Hoehndorf, Robert

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

Kulmanov, M., Khan, M. A., & Hoehndorf, R. (2018) · Bioinformatics

Machine Learning in BioinformaticsBioinformatics and Genomic Networks

Cited by 558

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Zhou, N., Jiang, Y., Bergquist, T. R., Lee, A. J., Kacsoh, B. Z., Crocker, A. W., Lewis, K. A., Georghiou, G., Nguyen, H. N., Hamid, M. N., et al. (2019) · Genome Biology

Bioinformatics and Genomic NetworksGenomics and Phylogenetic Studies

Cited by 452

Protein function prediction as approximate semantic entailment

Kulmanov, M., Guzmán-Vega, F. J., Duek Roggli, P., Lane, L., Arold, S. T., & Hoehndorf, R. (2024) · Nature Machine Intelligence

Machine Learning in BioinformaticsBioinformatics and Genomic Networks

Cited by 131

DeepGO-SE: Protein function prediction as Approximate Semantic Entailment

Kulmanov, M., Guzmán-Vega, F., Duek, P., Lane, L., Arold, S., & Hoehndorf, R. (2023) · Nature Machine Intelligence

Machine Learning in BioinformaticsBioinformatics and Genomic Networks

Cited by 129

DeepPVP: phenotype-based prioritization of causative variants using deep learning

Boudellioua, I., Kulmanov, M., Schofield, P. N., Gkoutos, G. V., & Hoehndorf, R. (2019) · BMC Bioinformatics

Genomics and Rare DiseasesGenetic Associations and Epidemiology

Cited by 79