| dc.contributor.author | Ruperao, P. |
| dc.contributor.author | Rangan, P. |
| dc.contributor.author | Shah, T. |
| dc.contributor.author | Thakur, V. |
| dc.contributor.author | Kalia, S. |
| dc.contributor.author | Mayes, S. |
| dc.contributor.author | Rathore, A. |
| dc.date.accessioned | 2023-10-11T15:53:04Z |
| dc.date.available | 2023-10-11T15:53:04Z |
| dc.date.issued | 2023-07-31 |
| dc.identifier.citation | Ruperao, P., Rangan, P., Shah, T., Thakur, V., Kalia, S., Mayes, S. & Rathore, A. (2023). The progression in developing genomic resources for crop improvement. Life, 13(8), 1-28. |
| dc.identifier.issn | 2075-1729 |
| dc.identifier.uri | https://hdl.handle.net/20.500.12478/8276 |
| dc.description.abstract | Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques. |
| dc.description.sponsorship | AVISA |
| dc.description.sponsorship | Indian Center for Agricultural Research |
| dc.description.sponsorship | Bill & Melinda Gates Foundation |
| dc.format.extent | 1-28 |
| dc.language.iso | en |
| dc.subject | Plant |
| dc.subject | Genomes |
| dc.subject | Bioinformatics |
| dc.subject | Databases |
| dc.subject | Big Data |
| dc.subject | Artificial Intelligence |
| dc.subject | Machine Learning |
| dc.title | The progression in developing genomic resources for crop improvement |
| dc.type | Journal Article |
| cg.contributor.affiliation | International Crops Research Institute for the Semi-Arid Tropics |
| cg.contributor.affiliation | ICAR-National Bureau of Plant Genetic Resources |
| cg.contributor.affiliation | International Institute of Tropical Agriculture |
| cg.contributor.affiliation | University of Hyderabad |
| cg.contributor.affiliation | Government of India |
| cg.contributor.affiliation | International Maize and Wheat Improvement Center |
| cg.coverage.region | ACP |
| cg.coverage.region | Europe |
| cg.coverage.country | Germany |
| cg.coverage.hub | Eastern Africa Hub |
| cg.researchtheme | Biometrics |
| cg.identifier.bibtexciteid | RUPERAO:2023 |
| cg.isijournal | ISI Journal |
| cg.authorship.types | CGIAR and developing country institute |
| cg.iitasubject | Biometrics |
| cg.iitasubject | Food Security |
| cg.iitasubject | Genetic Improvement |
| cg.iitasubject | Plant Genetic Resources |
| cg.journal | Life |
| cg.notes | Open Access Journal; Published online: 31 Jul 2023 |
| cg.accessibilitystatus | Open Access |
| cg.reviewstatus | Peer Review |
| cg.usagerightslicense | Creative Commons Attribution 4.0 (CC BY 0.0) |
| cg.targetaudience | Scientists |
| cg.identifier.doi | https://doi.org/10.3390/life13081668 |
| cg.iitaauthor.identifier | Trushar Shah: 0000-0002-0091-7981 |
| cg.futureupdate.required | No |
| cg.identifier.issue | 8: 1668 |
| cg.identifier.volume | 13 |
