Genomics and Bioinformatics Applications in Horticulture
A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Genetics, Genomics, Breeding, and Biotechnology (G2B2)".
Deadline for manuscript submissions: closed (20 March 2022) | Viewed by 18700
Special Issue Editors
Interests: bioinformatics; computational biology; genomics; transcriptomics; quantitative genetics; biostatistics; machine learning
Special Issue Information
Dear Researchers,
Horticulture plays a vital role in human lives by providing fruits, vegetables, medicines, spices, ornamentals, and beverages. Horticultural plants are getting increasing attention for balanced nutrition for better human health and a clean environment. Research into horticultural plants has emphasized improving quality and health-promoting beneficial compounds, shelf-life extension, increasing yield, and development of varieties resistant to biotic and abiotic stresses.
Continuous development in low-cost and high-throughput sequencing technologies provides a wealth of genetic information to study the complex gene regulatory mechanisms and defense systems in the plants. Modern genomics and bioinformatics have surged the genome sequencing and molecular research of horticultural plants. This Special Issue focuses on genomics and bioinformatics analysis of horticultural plants, which can add value to the improvement of horticultural plants.
This Special Issue covers broad topics on horticultural plants genomics, including but not limited to the following:
- Transcriptomics and genomics analysis in response to biotic and abiotic stresses
- Comparative genomics analysis
- Population genomics
- Genome- and transcriptome-wide association analysis
- Molecular marker discovery
- Plant–pathogen interactions
- Development of new computational tools, functional databases, and genetic information resources
- Machine learning in genomics analysis
Dr. Renesh Bedre
Dr. Devi R. Kandel
Guest Editors
Manuscript Submission Information
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Keywords
- horticultural plants
- genomics
- transcriptomics
- proteomics
- bioinformatics
- computational biology
- RNA-seq
- high-throughput sequencing
- plant–pathogen interactions
- computational tools and databases
- machine learning
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