Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/544653
Title: | Database Construction and Machine Learning Approach to Interogate the Microbiome for Different Diseases |
Researcher: | Nadia |
Guide(s): | Gandotra, Ekta and Kumar, Narendra |
Keywords: | Biotechnology and Applied Microbiology Cancer Database management Life Sciences Machine learning Metagenomics Microbiology |
University: | Jaypee University of Information Technology, Solan |
Completed Date: | 2023 |
Abstract: | The 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 |
Pagination: | xix, 131p |
URI: | http://hdl.handle.net/10603/544653 |
Appears in Departments: | Department of Bioinformatics |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 176 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 571.56 kB | Adobe PDF | View/Open | |
03_content.pdf | 324.97 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 149.31 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 1.38 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 725.1 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 979.86 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.74 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 502.8 kB | Adobe PDF | View/Open | |
10_annexures.pdf | 1.46 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 574.81 kB | Adobe PDF | View/Open |
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