World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
7803
World Ranking
6565
National Ranking
27

Overview

Robert Hoehndorf is affiliated with King Abdullah University of Science and Technology in Saudi Arabia. Their research primarily spans the fields of Biochemistry, Genetics and Molecular Biology as well as Computer Science, with a significant focus on subfields such as Molecular Biology, Artificial Intelligence, and Genetics.

Their work covers several specialized areas including Biomedical Text Mining and Ontologies, Bioinformatics and Genomic Networks, Semantic Web and Ontologies, Genomics and Rare Diseases, Topic Modeling, Machine Learning in Bioinformatics, and Natural Language Processing Techniques.

Notable recent publications by Robert Hoehndorf include:

  • Protein function prediction as approximate semantic entailment, 2024, Nature Machine Intelligence
  • DeepGOPlus: improved protein function prediction from sequence, 2021, Computer applications in the biosciences
  • Semantic similarity and machine learning with ontologies, 2020, Briefings in Bioinformatics
  • DeepGOZero: improving protein function prediction from sequence and zero-shot learning based on ontology axioms, 2022, Bioinformatics
  • DeepViral: prediction of novel virus-host interactions from protein sequences and infectious disease phenotypes, 2021, Bioinformatics

Robert Hoehndorf frequently collaborates with several co-authors, including Maxat Kulmanov, Georgios V. Gkoutos, Paul N. Schofield, Şenay Kafkas, and Fernando Zhapa-Camacho. These collaborations have produced a large body of work supporting advances in bioinformatics and related computational methods.

Their publications appear regularly in venues such as bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Bioinformatics, Journal of Biomedical Semantics, and Zenodo (CERN European Organization for Nuclear Research).

Best Publications

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

    Maxat Kulmanov;Mohammed Asif Khan;Robert Hoehndorf

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

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration.

    Damion M Dooley;Emma J Griffiths;Emma J Griffiths;Gurinder S Gosal;Pier Luigi Buttigieg

  • The role of ontologies in biological and biomedical research: a functional perspective

    Robert Hoehndorf;Paul N. Schofield;Georgios V. Gkoutos

  • Text-mining solutions for biomedical research: enabling integrative biology.

    Dietrich Rebholz-Schuhmann;Anika Oellrich;Robert Hoehndorf

  • The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery

    Michel Dumontier;Michel Dumontier;Christopher J. O. Baker;Joachim Baran;Alison Callahan

  • DeepGOPlus: improved protein function prediction from sequence.

    Maxat Kulmanov;Robert Hoehndorf

  • PhenomeNET: a whole-phenome approach to disease gene discovery

    Robert Hoehndorf;Paul Schofield;Georgios Vasileios Gkoutos

  • General Formal Ontology (GFO) - A Foundational Ontology Integrating Objects and Processes [Version 1.0]

    Heinrich Herre;Barbara Heller;Patryk Burek;Robert Hoehndorf

  • Neuro-symbolic representation learning on biological knowledge graphs.

    Mona Alshahrani;Mohammad Asif Khan;Omar Maddouri;Omar Maddouri;Akira R Kinjo

  • Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics.

    Martin Hrabě de Angelis;George Nicholson;Mohammed Selloum;Jacqueline K White

  • Semantic similarity and machine learning with ontologies

    Maxat Kulmanov;Fatima Zohra Smaili;Xin Gao;Robert Hoehndorf

  • OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction.

    Fatima Zohra Smaili;Xin Gao;Robert Hoehndorf

  • Semi-Supervised Entity Alignment via Knowledge Graph Embedding with Awareness of Degree Difference

    Shichao Pei;Lu Yu;Robert Hoehndorf;Xiangliang Zhang

  • The Units Ontology: a tool for integrating units of measurement in science

    Georgios V. Gkoutos;Paul N. Schofield;Robert Hoehndorf

  • Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations.

    Fatima Zohra Smaili;Xin Gao;Robert Hoehndorf

  • Protein function prediction as approximate semantic entailment

    Unknown

  • The anatomy of phenotype ontologies: principles, properties and applications.

    Georgios V Gkoutos;Paul N Schofield;Robert Hoehndorf

  • Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases

    Robert Hoehndorf;Paul N. Schofield;Georgios V. Gkoutos;Georgios V. Gkoutos

  • Evaluation of research in biomedical ontologies

    Robert Hoehndorf;Michel Dumontier;Georgios V. Gkoutos

  • Aber-OWL: a framework for ontology-based data access in biology.

    Robert Hoehndorf;Luke T. Slater;Luke T. Slater;Paul N. Schofield;Georgios V. Gkoutos

  • EL Embeddings: Geometric Construction of Models for the Description Logic EL++

    Maxat Kulmanov;Wang Liu-Wei;Yuan Yan;Robert Hoehndorf

Frequent Co-Authors

Georgios V. Gkoutos
Georgios V. Gkoutos University of Birmingham
Paul N. Schofield
Paul N. Schofield University of Cambridge
Michel Dumontier
Michel Dumontier Maastricht University
Janet Kelso
Janet Kelso Max Planck Society
Dietrich Rebholz-Schuhmann
Dietrich Rebholz-Schuhmann University of Cologne
Xin Gao
Xin Gao King Abdullah University of Science and Technology
Takashi Gojobori
Takashi Gojobori King Abdullah University of Science and Technology
John P. Sundberg
John P. Sundberg Vanderbilt University
Vladimir B. Bajic
Vladimir B. Bajic King Abdullah University of Science and Technology
Axel-Cyrille Ngonga Ngomo
Axel-Cyrille Ngonga Ngomo University of Paderborn

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