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Related Concept Videos

Masking and Demasking Agents01:19

Masking and Demasking Agents

EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
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RNA Editing02:23

RNA Editing

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HMMEditor: a visual editing tool for profile hidden Markov model.

Jianyong Dai1, Jianlin Cheng

  • 1School of Electrical Engineering and Computer Science, University of Central Florida, Orland, FL 32816, USA. daijy@cs.ucf.edu

BMC Genomics
|April 17, 2008
PubMed
Summary

A new visual editor, HMMEditor, allows for easy visualization and editing of profile Hidden Markov Models (HMMs). This tool aids in biological sequence analysis and modeling, offering unique functionalities for profile HMM manipulation.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Profile Hidden Markov Models (HMMs) are essential statistical tools for analyzing DNA, RNA, and protein sequences.
  • Applications include sequence alignment, gene prediction, motif discovery, and database searching.
  • A lack of user-friendly, visual editing tools for profile HMMs has been a limitation.

Purpose of the Study:

  • To develop a comprehensive, visual editing tool for profile Hidden Markov Models.
  • To provide intuitive visualization and editing capabilities for HMM architecture and parameters.
  • To facilitate sequence analysis and modeling workflows.

Main Methods:

  • Development of HMMEditor, a visual software tool.
  • Implementation of visualization features for HMM architecture, transition, and emission probabilities.
  • Integration of editing, saving, sequence alignment, and Viterbi path visualization functionalities.

Main Results:

  • HMMEditor enables clear visualization of profile HMM components.
  • Users can effectively edit and save HMMs and their parameters.
  • Sequence alignment against profile HMMs with Viterbi path visualization is supported.

Conclusions:

  • HMMEditor offers unique, valuable functions for profile HMM visualization and editing.
  • The tool serves as a significant asset for biological sequence analysis and modeling.
  • HMMEditor is freely accessible as both software and a web service.