Download - PSA [Conclusion]

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Page 1: PSA [Conclusion]

CONCLUSION- Take home message -

Matrix Gap opening Gap extension Dynamic Programming Needle Water

Local alignment Global alignmentSimilarity Identity

Page 2: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

Page 3: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

??? ???INPUT

Page 4: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

Page 5: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

Page 6: PSA [Conclusion]

Conclusion

LocalProcess Global

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

Pair wise Sequencing Alignment

Page 7: PSA [Conclusion]

Conclusion

LocalProcess Global

Smith-Waterman algorithm

• Types of AlgorithmNeedleman-Wunsch

algorithm

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

Pair wise Sequencing Alignment

Page 8: PSA [Conclusion]

Conclusion

LocalProcess Global

Smith-Waterman algorithm

• Types of Algorithm

• Types of software

Needleman-Wunsch algorithm

WATER NEEDLE- Parameters-

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

Pair wise Sequencing Alignment

Page 9: PSA [Conclusion]

Conclusion

LocalProcess Global

Smith-Waterman algorithm

• Types of Algorithm

• Types of software

Needleman-Wunsch algorithm

WATER NEEDLE- Parameters-

E-DNA or BLOSUM or PAM E-DNA or BLOSUM or PAM• Types of Matrix

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

Pair wise Sequencing Alignment

Page 10: PSA [Conclusion]

Conclusion

LocalProcess Global

Smith-Waterman algorithm

• Types of Algorithm

• Types of software

Needleman-Wunsch algorithm

WATER NEEDLE- Parameters-

E-DNA or BLOSUM or PAM E-DNA or BLOSUM or PAM• Types of Matrix

• GAP Penalties Default: Opening G – 10 Extension G – 0.5

Note: These settings can be customized accordingly!!!

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

Pair wise Sequencing Alignment

Page 11: PSA [Conclusion]

Conclusion

INPUT

• Types of Algorithm

• Types of software

• Types of Matrix

• GAP Penalties

Page 12: PSA [Conclusion]

Essence of Dynamic Programming

Conclusion

INPUT

• Types of Algorithm

• Types of software

• Types of Matrix

• GAP Penalties

Page 13: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

PROCESS

Outcome 1OUTPUT

Page 14: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

PROCESS

Outcome 1OUTPUT Outcome 2

Page 15: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

PROCESS

Outcome 1OUTPUT Outcome 2 Outcome 3

Page 16: PSA [Conclusion]

Pair wise Sequencing Alignment

Conclusion

DNA ProteinINPUT

LocalTypes of Alignment

Global Local Global

PROCESS

Outcome 1OUTPUT Outcome 2 Outcome 3 Outcome 4

Note: Do look out for Sequence Identity (%) , Similarity (%) and alignment of your input sequences


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