Greater confidence was reposed in strongly related motif-sets identified by more than one motif discovery program.
Motif Discovery De novo motif discovery was performed with the program MEME (Bailey et al., 2009 ) using default settings.
This study proposes a general framework for structural motif discovery.
Consequently, numerous motif discovery tools have been developed to date.
The MEME Suite (Multiple Expectation Maximization for Motif Elicitation) [50] was used for motif discovery in our previous study [31], and the discovered motifs were used.
With zone-restricted motif discovery, gap- and hash-interpolated Markov models [27, 28] become powerful tools for motif discovery in a restricted region [18, 28 32].
Motif discovery can be focused onto the cis-regulatory regions in particular, and if linked with the HMM discovery, the motif-discovery and gene-discovery efforts are simultaneously strengthened.
The task of sequence pattern discovery, also known as motif discovery, is to uncover these unseen subsequences ab initio and then build a motif model for them.
Motif discovery in biological sequences is of prime importance and a major challenge in computational biology.
In this study, in silico approaches, that is, the knowledge based motif discovery and de novo motif discovery were used to identify the regulatory motifs of 79 Mtb TA systems.
Some of these and other individual data sources have already been shown to improve de novo motif discovery [8 11].
