Nicole A Vasilevsky
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Explore the profile of Nicole A Vasilevsky including associated specialties, affiliations and a list of published articles.
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24
Citations
1525
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Recent Articles
1.
Mullen K, Tammen I, Matentzoglu N, Mather M, Balhoff J, Esdaile E, et al.
ArXiv
. 2024 Jun;
PMID: 38883236
Background: Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information-based tools to support advancement in diagnostics,...
2.
Callahan T, Tripodi I, Stefanski A, Cappelletti L, Taneja S, Wyrwa J, et al.
Sci Data
. 2024 Apr;
11(1):363.
PMID: 38605048
Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge...
3.
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...
4.
Carmody L, Gargano M, Toro S, Vasilevsky N, Adam M, Blau H, et al.
Med
. 2023 Nov;
4(12):913-927.e3.
PMID: 37963467
Background: Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize...
5.
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...
6.
Carmody L, Gargano M, Toro S, Vasilevsky N, Adam M, Blau H, et al.
medRxiv
. 2023 Jul;
PMID: 37503136
Navigating the vast landscape of clinical literature to find optimal treatments and management strategies can be a challenging task, especially for rare diseases. To address this task, we introduce the...
7.
Callahan T, Stefanski A, Wyrwa J, Zeng C, Ostropolets A, Banda J, et al.
NPJ Digit Med
. 2023 May;
6(1):89.
PMID: 37208468
Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and...
8.
Matentzoglu N, Goutte-Gattat D, Tan S, Balhoff J, Carbon S, Caron A, et al.
Database (Oxford)
. 2022 Oct;
2022.
PMID: 36208225
Similar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking and dependency management. To manage these processes, a...
9.
Dhombres F, Morgan P, Chaudhari B, Filges I, Sparks T, Lapunzina P, et al.
Am J Med Genet C Semin Med Genet
. 2022 Jul;
190(2):231-242.
PMID: 35872606
Technological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally. Phenotype-driven early genetic diagnosis of fetal genetic disease can...
10.
Jacobsen J, Baudis M, Baynam G, Beckmann J, Beltran S, Buske O, et al.
Nat Biotechnol
. 2022 Jun;
40(6):817-820.
PMID: 35705716
No abstract available.