Blast

NCBI-BLAST
www.ncbi.nlm.nih.gov/blast
WU-BLAST
http://blast.wustl.edu/
Statistical methods used to evaluate sequence similarity are
different

FASTA words or k-tuples
(1/2- prots, 4 to 6- NAs)
BLAST words or k-tuples
(3- prots, 11- NAs)
FASTA All possible words of same
length
BLAST Most significant Words
(e.g.., by BLOSUM62)

Step 1
Sequence filtering:
Programs that search for low-complexity regions or
for sequence repeats are used
e.g.., SEG, PSEG – Amino acid sequences
NSEG, DUST – For nucleic acids

Step 2
A list of words prepared
3 –for proteins
11 –for Nucleic acids
Step 3
Evaluation using the BLOSUM62

Step 4
Number of matches are reduced by a Cutoff score
called Neighborhood word score threshold (T)
Step 5
Above step repeated for each 3 letter code
Step 6
Remaining high-scoring words are organized into an
efficient search tree

Step 7
Each database sequence is scanned for an exact match
to one of all the words corresponding to the 1st
query
position, for the words to the second position & so on
Step 8
Alignment is extended in each direction
HSP (High-scoring segment pair) which has larger
score than the original word

Step 9
Identification of HSPs
Step 10
Statistical significance of each HSP
Step 11
Finding two or more HSP regions that can be made
into a longer alignment

Step 12
The score of the alignment is obtained and the expect
value for that score is calculated

Blast

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