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Identification of a Putative Ganoderic Acid Pathway Enzyme in a Ganoderma Australe Transcriptome by Means of a Hidden Markov Model

  • Germán López-GartnerEmail author
  • Daniel Agudelo-Valencia
  • Sergio Castaño
  • Gustavo A. Isaza
  • Luis F. Castillo
  • Mariana Sánchez
  • Jeferson Arango
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 375)

Abstract

Ganoderma australe is a fungus widely used as a traditional medicine mainly in Eastern countries, but not studied in silico at the genomic level. This species is probably related to other well characterized fungus with similar properties, which may facilitate gene finding through comparative molecular analysis using appropriated bioinformatics tools. This paper aims to present a preliminary analysis of a G. australe transcriptome through some computational biology techniques implementing Hidden Markov Models (HMM) in order to predict a key putative enzyme (lanosterol synthase, EC 5.4.99.7) involved in the metabolic pathway of triterpenoids of therapeutic interest. The findings suggest that the HMM approach results more efficient than traditional comparisons by homology based on methods of multiple sequences alignment. Here we report the first evidence of a putative lanosterol synthase protein being expressed in cell cultures of G. australe.

Keywords

HMM bioinformatics Ganoderma Gene finding 

Notes

Acknowledgments

This work is supported by the Call for Special Project funding for Research and Innovation at the University of Caldas 2013.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Germán López-Gartner
    • 1
    Email author
  • Daniel Agudelo-Valencia
    • 1
  • Sergio Castaño
    • 2
  • Gustavo A. Isaza
    • 2
  • Luis F. Castillo
    • 2
  • Mariana Sánchez
    • 1
  • Jeferson Arango
    • 2
  1. 1.Biology Sciences Department, GITIR Research GroupUniversidad de CaldasManizalesColombia
  2. 2.Systems and Informatics Department, GITIR Research GroupUniversidad de CaldasManizalesColombia

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