Nicolas Matentzoglu
Overview
Explore the profile of Nicolas Matentzoglu including associated specialties, affiliations and a list of published articles.
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31
Citations
1404
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Recent Articles
1.
Chimirri L, Caufield J, Bridges Y, Matentzoglu N, Gargano M, Cazalla M, et al.
medRxiv
. 2025 Mar;
PMID: 40061308
Background: Large language models (LLMs) are increasingly used in the medical field for diverse applications including differential diagnostic support. The estimated training data used to create LLMs such as the...
2.
Matentzoglu N, Bello S, Stefancsik R, Alghamdi S, Anagnostopoulos A, Balhoff J, et al.
Genetics
. 2025 Mar;
PMID: 40048704
Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a...
3.
Braun I, Hartley E, Olson D, Matentzoglu N, Schaper K, Walls R, et al.
JAMIA Open
. 2025 Feb;
8(1):ooaf001.
PMID: 39926165
Objectives: Demonstrate a methodology for improving discoverability of rare disease datasets by enriching source data with biological associations. Materials And Methods: We developed an extension of the Biolink semantic model...
4.
Hegde H, Vendetti J, Goutte-Gattat D, Caufield J, Graybeal J, Harris N, et al.
Database (Oxford)
. 2025 Jan;
2025.
PMID: 39841813
Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information systems. Most of these structures...
5.
Matentzoglu N, Bello S, Stefancsik R, Alghamdi S, Anagnostopoulos A, Balhoff J, et al.
bioRxiv
. 2024 Sep;
PMID: 39345458
Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a...
6.
Bridges Y, de Souza V, Cortes K, Haendel M, Harris N, Korn D, et al.
bioRxiv
. 2024 Jun;
PMID: 38915571
Background: Computational approaches to support rare disease diagnosis are challenging to build, requiring the integration of complex data types such as ontologies, gene-to-phenotype associations, and cross-species data into variant and...
7.
Caufield J, Hegde H, Emonet V, Harris N, Joachimiak M, Matentzoglu N, et al.
Bioinformatics
. 2024 Feb;
40(3).
PMID: 38383067
Motivation: Creating knowledge bases and ontologies is a time consuming task that relies on manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases, but current approaches...
8.
Putman T, Schaper K, Matentzoglu N, Rubinetti V, Alquaddoomi F, Cox C, et al.
Nucleic Acids Res
. 2023 Nov;
52(D1):D938-D949.
PMID: 38000386
Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global...
9.
Gargano M, Matentzoglu N, Coleman B, Addo-Lartey E, Anagnostopoulos A, Anderton J, et al.
Nucleic Acids Res
. 2023 Nov;
52(D1):D1333-D1346.
PMID: 37953324
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses...
10.
Caufield J, Putman T, Schaper K, Unni D, Hegde H, Callahan T, et al.
Bioinformatics
. 2023 Jun;
39(7).
PMID: 37389415
Motivation: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating...