3 research outputs found

    Blockchain-based data sharing platform customization with on/off-chain data balancing

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    Blockchain is widely considered as a promising solution, which can build a secure and efficient environment for data sharing. With more and more people working remotely and privacy becoming a major concern, having a secure and efficient way of sharing data has become a necessity. Blockchain being a decentralized ledger emphasizing cryptography obviously helps with data security and privacy, but the technology can suffer from major constraints in the context of data sharing such as on-chain data volume, storage, network performance, off-chain security, and more. In this study, we are looking at customization as a dynamic or adaptive strategy to determine when/how/what data should be stored on-chain versus off-chain to face the trade-off between performance and security; we explore the relevant research questions and the metrics by implementing a proof-of-concept solution using Hyperledger-fabric and IPFS (Inter Planetary File System). The results show that the on-chain latency increases with rising on-chain data ratio, whereas the off-chain exhibits reduced latency with respect to the on-chain ratio. In conclusion, the balance between on-chain and off-chain data storage in blockchain networks is a nuanced decision that hinges on the nature of the data, resource availability, and the desired trade-off between security and performance. A customized approach, where sensitive data is securely stored on-chain, while other data is managed off-chain for improved throughput, can help achieve the optimal equilibrium, ensuring both data integrity and network efficiency

    Integration of linkage maps for the Amphidiploid Brassica napus, and comparative mapping with Arabidopsis and Brassica rapa.

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    The large number of genetic linkage maps representing Brassica chromosomes constitute a potential platform for studying crop traits and genome evolution within Brassicaceae. However, the alignment of existing maps remains a major challenge. The integration of these genetic maps will enhance genetic resolution, and provide a means to navigate between sequence-tagged loci, and with contiguous genome sequences as these become available. Results: We report the first genome-wide integration of Brassica maps based on an automated pipeline which involved collation of genome-wide genotype data for sequence-tagged markers scored on three extensively used amphidiploid Brassica napus (2n = 38) populations. Representative markers were selected from consolidated maps for each population, and skeleton bin maps were generated. The skeleton maps for the three populations were then combined to generate an integrated map for each LG, comparing two different approaches, one encapsulated in JoinMap and the other in MergeMap. The BnaWAIT_01_2010a integrated genetic map was generated using JoinMap, and includes 5,162 genetic markers mapped onto 2,196 loci, with a total genetic length of 1,792 cM. The map density of one locus every 0.82 cM, corresponding to 515 Kbp, increases by at least threefold the locus and marker density within the original maps. Within the B. napus integrated map we identified 103 conserved collinearity blocks relative to Arabidopsis, including five previously unreported blocks. The BnaWAIT_01_2010a map was used to investigate the integrity and conservation of order proposed for genome sequence scaffolds generated from the constituent A genome of Brassica rapa. Conclusions: Our results provide a comprehensive genetic integration of the B. napus genome from a range of sources, which we anticipate will provide valuable information for rapeseed and Canola research
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