Database Construction and Machine Learning Approach to Interogate the Microbiome for Different Diseases

dc.contributor.guideGandotra, Ekta and Kumar, Narendra
dc.coverage.spatial
dc.creator.researcherNadia
dc.date.accessioned2024-02-09T08:30:40Z
dc.date.available2024-02-09T08:30:40Z
dc.date.awarded2023
dc.date.completed2023
dc.date.registered2017
dc.description.abstractThe microbiome impacts many physiological functions, including homeostasis, inflammation, and other biochemical process. Dysbiosis (imbalance of friendly and pathogenic bacteria) of the microbiome thus has a variety of impacts on different pathways, possibly causing cancer. Human bodies are continually filled with transient and resident microbial cells and their by-products, including potentially harmful metabolites. According to recent studies, the microbiome may play a role in many diseases. Every person has a unique microbiome, which is influenced by their living conditions, dietary preferences, and environmental factors. It is vital that the microbiome dataset for the diseases be extended. Intestinal tissue healing and innate immunity depend on the nucleotide-binding domain-containing leucine-rich repeat-containing proteins (NLR protein). Most recently, it was incorporated into the group of innate immunity effector molecules. It is the largest family of proteins that helps regulate intestinal microbiota. It is crucial to the health of the gut microbiota and has recently been linked to the emergence of colitis-associated cancer (CAC) and ulcerative colitis (UC). Although these proteins played a key role in several cellular processes, despite the fact that the NLR proteins family is not well characterized, very few of these family proteins have been identified through experimental validation. Concerning these research gaps, the proposed thesis work has been conducted and the objectives are defined in the three different chapters (Chapters 2, 3 and 4). In the first objective, we developed a comprehensive microbiome dataset named Human OncoBiome Database (HOBD) that has data on various malignancies (Liver Cancer, Oral Cancer, Colorectal Cancer, and Breast Cancer). The HOBD has all the bacterial information newlinewith its taxonomic classification and other information involved in several malignancies. The database provides an attractive and easy-to-use Graphical user interface (GUI) so that any user can download the data
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extentxix, 131p
dc.identifier.urihttp://hdl.handle.net/10603/544653
dc.languageEnglish
dc.publisher.institutionDepartment of Bioinformatics
dc.publisher.placeSolan
dc.publisher.universityJaypee University of Information Technology, Solan
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordBiotechnology and Applied Microbiology
dc.subject.keywordCancer
dc.subject.keywordDatabase management
dc.subject.keywordLife Sciences
dc.subject.keywordMachine learning
dc.subject.keywordMetagenomics
dc.subject.keywordMicrobiology
dc.titleDatabase Construction and Machine Learning Approach to Interogate the Microbiome for Different Diseases
dc.title.alternative
dc.type.degreePh.D.

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