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Agricultural Bioinformatics

  • Kavi Kishor P.B.
  • Rajib Bandopadhyay
  • Prashanth Suravajhala

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Sohini Gupta, Sayak Ganguli, Abhijit Datta
    Pages 21-32
  3. Sudhakar Reddy Palakolanu, Vincent Vadez, Sreenivasulu Nese, Kavi Kishor P. B.
    Pages 33-57
  4. Sujay Rakshit, K. N. Ganapathy
    Pages 59-87
  5. Jahangir Imam, Mukesh Nitin, Neha Nancy Toppo, Nimai Prasad Mandal, Yogesh Kumar, Mukund Variar et al.
    Pages 89-107
  6. P. Hima Kumari, S. Anil Kumar, Prashanth Suravajhala, N. Jalaja, P. Rathna Giri, Kavi Kishor P. B.
    Pages 109-127
  7. Venkatesh Kandula, Virginia A. Gottschalk, Ramesh Katam, Roja Rani Anupalli
    Pages 129-137
  8. Kompelli Saikumar, Viswanathaswamy Dinesh Kumar
    Pages 139-159
  9. Sameera Panchangam, Nalini Mallikarjuna, Prashanth Suravajhala
    Pages 161-170
  10. Priyanka James, S. Silpa, Raghunath Keshavachandran
    Pages 171-178
  11. Katsumi Sakata, Takuji Nakamura, Setsuko Komatsu
    Pages 179-187
  12. L. N. Chavali
    Pages 189-213
  13. Khyatiben V. Pathak, Sivaramaiah Nallapeta
    Pages 259-272
  14. Renuka Suravajhala, Rajdeep Poddar, Sivaramaiah Nallapeta, Saif Ullah
    Pages 283-291

About this book

Introduction

A common approach to understanding the functional repertoire of a genome is through functional genomics. With systems biology burgeoning, bioinformatics has grown to a larger extent for plant genomes where several applications in the form of protein-protein interactions (PPI) are used to predict the function of proteins. With plant genes evolutionarily conserved, the science of bioinformatics in agriculture has caught interest with myriad of applications taken from bench side to in silico studies. A multitude of technologies in the form of gene analysis, biochemical pathways and molecular techniques have been exploited to an extent that they consume less time and have been cost-effective to use. As genomes are being sequenced, there is an increased amount of expression data being generated from time to time matching the need to link the expression profiles and phenotypic variation to the underlying genomic variation. This would allow us to identify candidate genes and understand the molecular basis/phenotypic variation of traits. While many bioinformatics methods like expression and whole genome sequence data of organisms in biological databases have been used in plants, we felt a common reference showcasing the reviews for such analysis is wanting. We envisage that this dearth would be facilitated in the form of this Springer book on Agricultural Bioinformatics. We thank all the authors and the publishers Springer, Germany for providing us an opportunity to review the bioinformatics works that the authors have carried in the recent past and hope the readers would find this book attention grabbing.

 

Keywords

Cloud computing Genomespace Genomic Plant splicing Proteomic

Editors and affiliations

  • Kavi Kishor P.B.
    • 1
  • Rajib Bandopadhyay
    • 2
  • Prashanth Suravajhala
    • 3
  1. 1.Department of GeneticsOsmania UniversityHyderabadIndia
  2. 2.Department of BiotechnologyBirla Institute of TechnologyRanchiIndia
  3. 3.Bioclues Organization, IKP Knowledge Park, PicketSecunderabadIndia

Bibliographic information