Motif Search: Difference between revisions
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Latest revision as of 09:11, 28 April 2023
Description
Motif search is the problem of identifying motifs, recurring or conserved patterns, in the strings (typically biological sequence data sets).
Parameters
$n$: size of set of input strings
$m$: size of input strings
$k$: length of substrings
$\sigma$: function $V(k, m)$ defined as the number of $k$-mers that are at most $m$ Hamming distance from the motif space
Table of Algorithms
Name | Year | Time | Space | Approximation Factor | Model | Reference |
---|---|---|---|---|---|---|
Lawrence, Reilly | 1990 | $O(nm)$ | $O(nm)$ | Deterministic | Time & Space | |
Lawrence Gibbs Sampling | 1993 | $O(nm)$ | $O(n + m)$ | Deterministic | Time | |
MotifSampler | 2001 | $O(nm)$ | $O(n + m)$ | Deterministic | Time | |
Speller | 1998 | $O(mn^{2} \sigma)$ | $O(mn^{2}/w)$ | Exact | Deterministic | Time & Space |
Mitra | 2002 | $O(k nm \sigma)$ | $O(mnk)$ | Exact | Deterministic | Time & Space |
Census | 2003 | $O(k nm \sigma)$ | $O(mnk)$ | Exact | Deterministic | Time & Space |
Risotto | 2006 | $O(mn^{2} \sigma)$ | $O(mn^{2})$ | Exact | Deterministic | Time & Space |
PMS | 2007 | $O(nm^{2} \sigma)$ | $O(m^{2} n)$ | Exact | Deterministic | Time & Space |
Roth AlignACE | 1998 | $O(nm)$ | $O(n + m)$ | Deterministic | Time | |
Helden Oligo-Analysis | 1998 | $O(mn)$ | $O(m)$ | Exact | Deterministic | Time |
van Helden J; Rios AF; Collado-Vides J | 2000 | $O(mn)$ | $O(m)$ | Exact | Deterministic | Time |
Tompa M | 1999 | $O(mn)$ | $O(m^{2})$ | Exact | Deterministic | Time |
Sinha S; Tompa M YMF (Yeast Motif Finder) | 2000 | $O(n^{0.{6}6} m)$ | $O(m)$ | Exact | Deterministic | Time |
Bailey TL; Elkan C MEME | 1995 | $O(n^{2}m^{2})$ | $O(mn)$ | Exact | Deterministic | Time |
Sagot M | 1988 | $O(n \log(n)$ m^{1.{4}5}) | $O(mn^{2}/w)$ | Exact | Deterministic | Time & Space |
Liang Cwinnower | 2003 | $O(nm^{0.5})$ | $O(m^{2})$ | Exact | Deterministic | Time |
Kingsford | 2006 | $O(mn)$ | $O(m^{2}n^{2})$ | Exact | Deterministic | Time |