The Needleman-Wunsch algorithm is a foundational bioinformatics tool for aligning protein or nucleotide sequences, employing dynamic programming to achieve optimal global alignments. Developed by Saul B. Needleman and Christian D. Wunsch in 1970, it divides complex alignment problems into smaller, manageable tasks, and utilizes a scoring system based on matches, mismatches, and gaps. This algorithm remains crucial in sequence alignment applications due to its effectiveness and accuracy.

1. Needleman-Wunsch
Algorithm 1
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2. Presented By:
• Proshanta Kumar Shil
ID:141-15-3140
Section:B
Department of CSE
Daffodil International University
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3. What is Needleman-Wunsch algorithm?
The Needleman–Wunsch algorithm is an algorithm used
in bioinformatics to align protein or nucleotide sequences.
• It was one of the first applications of dynamic programming to compare
biological sequences.
• The algorithm was developed by Saul B. Needleman and Christian D.
Wunsch and published in 1970.
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4. Alignment methods
• Global and local sequence alignment methods
• Global : Needleman-Wunch
• Local : Smith-Waterman
• Database Search
• BLAST
• FASTA
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5. Goals of sequence databases
• To know about a newly sequenced database.
• To find the similarity of a unique sequence to another gene that
has a known function.
• To find the similarity of a new protein in a lower organism to a
protein from another species.
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6. Alignment Algorithms
• Global : Needleman-Wunch
• Local : Smith-Watermann
•  These two dynamic programming alignment algorithm are
guaranteed to give OPTIMAL alignments
•  But O(m*n) quadratic
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7. Needleman-Wunsch Method
• For example, the two hypothetical sequences
• abcdefghajklm
• abbdhijk
• could be aligned like this
• abcdefghajklm
• || | | ||
• abbd...hijk
• As shown, there are 6 matches,
• 2 mismatches, and one gap of length 3.
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8. Needleman-Wunsch Method
• The alignment is scored according to a payoff matrix
• $payoff = { match => $match,
• mismatch => $mismatch,
• gap_open => $gap_open,
• gap_extend => $gap_extend };
• For correct operation, match must be positive,
• and the other entries must be negative.
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9. Needleman-Wunsch Method
• Given the payoff matrix
• $payoff = { match => 4,
• mismatch => -3,
• gap_open => -2,
• gap_extend => -1 };
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10. Needleman-Wunsch Method
• The sequences
• abcdefghajklm
• abbdhijk
• are aligned and scored like this
• a b c d e f g h a j k l m
• | | | | | |
• a b b d . . . h i j k
• match 4 4 4 4 4 4
• mismatch -3 -3
• gap_open -2
• gap_extend -1-1-1
• for a total score of 24-6-2-3 = 13.
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11. Steps:
• 1. Initialization
• 2 Matrix fill or scoring
• 3. Traceback and alignment
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12. Lets see an example…
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13. Fill in the Table 13
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A G C
A
A
C
C
Two sequences will be aligned.
AGC (sequence #1)
AACC (sequence #2)
A simple scoring scheme will be used

14. Initialization step:
Create Matrix with M + 1
columns
and N + 1 rows.
For match=+1; Mismatch=-1;
Gap=-2
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A G C
0 -2 -4 -6
A -2
A -4
C -6
C -8

15. 15
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Fill in the Table
A G C
0 -2 -4 -6
A -2 1
A -4
C -6
C -8
Matrix fill step: Each position Mi,j is defined to be the
MAXIMUM score at position i,j
Mi,j = MAXIMUM [
Mi-1, j-1 + si,,j (match or mismatch in the diagonal)
Mi, j-1 + w (gap in sequence #1)
Mi-1, j + w (gap in sequence #2)]

16. Continuing
the procedure 16
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A G C
0 -2 -4 -6
A -2 1 -1 -3
A -4 -1 0 -2
C -6 -3 -2 -1
C -8 -5 -4 -1

17. Traceback step:
Position at current cell
and look at direct
predecessors
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A G C
0 -2 -4 -6
A -2 1 -1 -3
A -4 -1 0 -2
C -6 -3 -2 -1
C -8 -5 -4 -1

18. Traceback step:
Position at current cell and
look at direct predecessors
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A G C
0 -2 -4 -6
A -2 1 -1 -3
A -4 -1 0 -2
C -6 -3 -2 -1
C -8 -5 -4 -1
AG-C
AAAC
-AGC
AAAC
A-GC
AAAC

19. Summary
• The algorithm essentially divides a large problem into a series of
smaller problems and uses the solutions to the smaller problems to
reconstruct a solution to the larger problem.
• It is also sometimes referred to as the optimal matching algorithm
and the global alignment technique.
• The Needleman–Wunsch algorithm is still widely used for optimal
global alignment, particularly when the quality of the global
alignment is of the utmost importance.
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20. Any Question?
Thanks to All
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