Paul Jung

1.7k total citations · 1 hit paper
24 papers, 1.0k citations indexed

About

Paul Jung is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Paul Jung has authored 24 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 8 papers in Hematology and 5 papers in Genetics. Recurrent topics in Paul Jung's work include Acute Myeloid Leukemia Research (7 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers) and Chronic Myeloid Leukemia Treatments (3 papers). Paul Jung is often cited by papers focused on Acute Myeloid Leukemia Research (7 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers) and Chronic Myeloid Leukemia Treatments (3 papers). Paul Jung collaborates with scholars based in United States, United Kingdom and Germany. Paul Jung's co-authors include Gerard D. Gagné, Ning Cao, Ernst U. Frevert, Bradley A. Zinker, Andrew Adler, Lemma Kifle, Philip R. Kym, William J. Chiou, Robert Dickinson and Rajesh Iyengar and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Paul Jung

22 papers receiving 1.0k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Identification and characterization of a small molecule AMPK activator that treats key components of type 2 diabetes and the metabolic syndrome

2006 733 citations Barbara L. Cool, Bradley A. Zinker et al. Cell Metabolism profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Paul Jung United States	10	776	355	251	192	179	24	1.0k
Lubing Zhou United States	16	555 0.7×	160 0.5×	173 0.7×	161 0.8×	108 0.6×	33	1.0k
Susan F. Murray United States	19	759 1.0×	257 0.7×	386 1.5×	444 2.3×	520 2.9×	25	1.5k
Panjamaporn Sangwung United States	18	750 1.0×	143 0.4×	62 0.2×	258 1.3×	234 1.3×	23	1.3k
Andrew Adler United States	10	770 1.0×	374 1.1×	268 1.1×	429 2.2×	161 0.9×	20	1.2k
Jennifer Wen United States	10	736 0.9×	211 0.6×	136 0.5×	225 1.2×	131 0.7×	14	1.1k
Lamar Galloway United States	12	1.2k 1.6×	403 1.1×	118 0.5×	343 1.8×	71 0.4×	17	1.5k
Yannan Xi United States	11	462 0.6×	77 0.2×	126 0.5×	174 0.9×	219 1.2×	13	897
Yunzhuo Ren China	20	536 0.7×	94 0.3×	78 0.3×	127 0.7×	148 0.8×	30	1.0k
Naoko Iino Japan	16	563 0.7×	153 0.4×	165 0.7×	147 0.8×	80 0.4×	23	1.0k
Pavani Mocharla Switzerland	17	665 0.9×	324 0.9×	253 1.0×	241 1.3×	123 0.7×	18	1.5k

Countries citing papers authored by Paul Jung

Since Specialization

Citations

This map shows the geographic impact of Paul Jung's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Paul Jung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Jung more than expected).

Fields of papers citing papers by Paul Jung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Jung. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Paul Jung. The network helps show where Paul Jung may publish in the future.

Co-authorship network of co-authors of Paul Jung

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Jung. A scholar is included among the top collaborators of Paul Jung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paul Jung. Paul Jung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Konopleva, Marina, Courtney D. DiNardo, Yan Sun, et al.. (2023). AML-095 Findings From an Analysis of Patients With Monocytic and Monocytic-Like Acute Myeloid Leukemia (AML), Including AML-M4 and AML-M5, Treated With Venetoclax (Ven) Plus Azacitidine (Aza). Clinical Lymphoma Myeloma & Leukemia. 23. S266–S267. 2 indexed citations

Konopleva, Marina, Courtney D. DiNardo, Yan Sun, et al.. (2023). P521: FINDINGS FROM AN ANALYSIS OF PATIENTS WITH MONOCYTIC AND MONOCYTIC-LIKE ACUTE MYELOID LEUKEMIA (AML), INCLUDING AML-M4 AND AML-M5, TREATED WITH VENETOCLAX (VEN) PLUS AZACITIDINE (AZA). HemaSphere. 7(S3). e160928c–e160928c.

Jung, Paul, Irmgard Bumeder, Philipp Kiewe, et al.. (2022). Genotype and Intensive Pretreatment Influence Outcome of Acute Myeloid Leukemia Patients Treated With Venetoclax in Combination With Hypomethylating Agents or Low-dose Cytarabine: “Real World” Data From Germany. HemaSphere. 6(9). e759–e759.

Pemmaraju, Naveen, Jacqueline S. Garcia, Jalaja Potluri, et al.. (2022). Addition of navitoclax to ongoing ruxolitinib treatment in patients with myelofibrosis (REFINE): a post-hoc analysis of molecular biomarkers in a phase 2 study. The Lancet Haematology. 9(6). e434–e444. 30 indexed citations

Nicolaou, K. C., Sanjay Kumar, Ananda Rao Podilapu, et al.. (2021). Design, Synthesis, and Biological Investigation of Thailanstatin A and Spliceostatin D Analogues Containing Tetrahydropyran, Tetrahydrooxazine, and Fluorinated Structural Motifs. The Journal of Organic Chemistry. 86(3). 2499–2521. 4 indexed citations

Harrison, Claire, Jacqueline S. Garcia, Ruben A. Mesa, et al.. (2020). MPN-038: Navitoclax in Combination with Ruxolitinib in Patients with Primary or Secondary Myelofibrosis: A Phase 2 Study. Clinical Lymphoma Myeloma & Leukemia. 20. S325–S325. 5 indexed citations

Pemmaraju, Naveen, Jacqueline S. Garcia, Jalaja Potluri, et al.. (2020). The Addition of Navitoclax to Ruxolitinib Demonstrates Efficacy within Different High-Risk Populations in Patients with Relapsed/Refractory Myelofibrosis. Blood. 136(Supplement 1). 49–50. 22 indexed citations

Terrillon, Sonia, Peter F. Bousquet, Diana L. Donnelly‐Roberts, et al.. (2020). NRF2 activator A-1396076 ameliorates inflammation in autoimmune disease models by inhibiting antigen dependent T cell activation. SHILAP Revista de lepidopterología. 4. 100079–100079. 9 indexed citations

Moody, Laura, Huan Wang, Paul Jung, Hong Chen, & Yuan‐Xiang Pan. (2019). Maternal and Post-Weaning High-Fat Diets Produce Distinct DNA Methylation Patterns in Hepatic Metabolic Pathways within Specific Genomic Contexts. International Journal of Molecular Sciences. 20(13). 3229–3229. 7 indexed citations

10.

Moody, Laura, et al.. (2018). Perinatal phthalate and high-fat diet exposure induce sex-specific changes in adipocyte size and DNA methylation. The Journal of Nutritional Biochemistry. 65. 15–25. 9 indexed citations

11.

Jung, Paul, et al.. (2017). Hepatic Fat Accumulation Regulates Carnitine Palmitoyltransferase 1 (Cpt1a) Expression through Coordinated Epigenetic Mechanisms. The FASEB Journal. 31(S1). 1 indexed citations

12.

Jung, Paul, et al.. (2017). Regulation of microRNA 378 through diet and exercise. The FASEB Journal. 31(S1). 1 indexed citations

13.

Winnick, Jason J., Christopher J. Ramnanan, Viswanathan Saraswathi, et al.. (2013). Effects of 11β-hydroxysteroid dehydrogenase-1 inhibition on hepatic glycogenolysis and gluconeogenesis. American Journal of Physiology-Endocrinology and Metabolism. 304(7). E747–E756. 15 indexed citations

14.

Jung, Paul, et al.. (2011). Global Transcriptomic Profiling Using Small Volumes of Whole Blood: A Cost-Effective Method for Translational Genomic Biomarker Identification in Small Animals. International Journal of Molecular Sciences. 12(4). 2502–2517. 7 indexed citations

15.

Warder, Scott E., Lora A. Tucker, Evelyn McKeegan, et al.. (2009). Reducing agent-mediated precipitation of high-abundance plasma proteins. Analytical Biochemistry. 387(2). 184–193. 48 indexed citations

16.

Pappano, William N., Paul Jung, Jonathan A. Meulbroek, et al.. (2009). Reversal of oncogene transformation and suppression of tumor growth by the novel IGF1R kinase inhibitor A-928605. BMC Cancer. 9(1). 314–314. 14 indexed citations

17.

Yang, Ruojing, Denise M. Wilcox, Deanna L. Haasch, et al.. (2007). Liver-specific Knockdown of JNK1 Up-regulates Proliferator-activated Receptor γ Coactivator 1β and Increases Plasma Triglyceride despite Reduced Glucose and Insulin Levels in Diet-induced Obese Mice. Journal of Biological Chemistry. 282(31). 22765–22774. 51 indexed citations

18.

Wilcox, Denise M., Ruojing Yang, Sherry J. Morgan, et al.. (2006). Delivery of RNAi reagents in murine models of obesity and diabetes.. Europe PMC (PubMed Central). 8 indexed citations

19.

Cool, Barbara L., Bradley A. Zinker, William J. Chiou, et al.. (2006). Identification and characterization of a small molecule AMPK activator that treats key components of type 2 diabetes and the metabolic syndrome. Cell Metabolism. 3(6). 403–416. 733 indexed citations breakdown →

20.

Jung, Paul, et al.. (1994). Hybridization of Alternating Cationic/Anionic Oligonucleotides to RNA Segments. Nucleosides and Nucleotides. 13(6-7). 1597–1605. 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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