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Hierarchical Clustering-Based Algorithms and In Silico Techniques for Phylogenetic Analysis of Rhizobia

  • Jyoti Lakhani
  • Ajay Khuteta
  • Anupama Choudhary
  • Dharmesh Harwani
Chapter
Part of the Soil Biology book series (SOILBIOL, volume 50)

Abstract

There are several in silico methodologies and tools available to study evolutionary history of rhizobia. Previously, it was very difficult to study and predict evolutionary relationships between two microbial species in a laboratory using wet lab experiments due to the lack of fossil evidences of microorganisms. In previous two decades, emergence and development of bioinformatics tools resolved this problem by replacing wet experiments by in silico experiments. The present communication is a survey on phylogenetic tools and algorithms used by researchers to study phylogeny of rhizobia. Phylogenetic analysis may be considered to be a highly reliable and important bioinformatics tool in biological sciences. The importance of phylogenetic analysis lies in its simple and easy handling of data. The varied applications of phylogenetics in different fields of biology make this analysis an unconditional necessity. This chapter is a survey on the molecular phylogenetic analysis of rhizobia with reference to the contemporary in silico methods used for rhizobia. Evidences and input parameters have also been discussed.

Keywords

Rhizobia In silico Phylogenetic analysis Hierarchical clustering Evolution 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jyoti Lakhani
    • 1
    • 2
  • Ajay Khuteta
    • 1
  • Anupama Choudhary
    • 3
  • Dharmesh Harwani
    • 4
  1. 1.Department of Computer SciencePoornima UniversityJaipurIndia
  2. 2.Department of Computer ScienceMaharaja Ganga Singh UniversityBikanerIndia
  3. 3.Department of Computer ScienceKeen CollegeBikanerIndia
  4. 4.Department of MicrobiologyMaharaja Ganga Singh UniversityBikanerIndia

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