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MAMOT (hidden MArkov MOdelling Tool) - HOME

Program

Functionalities

Distribution

Examples and Applications


Program

MAMOT (hidden MArkov MOdelling Tool) is a program that provides access to the classic algorithms used for HMM modelling and some useful non-standard options for applications such as modelling protein binding sites in DNA sequences and the recognition of protein domains.

The user specifies a model or initial model and optional features in an input file.


Main Functionalities:

1) GENERATION of random sequences according to the specified model,

2) Baum-Welch (BW) LEARNING (expectation maximization algorithm that maximizes the data likelihood)

3) Viterbi LEARNING

4) PROBABILITY of a sequence given the model and DECODING by posterior state probabilites

5) Viterbi PROBABILITY and DECODING by most likely path sequence


Distribution

The distribution contains a Makefile for compiling the source code, example HMM model files and a README file with information for the use of the program.

Link to the distribution:
MAMOT version v1.0 February 2008:

MAMOT_v1.tgz



README file:
README



Examples and Applications


Introductory examples and models for Transcription Factors (Nuclear Receptor SuperFamily)


Coiled-coil models, MARCOIL


Example application to p53 transcription factor binding site recognition


Enquiries should be addressed to:
Mauro.Delorenzi@isb-sib.ch
and
Frederic.Schutz@isb-sib.ch

Please send comments on web pages to bcf@isb-sib.ch