Technical interview guide

Sequence Alignment (Needleman-Wunsch, Smith-Waterman, BLAST)

The algorithms for comparing DNA, RNA, and protein sequences — global vs. local alignment, and the heuristics that make searching billions of bases practical.

Read: 47 min
Practice MCQs: 25
Interview QA: 25
Edition: v7
Editorial status: Reviewed
Relevant for: Computational Biologist

Scope: Needleman-Wunsch and Smith-Waterman algorithms; NCBI BLAST+ documentation and statistical guidance; BLOSUM and PAM source publications reviewed 2026-09-04.

Interview QA

Treat each question like a live interview question: answer out loud first (structure, assumptions, tradeoffs), then open the model answer to spot gaps and rehearse a tighter follow-up.

Curated: 2026-10-05 · Written: 2026-10-05 · Reviewed: 2026-10-04

QA-1

Choose global versus local alignment for two proteins.

QA-2

Walk me through the BLAST algorithm workflow: how are seed hits identified, extended into HSPs, and evaluated for statistical significance?

QA-3

Implement Needleman-Wunsch correctly.

QA-4

Implement and verify local alignment.

QA-5

Derive an alignment recurrence.

QA-6

Align chromosome-scale sequences under memory constraints.

QA-7

Implement affine-gap alignment.

QA-8

Align a read expected to cover part of a reference end.

QA-9

Choose a protein scoring matrix.

QA-10

How does dynamic programming sequence alignment with affine gap penalties reduce its time complexity from O(n^3) to O(n^2)?

QA-11

Choose BLAST sensitivity settings.

QA-12

Choose a BLAST program for finding unannotated coding loci.

QA-13

Interpret a BLAST hit with E-value 1e-20.

QA-14

Rank and filter BLAST alignments.

QA-15

Compare results from custom and comprehensive databases.

QA-16

How do Karlin-Altschul statistics derive bit scores and E-values from raw local alignment scores, and when does the underlying model break down?

QA-17

Choose masking policy for a repeat-rich protein family.

QA-18

Combine multiple HSPs for candidate review.

QA-19

How does BLAST's two-hit heuristic decide when to trigger an extension, and why does it outperform single-hit extension in throughput without losing sensitivity?

QA-20

Build an orthology-candidate workflow.

QA-21

Create an alignment input validator.

QA-22

Make a database search reproducible.

QA-23

Build a robust BLAST result parser.

QA-24

Construct a pairwise-alignment regression suite.

QA-25