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dc.contributor.advisorJoshi, Trupti, 1977-eng
dc.contributor.authorNarisetti, Siva Ratna Kumarieng
dc.date.issued2017eng
dc.date.submitted2017 Falleng
dc.descriptionDr. Trupti Joshi, Advisor.eng
dc.descriptionField of study: Computer science.eng
dc.descriptionIncludes vita.eng
dc.description"December 2017."eng
dc.description.abstractMulti-level 'OMICS' data integration for multiple organisms has been one of the major challenges in the era of advanced next generation sequencing and high performance technologies. Biological data has been producing tremendously fast with the availability of these high throughput sequencing technologies at low price and high speed. However, these data are often stored individually across different web resources based on data type and organism, making it difficult to find and integrate them. There are many websites available which store data from different data types and display that data in pie charts or plain text format but limit their data to only one fixed organism. These web-based multi-omics analysis is an efficient and easy way of analyzing the data but it would be difficult for other researchers working with other organisms and with complex data. The complex multi-omics data requires extensive data management, exhaustive computational analysis, and effective integration to have a one-stop interactive, web-based portal to browse, access, analyze, integrate and share knowledge about genomics and molecular mechanisms, with ultimate links to phenotypes and traits for many different organisms. To achieve this, we have developed Knowledge Base Commons (KBCommons), a platform that automates the process of establishing the database and making the tools available for organisms via a dedicated web resource. KBCommons is currently supporting four different categories including Plants and Crops; Animals and Pets; Humans and Diseases; Microbes and Viruses. It has four main functionalities including Browse KBCommons, Contribute to KB, Add version to KB, and Create a new KB. Using KBCommons, researchers from different groups with different organisms' data can be shared and accessed among all. KBCommons is an automatic framework which uses famous and widely used Laravel PHP framework. This is very efficient to deal with complex and diverse biological datasets. In the Browse KBCommons section, all existing organisms will be displayed under each category and it also shows organisms which can be used as model organisms. KBCommons also displays the logo of each organism along with existing versions, in this way it will give a detailed information on all existing organisms. The user can browse existing data of each organism using various tools including Blast, Multiple Sequence Alignment, Motif Sampler, etc., by going to that particular page. Users can also visualize gene expression and differential expression data via pie charts and plain text. Add version to KB and Create a new KB are related because of their similar steps in the process, users must bring corresponding data in each section. When a particular organism of interest is not existing then the user can create a new Knowledge Base for that new organism with 6 essential files of Genome Sequence, protein coding sequence for Amino acid, gene coding sequence for Nucleotide and Spliced mRNA transcripts, mRNA sequences in GFF3, and a functional annotation file. In Add version to KB, if an organism is already existing then the user can add a new version to the existing KB with these 6 essential files for the new version. In Contribute to KB, user can upload multi-omics data including Transcriptomics -- RNA-Seq and Microarray; Proteomics -- Mass Spectrometry and 2DGel; Epigenomics -- Bisulphite Sequencing, Methylation Array, and MBD-Seq Array. We support both gene expression/ protein expression/ or methylation data and differential expression comparison for each data type. We also support different entities including miRNA/sRNA, Metabolite, SNP/GWAS, Plant introduction lines/ Animal strains, and Phenotype/ TRAIT/Diseases.eng
dc.description.bibrefIncludes bibliographical references (pages 72-76).eng
dc.format.extent1 online resource (ix, 77 pages) : illustrationseng
dc.identifier.merlinb129198031eng
dc.identifier.oclc1099279553eng
dc.identifier.urihttps://hdl.handle.net/10355/66748
dc.identifier.urihttps://doi.org/10.32469/10355/66748eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.eng
dc.sourceSubmited to University of Missouri--Columbia Graduate School.eng
dc.titleDevelopment of KBCommons : universal informatics framework for multi-omics translational researcheng
dc.typeThesiseng
thesis.degree.disciplineComputer science (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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