ResearcherUniversity of PennsylvaniaActive in the last 2 years
Jina Ko
Matched on ORCID iD 0000-0002-4941-4234; OpenAlex author ID A5065605894. Sources: OpenAlex.
Their work
- Papers
- 4 (first author 0, last author 1)
- Trials
- 0
- Grants
- 0
- Labs led
- 0
- Collaborators
- 11
2017: 1 paper · 2018: 1 paper · 2019: none · 2020: 1 paper · 2021: none · 2022: none · 2023: none · 2024: 1 paper
Papers 4
- Anti-cancer bioactivity of sweet basil leaf derived extracellular vesicles on pancreatic cancer cells. Last author DOI 10.1002/jex2.142↗
- A Multianalyte Panel Consisting of Extracellular Vesicle miRNAs and mRNAs, cfDNA, and CA19-9 Shows Utility for Diagnosis and Staging of Pancreatic Ductal Adeno… Co-author DOI 10.1158/1078-0432.ccr-19-3313↗
- miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer. Co-author DOI 10.1158/0008-5472.can-17-3703↗
- Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes. Co-author DOI 10.1021/acsnano.7b05503↗
Closest collaborators
The 11 strongest of 11 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Uday K. Chintapula · 1 shared paper, 2024 · strength 0.28
- Neha Bhagwat · 3 shared papers, 2017–2020 · strength 0.23
- Paper A Multianalyte Panel Consisting of Extracellular Vesicle miRNAs and mRNAs, cfDNA, and CA19-9 Shows Utility for Diagnosi… DOI 10.1158/1078-0432.ccr-19-3313↗
- Paper miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer. DOI 10.1158/0008-5472.can-17-3703↗
- Paper Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes. DOI 10.1021/acsnano.7b05503↗
- Ben Z. Stanger · 3 shared papers, 2017–2020 · strength 0.23
- Paper A Multianalyte Panel Consisting of Extracellular Vesicle miRNAs and mRNAs, cfDNA, and CA19-9 Shows Utility for Diagnosi… DOI 10.1158/1078-0432.ccr-19-3313↗
- Paper miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer. DOI 10.1158/0008-5472.can-17-3703↗
- Paper Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes. DOI 10.1021/acsnano.7b05503↗
- David Aaron Issadore · 3 shared papers, 2017–2020 · strength 0.23
- Paper A Multianalyte Panel Consisting of Extracellular Vesicle miRNAs and mRNAs, cfDNA, and CA19-9 Shows Utility for Diagnosi… DOI 10.1158/1078-0432.ccr-19-3313↗
- Paper miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer. DOI 10.1158/0008-5472.can-17-3703↗
- Paper Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes. DOI 10.1021/acsnano.7b05503↗
- Erica L. Carpenter · 3 shared papers, 2017–2020 · strength 0.23
- Paper A Multianalyte Panel Consisting of Extracellular Vesicle miRNAs and mRNAs, cfDNA, and CA19-9 Shows Utility for Diagnosi… DOI 10.1158/1078-0432.ccr-19-3313↗
- Paper miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer. DOI 10.1158/0008-5472.can-17-3703↗
- Paper Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes. DOI 10.1021/acsnano.7b05503↗
- Mark H. O’Hara · 2 shared papers, 2017–2020 · strength 0.15
- Charles M. Vollmer · 1 shared paper, 2020 · strength 0.09
- Zijian Yang · 1 shared paper, 2020 · strength 0.09
- Jacob Edward Till · 1 shared paper, 2020 · strength 0.09
- Bryson W. Katona · 1 shared paper, 2020 · strength 0.09
- Nicole M. Aiello · 1 shared paper, 2017 · strength 0.06
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.