Christopher J Mungall
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Explore the profile of Christopher J Mungall including associated specialties, affiliations and a list of published articles.
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144
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13839
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Recent Articles
11.
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...
12.
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,...
13.
Danis D, Bamshad M, Bridges Y, Cacheiro P, Carmody L, Chong J, et al.
medRxiv
. 2024 Jun;
PMID: 38854034
The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual,...
14.
Eloe-Fadrosh E, Mungall C, Miller M, Smith M, Patil S, Kelliher J, et al.
Methods Mol Biol
. 2024 May;
2802:587-609.
PMID: 38819573
Comparative analysis of (meta)genomes necessitates aggregation, integration, and synthesis of well-annotated data using standards. The Genomic Standards Consortium (GSC) collaborates with the research community to develop and maintain the Minimum...
15.
Chan L, Casiraghi E, Reese J, Harmon Q, Schaper K, Hegde H, et al.
Int J Med Inform
. 2024 Apr;
187:105461.
PMID: 38643701
Objective: Female reproductive disorders (FRDs) are common health conditions that may present with significant symptoms. Diet and environment are potential areas for FRD interventions. We utilized a knowledge graph (KG)...
16.
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...
17.
Schadt C, Martin S, Carrell A, Fortner A, Hopp D, Jacobson D, et al.
Sci Data
. 2024 Apr;
11(1):339.
PMID: 38580669
Bridging molecular information to ecosystem-level processes would provide the capacity to understand system vulnerability and, potentially, a means for assessing ecosystem health. Here, we present an integrated dataset containing environmental...
18.
Cappelletti L, Rekerle L, Fontana T, Hansen P, Casiraghi E, Ravanmehr V, et al.
Bioinform Adv
. 2024 Apr;
4(1):vbae036.
PMID: 38577542
Motivation: Graph representation learning is a family of related approaches that learn low-dimensional vector representations of nodes and other graph elements called embeddings. Embeddings approximate characteristics of the graph and...
19.
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...
20.
Groza T, Caufield H, Gration D, Baynam G, Haendel M, Robinson P, et al.
BMC Med Inform Decis Mak
. 2024 Jan;
24(1):30.
PMID: 38297371
Objective: Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare...