A1.4
Question 1 Single best answer Level 2 1 point
Why can dynamic programming find the best alignment without listing and scoring every possible alignment?
- It samples a large random set of alignments and keeps the best, which is almost always the true optimum.
- It still scores every alignment, but runs faster by reusing one substitution-matrix lookup table across them.
- It discards any alignment that contains a gap early on, cutting most possibilities before it scores them.
- Each prefix pair’s best sub-alignment is built from shorter ones, so each pair is solved once and reused.
Question 2 Single best answer Level 3 1 point
Fill a Needleman-Wunsch matrix for the top sequence GATC and the side sequence GTC, using match \(+1\), mismatch \(-1\), and gap \(-2\). What is the optimal global alignment score?
- \(-1\)
- \(3\)
- \(-3\)
- \(1\)
Question 3 Single best answer Level 2 1 point
How do global and local alignment differ in what they report?
- Global alignment permits gaps, while local alignment forbids them and allows only exact matches.
- Global alignment uses one gap penalty, while local alignment uses another, but both align end to end.
- Global alignment reports only the best-matching region, while local alignment lines up the full lengths.
- Global alignment scores the sequences end to end, while local alignment reports only the highest-scoring shared region.
Question 4 Single best answer Level 3 1 point
Run Smith-Waterman on the top sequence AGCT and the side sequence GC, using match \(+1\), mismatch \(-1\), gap \(-2\), and a floor of \(0\). What is the optimal local alignment score? (You can do this without filling out a matrix; look for similarities between sequences.)
- \(-2\)
- \(0\)
- \(2\)
- \(1\)
Question 5 Single best answer Level 2 1 point
In BLOSUM62 the leucine-isoleucine pair scores \(+2\), while the leucine-aspartate pair scores \(-4\). What does the sign of a substitution-matrix entry tell you?
- The sign reflects how frequent each amino acid is on its own, not how often the two are swapped for each other.
- A positive score means the swap is disfavored and rare, while a negative score means it is favored and common.
- A positive score means the swap is seen more often than chance and tolerated; a negative score, less often and penalized.
- A positive score means the two residues are chemically identical, and a negative score means they are in different classes.
Question 6 Single best answer Level 2 1 point
How does a linear gap penalty differ from an affine gap penalty?
- A linear penalty charges the same for every gap position, while affine charges a large open cost plus a smaller extend cost per extra position.
- Both charge the gap length times a per-position amount, but an affine penalty makes that amount positive so gaps raise the score.
- A linear penalty is used for DNA while an affine penalty is used for protein, though the two share the same formula.
- A linear penalty charges per position, while an affine penalty charges a single flat fee for the whole gap regardless of its length.
Question 7 Single best answer Level 3 1 point
An optimal global alignment currently uses two gaps and no mismatches under match \(+1\), mismatch \(-1\), and gap \(-1\). If the gap becomes more costly, changing from \(-1\) to \(-3\) per position, how will the new optimal alignment most likely change?
- It will use more gaps to avoid the mismatches, which are now the costlier option.
- It will keep the same gaps, and the higher penalty will push the total score up.
- It will not change, because the match and mismatch scores are the same as before.
- It will use fewer gaps and take more mismatches, since a gap now costs more than a mismatch.
Question 8 Single best answer Level 4 1 point
A 30-residue query is compared against a 5,000-residue genome region. You expect the query to match one internal stretch of the long sequence, and you expect any indels to occur as single multi-residue events. Which combination of alignment method and gap penalty best fits this pair?
- Global alignment with a linear gap penalty.
- Global alignment with an affine gap penalty.
- Local alignment with an affine gap penalty.
- Local alignment with a linear gap penalty.