Harnessing Genomic Tools for Crop Improvement
Academic Press Inc (Verlag)
978-0-443-29281-1 (ISBN)
Beyond technical tutorials, the book explores cutting-edge bioinformatics tools such as sequence databases, BLAST, primer designing, and sequence alignment, ensuring users gain a holistic understanding of genomics-driven crop improvement. Definitions, terminology clarifications, and interpretation of the results help bridge the gap between theory and application, simplifying complex analyses.
Whether you are a novice or an experienced researcher, this book equips you with the skills to analyze and apply genomic data effectively, making it an invaluable asset for transforming geneticists into genomicists in both plant and animal sciences.
Dr. Lakshmi Narayana R. Vemireddy is a leading molecular geneticist and professor at Acharya N.G. Ranga Agricultural University (ANGRAU), India, with over 15 years of experience in teaching and research. He specializes in genomic tools such as QTL mapping, molecular breeding, genome-wide association studies (GWAS), QTL-seq and transcriptomics techniques like RNA-Seq. His key contributions include the discovery of novel QTLs for drought tolerance, grain quality, and yield, the development of DNA fingerprinting for Basmati rice authentication, and the creation of cultivar-specific QR codes for rice, sesame and little millet. He has also identified alternate dwarfing gene and employs marker-assisted breeding to enhance popular rice varieties in India. With numerous publications in high-impact journals, he has been instrumental in advancing genomic tools for crop improvement. As a dedicated mentor, he has supervised numerous Master’s and Ph.D. students, shaping the next generation of geneticists. Dr. Bommisetty Reddyyamini earned her postgraduate degree from Agricultural College, Mahanandi, and her Doctoral degree from S.V. Agricultural College, Tirupati, ANGRAU, India. She has extensive teaching and research experience in advanced plant breeding methods, specializing in genomics-assisted breeding. Her research led to the identification of novel QTLs for grain number and grain weight in rice using QTL-Seq. She has published several research articles in reputed peer-reviewed journals. In recognition of her contributions, she received the “Outstanding Ph.D. Thesis Award at the Second International Conference on Advancement of Science and Technology for Environment, Society, and People (ICASTESP-2023). Dr. Yellari Amaravathi has extensive research experience in molecular breeding, tissue culture, genetic engineering, and genomics. She earned her M.Sc. (Ag) in Plant Genetic Resources from the National Bureau of Plant Genetic Resources (NBPGR), IARI, New Delhi, and completed her doctoral studies at the National Institute of Plant Biotechnology, IARI, New Delhi. She began her career as a Scientist at the Defence Agricultural Research Laboratory (DARL), Ministry of Defence, where she worked on genetic engineering for cold tolerance in vegetable crops such as tomatoes, bell peppers, cucumbers, and radishes. In 2013, she joined ANGRAU engaging in both teaching and research. Her research focuses on understanding molecular mechanisms in plant-pathogen interactions, identifying genes for durable resistance, and leveraging advanced technologies such as CRISPR/Cas9 for crop improvement.
1. Basic bioinformatics software: Sequence retrieval and sequence submission
2. SSR and SNP identification and marker development
3. NGS analysis: Variant calling and genome assembly
4. Genetic diversity and population structure analysis—DARwin, MEGA, and STRUCTURE
5. QTL Mapping—QTL IciMapping, Windows QTL Cartographer and Mapchart
6. Genome-wide association mapping tools: TASSEL and GAPIT
7. Statistical models for genomic selection: Practical implementation using R
8. Haplotype analysis software: HAPLOTYPE ANALYSIS, DnaSP, Haploview, and PopART
9. Analysis of transcription factor (TF)-target gene regulatory networks
10. Transcriptome analysis: RT-PCR and RNA-seq analysis
11. MiRNA structure and target prediction tools
12. Designing of guide RNA for CRISPR gene editing: A web based foundational approach
13. Protein interaction network analysis: STRING and CYTOSCAPE
14. Navigating in silico drug discovery: A hands-on guide with autodock vina and discovery studio
15. Machine learning techniques for gene prediction
| Erscheinungsdatum | 02.12.2025 |
|---|---|
| Verlagsort | San Diego |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Gewicht | 450 g |
| Themenwelt | Informatik ► Weitere Themen ► Bioinformatik |
| Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie | |
| Technik ► Umwelttechnik / Biotechnologie | |
| Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei | |
| ISBN-10 | 0-443-29281-7 / 0443292817 |
| ISBN-13 | 978-0-443-29281-1 / 9780443292811 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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