D-Index & Metrics Best Publications

Robert Hoehndorf

King Abdullah University of Science and Technology
Saudi Arabia

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 37 Citations 4,759 195 World Ranking 6904 National Ranking 21

Overview

What is he best known for?

The fields of study Robert Hoehndorf is best known for:

Gene
Bioinformatics
Semantic Web

Semantics (computer science) and Software are fields of study that overlap with his Programming language research. He performs integrative study on Software and Programming language in his works. He performs multidisciplinary study in the fields of Ontology and Suggested Upper Merged Ontology via his papers. He undertakes interdisciplinary study in the fields of Suggested Upper Merged Ontology and Ontology through his research. His Epistemology study frequently links to other fields, such as Meaning (existential). Meaning (existential) is closely attributed to Epistemology in his work. Robert Hoehndorf performs integrative study on Gene and Computational biology in his works. His multidisciplinary approach integrates Computational biology and Genetics in his work. His study connects Sequence (biology) and Genetics.

His most cited work include:

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier (262 citations)
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (200 citations)
PhenomeNET: a whole-phenome approach to disease gene discovery (198 citations)

What are the main themes of his work throughout his whole career to date

In his work, Robert Hoehndorf performs multidisciplinary research in Ontology and Process ontology. He applies his multidisciplinary studies on Epistemology and Ontology in his research. Robert Hoehndorf conducts interdisciplinary study in the fields of Artificial intelligence and Data mining through his works. He integrates Gene with Annotation in his study. He conducted interdisciplinary study in his works that combined Annotation and Gene. He regularly links together related areas like Function (biology) in his Genetics studies. Function (biology) is closely attributed to Genetics in his work. Robert Hoehndorf incorporates Computational biology and Bioinformatics in his research. He integrates many fields in his works, including Bioinformatics and Computational biology.

Robert Hoehndorf most often published in these fields:

Ontology (53.21%)
Epistemology (53.21%)
Artificial intelligence (49.54%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

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

Dietrich Rebholz-Schuhmann;Anika Oellrich;Robert Hoehndorf.
Nature Reviews Genetics (2012)

259 Citations

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

Maxat Kulmanov;Mohammed Asif Khan;Robert Hoehndorf.
Bioinformatics (2018)

249 Citations

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

Robert Hoehndorf;Paul N. Schofield;Georgios V. Gkoutos.
Briefings in Bioinformatics (2015)

232 Citations

PhenomeNET: a whole-phenome approach to disease gene discovery

Robert Hoehndorf;Paul Schofield;Georgios Vasileios Gkoutos.
Nucleic Acids Research (2011)

225 Citations

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

Michel Dumontier;Michel Dumontier;Christopher J. O. Baker;Joachim Baran;Alison Callahan.
Journal of Biomedical Semantics (2014)

194 Citations

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.
Genome Biology (2019)

187 Citations

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

Heinrich Herre;Barbara Heller;Patryk Burek;Robert Hoehndorf.
(2006)

183 Citations

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.
Nature Genetics (2015)

130 Citations

Neuro-symbolic representation learning on biological knowledge graphs.

Mona Alshahrani;Mohammad Asif Khan;Omar Maddouri;Omar Maddouri;Akira R Kinjo.
Bioinformatics (2017)

113 Citations

DeepGOPlus: improved protein function prediction from sequence.

Maxat Kulmanov;Robert Hoehndorf.
Bioinformatics (2019)

108 Citations

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Frequent Co-Authors

External Links

Personal Website for Robert Hoehndorf