Multi-Omic Data Analysis for Small Intestine Insights

Nimble Science Ltd. seeks to leverage its extensive Small Intestine multi-omic datasets to uncover novel biological insights. The project aims to apply bioinformatic techniques to analyze these datasets, focusing on identifying patterns, correlations, and potential biomarkers relevant to intestinal health. Learners will utilize classroom knowledge in bioinformatics, data analysis, and molecular biology to tackle this challenge. The project involves processing and integrating genomic, metabolomic, and proteomic data to generate comprehensive insights. By the end of the project, learners will have developed a deeper understanding of multi-omic data analysis and its applications in real-world biological research. Key tasks include: - Preprocessing and cleaning multi-omic datasets. - Conducting statistical and computational analyses to identify significant patterns. - Visualizing data to highlight key findings. - Compiling a report summarizing insights and potential implications for intestinal health research.