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Customer Relationship Management for Personalized Nutrition Service

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12254))

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Abstract

Sufficient food and nutrition supplement is very important for the health of our body. However, most of us do not know which food or nutrition is needed for our bodies, because we do not know our bodies’ detail nutrition requirement. Each person’s nutrition demand is different because of the differences of each person’s genes, age, and life style. With the fast development of genomics, genetics, nutrigenomics, nutrigenetics, and nutrition science, we can now provide personalized nutrition service for customers. The service can provide personalized food supplement solutions based on the DNA genetic testing and the lifestyle evaluation. For the nutrients that can not be supplemented sufficiently from food, the service can provide dietary supplement solutions for customers. Since the dietary supplement products on the market are general products for all the people that can not meet the need of each person’s unique nutrition requirement, therefore, our solution collaborates with nutrition product production factory to produce customized nutrition products for the customers. Personalized nutrition service needs to connect customers, genetic testing laboratories, and nutrition product production factory, therefore a customer relationship management (CRM) system is necessary to let customer read genetic report, order personalized nutrition products, place an order to nutrition factory to produce personalized nutrition products. In the paper, we give the technical design and deployment of a CRM system for supporting the personalized nutrition service. The CRM system has been delivered online and provides very successful service for customers, business partners, and intelligent nutrition factory.

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References

  1. Sales, N.M.R., Pelegrini, P.B., Goersch, M.C.: Nutrigenomics: definitions and advances of this new science. J. Nutr. Metab. 2014, 202759 (2014)

    Article  Google Scholar 

  2. Simopoulos, A.P.: The impact of the Bellagio report on healthy agriculture, healthy nutrition, healthy people: scientific and policy aspects and the international network of centers for genetics, nutrition and fitness for health. J. Nutrigenet Nutrigenomics 7(4–6), 191–211 (2015)

    Article  Google Scholar 

  3. Fenech, M., et al.: Nutrigenetics and nutrigenomics: viewpoints on the current status and applications in nutrition research and practice. J. Nutrigenet Nutrigenomics 4(2), 69–89 (2011)

    Article  Google Scholar 

  4. Nielsen, R., Paul, J.S., Albrechtsen, A., Song, Y.S.: Genotype and SNP calling from next-generation sequencing data. Nat. Rev. Genet. 12(6), 443–451 (2011)

    Article  Google Scholar 

  5. Mullaney, J.M., Mills, R.E., Pittard, W.S., Devine, S.E.: Small insertions and deletions (INDELs) in human genomes. Hum. Mol. Genet. 19(R2), R131–R136 (2010)

    Article  Google Scholar 

  6. McKenna, A., et al.: The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20(9), 1297–1303 (2010)

    Article  Google Scholar 

  7. Genome Analysis Toolkit. https://gatk.broadinstitute.org/. Accessed 2 May 2020

  8. U.S. National Library of Health: What are single nucleotide polymorphisms (SNPs)? https://ghr.nlm.nih.gov/primer/genomicresearch/snp. Accessed 2 May 2020

  9. Khalfan, M.: Variant Calling Pipeline using GATK4. https://gencore.bio.nyu.edu/variant-calling-pipeline-gatk4/. Accessed 2 May 2020

  10. Illumina: DNA Sequencing Methods Collection. https://www.illumina.com/content/dam/illumina-marketing/documents/products/research_reviews/dna-sequencing-methods-review-web.pdf. Accessed 2 May 2020

  11. HiSeq X Ten Sequencing System. https://www.illumina.com/systems/sequencing-platforms/hiseq-x.html. Accessed 2 May 2020

  12. NovaSeq Sequencing System. https://www.illumina.com/systems/sequencing-platforms/novaseq.html. Accessed 2 May 2020

  13. iScan System - Array scanner for extensive applications. https://www.illumina.com/systems/array-scanners/iscan.html. Accessed 2 May 2020

  14. Salesforce. https://www.salesforce.com/. Accessed 2 May 2020

  15. Oracle CRM. https://www.oracle.com/crmondemand/. Accessed 2 May 2020

  16. Cock, P.J., Fields, C.J., Goto, N., Heuer, M.L., Rice, P.M.: The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res. 38(6), 1767–1771 (2010)

    Article  Google Scholar 

  17. Nagle, D.F., Ganger, G.R., Butler, J., Goodson, G., Sabol, C.: Network support for network-attached storage. In: Proceedings of Hot Interconnects, Stanford University, Stanford, California, USA, August 1999

    Google Scholar 

  18. Richards, S., et al.: Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17(5), 405–423 (2015)

    Article  Google Scholar 

  19. Lee, J.J., Wedow, R., Okbay, A., et al.: Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50, 1112–1121 (2018)

    Article  Google Scholar 

  20. Sanchez-Roige, S., et al.: Genome-wide association studies of impulsive personality traits (BIS-11 and UPPS-P) and drug experimentation in up to 22,861 adult research participants identify loci in the CACNA1I and CADM2 genes. J. Neurosci. 39(13), 2562–2572 (2019)

    Google Scholar 

  21. Hamosh, A., Scott, A.F., Amberger, J.S., Bocchini, C.A., McKusick, V.A.: Online mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 33(Database issue), D514–D517 (2005)

    Google Scholar 

  22. OMIM - Online Mendelian Inheritance in Man, an Online Catalog of Human Genes and Genetic Disorders. https://www.omim.org/. Accessed 2 May 2020

  23. Pereanu, W., et al.: AutDB: a platform to decode the genetic architecture of autism. Nucleic Acids Res. 46(D1), D1049–D1054 (2018)

    Article  Google Scholar 

  24. Crider, K.S., Yang, T.P., Berry, R.J., Bailey, L.B.: Folate and DNA methylation: a review of molecular mechanisms and the evidence for folate’s role. Adv Nutr. 3(1), 21–38 (2012)

    Article  Google Scholar 

  25. Cruts, M., Theuns, J., Van Broeckhoven, C.: Locus-specific mutation databases for neurodegenerative brain diseases. Hum. Mutat. 33(9), 1340–1344 (2012)

    Article  Google Scholar 

  26. Alibaba Cloud. https://www.alibabacloud.com/. Accessed 3 May 2020

  27. ApsaraDB RDS for MySQL. https://www.alibabacloud.com/product/apsaradb-for-rds-mysql. Accessed 3 May 2020

  28. Elastic Compute Service. https://www.alibabacloud.com/product/ecs. Accessed 3 May 2020

  29. Spring Cloud. https://spring.io/projects/spring-cloud. Accessed 2 May 2020

  30. Spring Boot. https://spring.io/projects/spring-boot/. Accessed 2 May 2020

  31. Redis. https://redis.io/. Accessed 3 May 2020

  32. Swagger. https://swagger.io/. Accessed 3 May 2020

  33. MyBatis-Plus. https://mybatis.plus/en/. Accessed 3 May 2020

  34. Spring Cloud Gateway. https://spring.io/projects/spring-cloud-gateway. Accessed 3 May 2020

  35. Axios. https://github.com/axios/axios. Accessed 3 May 2020

  36. Vue - JavaScript Framework. https://vuejs.org/. Accessed 3 May 2020

  37. Francesco, P.D., Malavolta, I., Lago, P.: Research on architecting microservices: trends, focus, and potential for industrial adoption. In: IEEE International Conference on Software Architecture (ICSA), Gothenburg, pp. 21–30 (2017)

    Google Scholar 

  38. Apache Shiro. http://shiro.apache.org/. Accessed 3 May 2020

  39. Activiti. https://www.activiti.org/. Accessed 3 May 2020

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Acknowledgment

This work was partially supported by the Science Foundation of Beijing Language and Culture University (supported by “the Fundamental Research Funds for the Central Universities”) (20YJ040007, 19YJ040010, 17YJ0302).

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Correspondence to Jitao Yang .

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Yang, J. (2020). Customer Relationship Management for Personalized Nutrition Service. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12254. Springer, Cham. https://doi.org/10.1007/978-3-030-58817-5_70

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  • DOI: https://doi.org/10.1007/978-3-030-58817-5_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58816-8

  • Online ISBN: 978-3-030-58817-5

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