Print Email Facebook Twitter Finding biological markers for the prediction of colorectal cancer Title Finding biological markers for the prediction of colorectal cancer: Using machine learning methods to identify functional biomarkers in the human gut microbiome Author Sloof, Jos (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Abeel, T.E.P.M.F. (mentor) van der Toorn, E.A. (mentor) Calderon Franco, D. (mentor) Höllt, T. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2023-06-29 Abstract Colorectal cancer (CRC), one of the leading causes of mortality, is challenging to diagnose. By using metagenomic analysis with machine learning methods, this can be done in a non-invasive manner. In this research, a neural network has been trained on relative pathway abundance data, a way to measure the functional potential of a microbiome, in order to find biomarkers for colorectal cancer. The accuracy achieved by the neural network is 57%. The most important features used by the model are compared to established biomarkers in literature. Besides overlapping pathways, this research also found new potential biomarkers for CRC. Subject Colorectal CancerNeural NetworkBiomarkersMetagenomics To reference this document use: http://resolver.tudelft.nl/uuid:e55fbfa2-82d2-4744-b083-70311794c005 Part of collection Student theses Document type bachelor thesis Rights © 2023 Jos Sloof Files PDF CSE3000_Final_Paper_Jos_Sloof.pdf 4.72 MB Close viewer /islandora/object/uuid:e55fbfa2-82d2-4744-b083-70311794c005/datastream/OBJ/view