l x yi lxyiwc at yahoo.com
Thu Aug 26 18:46:12 EDT 2004

I was reading the paper "Maximum Likelihood Estimation
of the Statistical distribution of Smith-Waterman
Local Sequence Similarity Scores", published in
Bulletin of Mathematical Biology Vol54, No1, p59-75 by
R. Mott, and the paper "Sequence Comparison
Significance and Poisson Approximation" published in
Statistical Science vol9, 1994, 367-381,by M.S.
Waterman et al. 

These articles discuss the ML method for estimating
parameters for distributions obtained by searching a
random sequence with a databank.It can be assumed that
the sequences in the databank are independent
sequences, but if we are using the same sequence as
query each time,wouldn't the scores obtained be
dependent? then the likelihood needs to be modified to
account for this dependency? both of these papers used
the likelihood assuming all the scores obtained are
independent. Am I missing something here?

Could someone please help me understand? Thanks very


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