Functional metagenomics: AI-based analysis of complex microbial interactionsApply
The amount of available protein sequence data is rapidly increasing, for example through applications of sequencing technologies to metagenomics. To understand biological phenomena on a molecular scale, it is crucial to determine the functions of proteins as well as their interactions. Experimental identification of protein functions will not scale to the current and rapidly increasing amount of available protein sequences. Function prediction methods using machine learning may be used to determine protein functions from their sequence. However, proteins rarely function alone but rely on other proteins to perform their function through direct and indirect interactions. The aim of the project is to computationally characterize the functions and interactions of proteins in metagenomes through the development and application of novel AI methods.
Program - BioEngineering
Division - Biological and Environmental Sciences and Engineering
Faculty Lab Link - https://cemse.kaust.edu.sa/borg
Center Affiliation - Computational Bioscience Research Center
Field of Study - Bioinformatics
Associate Professor, Computer Science
Professor Hoehndorf is interested in artificial intelligence, knowledge representation, biomedical informatics, ontology.
Desired Project Deliverables
Month 1: identification of AI methods, characterization of metagenomics dataset, technical presentation Month 2: preparation and preprocessing of metagenomics data (QC, assembly) Month 3: implementation of AI method and data analysis, evaluation Month 4: combination of AI methods: protein functions and interactions between proteins Month 5: evaluation results, quantitative characterization Month 6: write-up