Author

Jonggeol Jeff Kim

National Institutes of Health

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Andrew SingletoniD· 2 shared Cornelis BlauwendraatiD· 2 shared Dan VitaleiD· 2 shared Hampton L. LeonardiD· 2 shared Hirotaka IwakiiD· 2 shared Mary B. MakariousiD· 2 shared Mike A. NallsiD· 2 shared Sara Bandrés‐CigaiD· 2 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersGenetics

Andrew SingletonORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data

Hampton L. Leonard, Ruqaya Murtadha, Alejandro Martínez-Carrasco, Alina Jama, Amica Corda Müller-Nedebock, Ana Luisa Gil-Martínez, Anastasia Illarionova, Anni K. Moore, Bernabé I. Bustos, Bharati Jadhav, Brook Huxford, Catherine S. Storm, Clodagh Towns, Dan Vitale, Devina Chetty, , Alastair John Noyce

The paper describes a virtual hackathon event that brought together early career scientists to develop tools for Parkinson's disease research using open science principles.

npj Parkinson s Disease · Mar 4, 2023Peer-reviewedGenetics

Multi-Modality Machine Learning Predicting Parkinsons Disease

Mary B. Makarious, Hampton L. Leonard, Dan Vitale, Hirotaka Iwaki, Lana J. Sargent, Anant Dadu, Ivo Violich, Elizabeth D. Hutchins, David Saffo, Sara Bandrés‐Ciga, Jonggeol Jeff Kim, Yeajin Song, Melina Maleknia, Matt Bookman, Willy Nojopranoto, , Mike A. Nalls

This paper develops an automated ML model to predict Parkinson's Disease using multi-modal data, achieving high AUC scores and constructing gene networks relevant to PD.

npj Parkinson s Disease · Apr 1, 2022Peer-reviewedGenomics