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https://github.com/duartebred/mapping-omics-datasets-on-kegg-metabolic-pathways

Repository for the presentation of work developed by the student Duarte Velho for the UC Project, of the Master in Bioinformatics of the University of Minho, academic year 23-24.
https://github.com/duartebred/mapping-omics-datasets-on-kegg-metabolic-pathways

bioinformatics-tool kegg-pathway metabolic-network metabolic-pathways-mapping metagenomics

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Repository for the presentation of work developed by the student Duarte Velho for the UC Project, of the Master in Bioinformatics of the University of Minho, academic year 23-24.

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# Mapping Omics datasets on KEGG Metabolic Pathways



# Index

- [Context and Motivation](#context-and-motivation)

- [Objective](#Objective-of-the-project)

- [Key Features](#key-features)

- [Credits](#credits)

  

# Context and Motivation



KEGG (Kyoto Encyclopedia of Genes and Genomes) is a comprehensive database resource that integrates genomic, chemical, and systemic functional information. Specifically, KEGG metabolic maps provide a visual representation of metabolic pathways, offering insights into the complex biological systems. KEGGCharter emerges as a tool designed to superimpose differential gene expression and taxonomy information onto KEGG metabolic maps, utilizing Biopython for manipulation and visualization. Presently, KEGGCharter depicts differential gene expression and gene taxonomic assignment as separate entities on the maps. This separation limits the utility in directly associating microbial identities with gene expression data within a unified visual context.




## Objective of the project



In this work, the plots of KEGGCharter will be expanded to include multi-level representation of gene expression information. The work will involve developing new interactive representations over the currently outputted plots, to allows the inclusion of more information in metabolic maps.




## Key Features

- **Interactive Visualization**: Dive deeper into the metabolic pathways with interactive elements that reveal intricate details of gene expression and microbial taxonomy in a singular, cohesive map.

- **Multi-Level Taxonomic Representation**: Navigate through various taxonomic levels directly on the KEGG maps, enriching the contextual understanding of the data.

- **Direct Data Access**: Obtain numeric values and detailed information with just a click, simplifying data analysis and interpretation.

- **Enhanced Connectivity**: Seamlessly access related online databases through embedded links and cross-references, expanding the research horizon.



## Credits



This project was developed by student [Duarte Velho](https://github.com/duartebred) (PG53481), under the guidance of [João Sequeira](https://github.com/iquasere) and Andreia Salvador, in collaboration with the Center of Biological Engineering - University of Minho (CEB-UM).





This repository was created as part of the UC Project (2023/24), of the Master's Degree in Bioinformatics at the School of Engineering of the University of Minho, and aims to bring together the scripts built throughout the work, as well as articles in their different versions, presentation slides and all relevant supplementary material (data, results, software developed, etc).

This repository stands out for the originality and authorship of the written code.




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Visit [KEGGCharter on GitHub](https://github.com/iquasere/KEGGCharter), and [paper](https://www.sciencedirect.com/science/article/pii/S2001037022001179) for more information and updates.

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