Basic Applied Bioinformatics

Chandra Sekhar Mukhopadhyay, Ratan Kumar Choudhary, Mir Asif Iquebal

• Publisher: Wiley-Blackwell
• Year: 2017
• ISBN:
  9781119244417
• Edition: 1
• Topic: Medicine
• Subtopic: Biostatistics

An accessible guide that introduces students in all areas of life sciences to bioinformatics

Basic Applied Bioinformatics provides a practical guidance in bioinformatics and helps students to optimize parameters for data analysis and then to draw accurate conclusions from the results. In addition to parameter optimization, the text will also familiarize students with relevant terminology. Basic Applied Bioinformatics is written as an accessible guide for graduate students studying bioinformatics, biotechnology, and other related sub-disciplines of the life sciences. This accessible text outlines the basics of bioinformatics, including pertinent information such as downloading molecular sequences (nucleotide and protein) from databases; BLAST analyses; primer designing and its quality checking, multiple sequence alignment (global and local using freely available software); phylogenetic tree construction (using UPGMA, NJ, MP, ME, FM algorithm and MEGA7 suite), prediction of protein structures and genome annotation, RNASeq data analyses and identification of differentially expressed genes and similar advanced bioinformatics analyses. The authors Chandra Sekhar Mukhopadhyay, Ratan Kumar Choudhary, and Mir Asif Iquebal are noted experts in the field and have come together to provide an updated information on bioinformatics.

Salient features of this book includes:

• Accessible and updated information on bioinformatics tools
• A practical step-by-step approach to molecular-data analyses

• Information pertinent to study a variety of disciplines including biotechnology, zoology, bioinformatics and other related fields
• Worked examples, glossary terms, problems and solutions

Basic Applied Bioinformatics gives students studying bioinformatics, agricultural biotechnology, animal biotechnology, medical biotechnology, microbial biotechnology, and zoology an updated introduction to the growing field of bioinformatics.

SECTION V
Molecular Phylogenetics

CHAPTER 21
Construction of Phylogenetic Tree: Unweighted‐Pair Group Method with Arithmetic Mean (UPGMA)

CS Mukhopadhyay and RK Choudhary

School of Animal Biotechnology, GADVASU, Ludhiana

21.1 INTRODUCTION

UPGMA is a clustering algorithm that works by joining the branches of a tree on the basis of maximum similarity criteria among pairs of sequences, and by calculating the means of joined pairs. UPGMA is “ultrametric”, so all the terminal nodes are equally distanced from the root. Hence, at the end, when a root is added, the rooted tree is produced.

• Unweighted: It indicates equal contribution of all the pair‐wise distances. There is no weighting of any specific taxa‐pairs to indicate a different evolutionary rate compared with another pair(s). This is the opposite of the Weighted‐Pair Group Method with Arithmetic mean (WPGMA).
• Pair‐groups: Any two taxa or any two clusters (clade) or one taxon and a cluster are always combined in pairs (that is, interpreted as dichotomies).
• Arithmetic mean: Pair‐wise distance of each group is the mean distance to all members of that group.

21.2 ASSUMPTIONS

1. Constant rate of evolution (i.e., mutation‐rate) amongst all the sequences.
2. Distance data are ultrametric: This enables clustering by satisfying the “three point condition” to generate the tree.

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TERMINOLOGIES AND POINTS

1. Neighbors: the external nodes with the smallest number of mismatches.
2. Ultrametric: in distance methods, an ultrametric tree is characterized by a “Three point condition”, where three points (a, b, c) satisfy the condition for the distance...