity refers to the ability to include incorrect hits.
22. The web-based FASTA program is offered by the European Bioinformatics Institute.
23. A recent improvement in the implementation of BLAST is the ability to provide gapped alignment.
24. In FASTA, For a Z-score > 15, the match can be considered extremely ______ with _____ of a homologous relationship.
25. Which of the following is not correct about FASTA?

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