Plant Bioinformatics Decoding the Phyta / edited by Khalid Rehman Hakeem, Adeel Malik, Fazilet Vardar-Sukan, Munir Ozturk.

Dr. Khalid Rehman Hakeem (PhD) is working as Associate Professor at Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia, He has obtained his MSc. (Environmental Botany) as well as PhD (Botany) from Jamia Hamdard, New Delhi, India in 2006 and 2011 re...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Hakeem, Khalid Rehman (Editor), Malik, Adeel (Editor), Vardar-Sukan, Fazilet (Editor), Ozturk, Munir (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
Edition:1st ed. 2017.
Series:Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
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Table of Contents:
  • 1. Introduction to fundamental and applied bioinformatics research in plant life sciences
  • Concept, development and application of novel computational methods for the analysis and integration of –omics data
  • 3. Impact of high-throughput techniques on plant translational research
  • 4. Functional genomics approaches in plant research
  • 5. Bioinformatical versus experimental analyses of small RNAs in plants
  • 6. Systems analyses of plant functions
  • 7. Phylogenetic analyses and whole genome duplication (WGD) events
  • 8. Application of bioinformatics in agriculture, plant breeding and, improved complex traits (e.g. yield and quality)
  • 9. Application of bioinformatics in developing resistance against insects and harsh environments
  • 10. Discovery of molecular markers such as single sequence repeats (SSRs) involved in gene mapping, molecular breeding and genetic diversity
  • 11. Significance of bioinformatics in the new crop diseases-emergence
  • 12. From genomics to the improved crop phenotype
  • 13. Deciphering the effects of microbiome on plants using computational methods
  • 14. Bioinformatics resources for plants
  • 15. Recent Technological advances in plant bioinformatics
  • 16. ‘Big Data’ challenges and future trends in plant bioinformatics research.