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picture1_Design Of Experiments Slideshare 66921 | Sequence Alignment 2015


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File: Design Of Experiments Slideshare 66921 | Sequence Alignment 2015
sequence alignment a way of arranging two or more sequences to identify regions of similarity shows locations of similarities and differences between the sequences an optimal alignment exhibits the most ...

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                                         Sequence alignment
         •  A way of arranging two or more sequences to identify regions of similarity
         •  Shows locations of similarities and differences between the sequences
         •  An 'optimal' alignment exhibits the most similarities and the least differences
         •  The aligned residues correspond to original residue in their common ancestor
         •  Insertions and deletions are represented by gaps in the alignment
         •  Examples
             Protein sequence alignment
             MSTGAVLIY--TSILIKECHAMPAGNE-----
             ---GGILLFHRTHELIKESHAMANDEGGSNNS
                *  *    *  **** ***     
             Nucleotide sequence alignment
             attcgttggcaaatcgcccctatccggccttaa
             att---tggcggatcg-cctctacgggcc----
             ***   ****  **** **    ******
         2015-12-09                                                                                                             2
             Sequence alignment: Purpose
      •  Reveal structural, functional and evolutionary relationship between 
         biological sequences
      •  Similar sequences may have similar structure and function
      •  Similar sequences are likely to have common ancestral sequence
      •  Annotation of new sequences
      •  Modelling of protein structures
      •  Design and analysis of gene expression experiments
    2015-12-09                                          3
                  Sequence alignment: Types
     •  Global alignment
         – Aligns each residue in each sequence by introducing gaps
         – Example: Needleman-Wunsch algorithm
                      L G P S S K Q T G K G S - S R I W D N
                      L N - I T K S A G K G A I M R L G D A
     2015-12-09                                                          4
                   Sequence alignment: Types
     •  Local alignment
         – Finds regions with the highest density of matches locally
         – Example: Smith-Waterman algorithm
                      - - - - - - - T G K G - - - - - - - -  
                      - - - - - - - A G K G - - - - - - - - 
     2015-12-09                                                            5
                            Sequence alignment: Scoring
               T A C G G G C A G                T A C G G G C A G                      T A C G G G C A G
               -  A C - G G C - G               -  A C G G - C - G                     -  A C G - G C - G
                        Option 1                         Option 2                               Option 3
        •    Scoring matrices are used to assign scores to each comparison of a pair of 
             characters
        •    Identities and substitutions by similar amino acids are assigned positive scores
        •    Mismatches, or matches that are unlikely to have been a result of evolution, are given 
             negative scores
                                     A      C     D     E      F     G H I K
                                     A      C     Y     E      F     G R I K
                                     +5 +5 -5 +5 +5 +5 -5 +5 +5
        2015-12-09                                                                                                         6
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...Sequence alignment a way of arranging two or more sequences to identify regions similarity shows locations similarities and differences between the an optimal exhibits most least aligned residues correspond original residue in their common ancestor insertions deletions are represented by gaps examples protein mstgavliy tsilikechampagne ggillfhrthelikeshamandeggsnns nucleotide attcgttggcaaatcgcccctatccggccttaa att tggcggatcg cctctacgggcc purpose reveal structural functional evolutionary relationship biological similar may have structure function likely ancestral annotation new modelling structures design analysis gene expression experiments types global aligns each introducing example needleman wunsch algorithm l g p s k q t r i w d n m local finds with highest density matches locally smith waterman scoring c option matrices used assign scores comparison pair characters identities substitutions amino acids assigned positive mismatches that unlikely been result evolution given negative e...

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