About Md Nurul Muttakin Md Nurul Muttakin M.S. (former), Computer Science protein function Biomedical Informatics Ontology engineering Md Nurul Muttakin completed his MSc in Computer Science at KAUST in 2023 under the supervision of Robert Hoehndorf. His research focused on machine learning methods for predicting protein function from three-dimensional structural information. His thesis, 3D conformation-based protein function prediction, investigated how structural information should be exploited by deep learning models in light of the availability of near-experimental-accuracy structures from AlphaFold. Almost all existing structure-aware protein function predictors combine graph neural networks (GNNs) operating on 2D Projects Related Projects 2022 Computational methods for functional metagenomics: from protein functions to multi-scale interactions Sat, Jan 1 2022 - Tue, Dec 31 2024 Applied Ontology Microbial communities Neuro-Symbolic AI protein function Metagenomic sequencing has made it routine to read the DNA of an entire microbial community, but most analysis pipelines stop at taxonomic composition or at the level of individual protein families. The really biologically informative questions, which proteins do what, which proteins interact, which metabolic pathways are reconstructible, and how the community as a whole interacts with its environment or host, remain largely out of reach computationally. Even associations that are very robust empirically, for example between gut microbiome composition and colorectal cancer or inflammatory
Computational methods for functional metagenomics: from protein functions to multi-scale interactions Sat, Jan 1 2022 - Tue, Dec 31 2024 Applied Ontology Microbial communities Neuro-Symbolic AI protein function Metagenomic sequencing has made it routine to read the DNA of an entire microbial community, but most analysis pipelines stop at taxonomic composition or at the level of individual protein families. The really biologically informative questions, which proteins do what, which proteins interact, which metabolic pathways are reconstructible, and how the community as a whole interacts with its environment or host, remain largely out of reach computationally. Even associations that are very robust empirically, for example between gut microbiome composition and colorectal cancer or inflammatory
