CABI Biotechnology Series Series 11

Plant Omics

Advances in Big Data Biology

December 2022
More details
  • Publisher
  • Published
    20th December 2022
  • ISBN 9781789247510
  • Language English
  • Pages 264 pp.
  • Size 6" x 9"

This book provides a comprehensive overview of plant omics and big data in the fields of plant and crop biology. It discusses each omics layer individually, including genomics, transcriptomics, proteomics, and covers model and non-model species. In a section on advanced topics, it considers developments in each specialized domain, including genome editing and enhanced breeding strategies (such as genomic selection and high-throughput phenotyping), with the aim of providing tools to help tackle global food security issues. The importance of online resources in big data biology are highlighted in a section summarizing both wet- and dry-biological portals. This section introduces biological resources, datasets, online bioinformatics tools and approaches that are in the public domain. This title:

  • reviews each omics layer individually;
  • focuses on new advanced research domains and technology; and
  • summarizes publicly available experimental and informatics resources.
This book is for students, engineers, researchers, and academics in plant biology, genetics, biotechnology, and bioinformatics.

1. Plant Genomics
2. Plant Transcriptomics: Data-driven global approach to understand cellular processes and their regulation in model and non-model plants
3. Plant Proteomics
4. Plant Metabolomics: The Great Potential of Plant Metabolomics in Big Data Biology
5. Plant Phenomics
6. Plant Non-coding Transcriptomics: Overview of lncRNAs in abiotic stress responses
7. Plant Epigenomics
8. Plant Organellar Omics
9. Plant Cis-elements and Transcription Factors
10. Plant Gene Expression Network
11. Plant hormones: Gene family organization and homeologue interactions of genes for gibberellin metabolism and signaling in allotetraploid Brassica napus
12. Plant-pathogen interaction: New era of plant pathogen interaction studies
13. Plant GWAS
14. Plant Genomic selection: a concept that uses genomics data in plant breeding
15. Plant Genome Editing
16. Introduction of Deep Learning Approaches in Plant Omics Research
17. Deep learning on images and genetic sequences in plants: classifications and regressions
18. Deep Learning in Plant Omics: Object Detection and Image Segmentation
19. Plant Experimental Resources
20. Plant Omics Databases: an online resource guide

Hajime Ohyanagi

Dr. Hajime Ohyanagi received his BSc and MSc degrees in Biotechnology from the University of Tokyo, Japan, and PhD degree in Genetics from the Graduate University for Advanced Studies, Japan. He has worked in the private sector of the Japanese bioinformatics business for more than 16 years, and has been associated with multiple academic institutions as Guest Research Scientist/Lecturer. He is currently a Technical Specialist at King Abdullah University of Science and Technology in Saudi Arabia. He is appointed as Research-II Grade, associated both with the Biological and Environmental Science and Engineering (BESE) Division and the Computational Bioscience Research Center (CBRC), and is a co-lecturer of Population Genomics in the BESE graduate student education program. Currently he is determining the biological significance of big data of marine and crop genomics, by the means of diverse bioinformatics methodologies.

Kentaro Yano

Dr. Kentaro Yano recieved his BSc, MSc and PhD degree in Agriculture from Kyoto University, Japan. He is a professor at Meiji University, Japan. Currently he is focused on knowledge-based information from agricultural big-data analysis.

Eiji Yamamoto

No information

Ai Kitazumi

Ai Kitazumi has been working with Benildo de los Reyes since undergraduate (genotyping overexpression lines, making transformation constructs), master's (cis element analysis in orthologous transcription factors, miRNA profiling and target prediction in landraces of potatoes, comparative genomics of wild species of Oryza), Ph.D (high throughput sequencing on salinity tolerant individuals in transgressive rice population), moving from wet lab experiments to bioinformatics. In projects on stress response in rice and cotton, her role is a rice genome/transcript assembler with a goal to understand a mechanism of how genome shock upon hybridization of genetically distant parents and through successive rounds of meiosis, through integrating DNA-seq, RNA-seq, BS-seq, and action of ncRNA and transposons. Current analysis has revealed variation beyond SNP level and she is working on further analysis that might change how we look at hybrids and breeding lines.

Plant; Crop; Genome; Transcriptome; Proteome; Metabolome; Phenome; Hormone; Non-coding Transcriptome; Epigenome; Organellar Omics; Plant-Microbe Interaction; GWAS; Genomic Selection; Genome Editing; Enhanced Plant Breeding; Plant Experimental Resources; Database; High-throughput DNA sequencing; High-throughput Phenotyping; omics; big data