Jennifer R. Riggs

612 total citations
23 papers, 342 citations indexed

About

Jennifer R. Riggs is a scholar working on Molecular Biology, Organic Chemistry and Hematology. According to data from OpenAlex, Jennifer R. Riggs has authored 23 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Organic Chemistry and 5 papers in Hematology. Recurrent topics in Jennifer R. Riggs's work include Click Chemistry and Applications (4 papers), Blood Coagulation and Thrombosis Mechanisms (4 papers) and Protein Degradation and Inhibitors (3 papers). Jennifer R. Riggs is often cited by papers focused on Click Chemistry and Applications (4 papers), Blood Coagulation and Thrombosis Mechanisms (4 papers) and Protein Degradation and Inhibitors (3 papers). Jennifer R. Riggs collaborates with scholars based in United States, Switzerland and France. Jennifer R. Riggs's co-authors include Thomas J. Bruno, Tara M. Lovestead, Marvin M. Hansen, Marcia L. Huber, Bret Windom, Mary E. Matyskiela, Philip P. Chamberlain, Joshua D. Hansen, Joseph J. McDonald and Lawrence G. Hamann and has published in prestigious journals such as Blood, CHEST Journal and Journal of Medicinal Chemistry.

In The Last Decade

Jennifer R. Riggs

22 papers receiving 327 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jennifer R. Riggs United States 12 109 101 71 58 46 23 342
Laurine G. Galya United States 13 99 0.9× 114 1.1× 38 0.5× 52 0.9× 50 1.1× 20 479
Anasuya Hazra United States 14 81 0.7× 81 0.8× 38 0.5× 102 1.8× 113 2.5× 30 522
Michelle Hutnik United States 7 84 0.8× 33 0.3× 31 0.4× 16 0.3× 30 0.7× 8 338
Walter C. Ogier United States 4 464 4.3× 58 0.6× 79 1.1× 111 1.9× 223 4.8× 5 625
Ming‐Hsiung Chen United States 11 139 1.3× 63 0.6× 66 0.9× 3 0.1× 72 1.6× 24 482
Masahide Kobayashi Japan 9 101 0.9× 146 1.4× 73 1.0× 69 1.2× 38 0.8× 37 437
Michael R. Myers United States 12 140 1.3× 195 1.9× 30 0.4× 23 0.4× 45 1.0× 31 441
M. A. Graham United Kingdom 14 265 2.4× 401 4.0× 159 2.2× 6 0.1× 70 1.5× 25 849
James W. Sawicki United States 10 114 1.0× 114 1.1× 42 0.6× 37 0.6× 20 0.4× 16 360
Kouji Inoue Japan 12 171 1.6× 71 0.7× 63 0.9× 90 1.6× 52 1.1× 39 507

Countries citing papers authored by Jennifer R. Riggs

Since Specialization
Citations

This map shows the geographic impact of Jennifer R. Riggs'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 Jennifer R. Riggs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jennifer R. Riggs more than expected).

Fields of papers citing papers by Jennifer R. Riggs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jennifer R. Riggs. 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 Jennifer R. Riggs. The network helps show where Jennifer R. Riggs may publish in the future.

Co-authorship network of co-authors of Jennifer R. Riggs

This figure shows the co-authorship network connecting the top 25 collaborators of Jennifer R. Riggs. A scholar is included among the top collaborators of Jennifer R. Riggs 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 Jennifer R. Riggs. Jennifer R. Riggs is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Riggs, Jennifer R., et al.. (2025). Leveraging efficiency metrics for the optimization of CELMoDs™ as cereblon-based molecular glue degraders. RSC Medicinal Chemistry. 16(5). 2117–2123. 3 indexed citations
2.
Luchini, Guilian, Shuang Liu, Emily C. Cherney, et al.. (2025). Application of Weighted Interaction-Fingerprints for Rationalizing Neosubstrate Potency and Selectivity of Cereblon-Based Molecular Glues. Journal of Medicinal Chemistry. 68(19). 20657–20674.
3.
Mascarenhas, John, Claire Harrison, Prithviraj Bose, et al.. (2024). Imetelstat Versus Best Available Therapy in Patients with Intermediate-2 or High-Risk Myelofibrosis Relapsed or Refractory to Janus Kinase Inhibitor in IMpactMF, a Randomized, Open-Label, Phase 3 Trial. Blood. 144(Supplement 1). 1808.1–1808.1. 3 indexed citations
4.
Robinson, Dale, Sogole Bahmanyar, Lida Tehrani, et al.. (2021). Structure-Guided Optimization Provides a Series of TTK Protein Inhibitors with Potent Antitumor Activity. Journal of Medicinal Chemistry. 64(17). 12670–12679. 5 indexed citations
5.
Riggs, Jennifer R., Rachel Lam, Sophia Kwon, et al.. (2019). FOOD INTAKE RESTRICTION FOR HEALTH OUTCOME SUPPORT AND EDUCATION (FIREHOUSE) TRIAL: STUDY DESIGN. CHEST Journal. 155(4). 227A–227A. 1 indexed citations
6.
Riggs, Jennifer R., Dale Robinson, Lida Tehrani, et al.. (2019). Design and Optimization Leading to an Orally Active TTK Protein Kinase Inhibitor with Robust Single Agent Efficacy. Journal of Medicinal Chemistry. 62(9). 4401–4410. 17 indexed citations
7.
Zhu, Dan, Shuichan Xu, Gordafaried Deyanat‐Yazdi, et al.. (2018). Synthetic Lethal Strategy Identifies a Potent and Selective TTK and CLK1/2 Inhibitor for Treatment of Triple-Negative Breast Cancer with a Compromised G1–S Checkpoint. Molecular Cancer Therapeutics. 17(8). 1727–1738. 28 indexed citations
8.
Riggs, Jennifer R., Alex Reyentovich, Matthew J. Maurer, & John A. Dodson. (2017). Frailty and Advanced Heart Failure in Older Adults. Current Cardiovascular Risk Reports. 11(5). 3 indexed citations
9.
Bruno, Thomas J., et al.. (2012). Comparison of JP-8 and JP-8+100 with the Advanced Distillation Curve Approach. Energy & Fuels. 26(9). 5843–5850. 12 indexed citations
10.
Rai, Roopa, Ken A. Brameld, Jennifer R. Riggs, et al.. (2011). 3-Heterocyclyl quinolone inhibitors of the HCV NS5B polymerase. Bioorganic & Medicinal Chemistry Letters. 22(1). 300–304. 15 indexed citations
11.
12.
Windom, Bret, et al.. (2010). Assessment of the Compositional Variability of RP-1 and RP-2 with the Advanced Distillation Curve Approach | NIST. 2 indexed citations
13.
Valiulin, R.A., et al.. (2009). Effect of Intramolecular Paternò−Büchi Reaction on the Thermodynamics and Kinetics of Nearly Degenerate [3,3]-Sigmatropic Shift in Fluxional Polycycles. The Journal of Organic Chemistry. 74(9). 3484–3490. 9 indexed citations
14.
15.
Rai, Roopa, Michael B. Shaghafi, Ellen M. Leahy, et al.. (2006). Efforts toward oral bioavailability in factor VIIa inhibitors. Bioorganic & Medicinal Chemistry Letters. 16(14). 3829–3832. 5 indexed citations
16.
Hu, Huiyong, Aleksandr Kolesnikov, Jennifer R. Riggs, et al.. (2006). Potent 4-amino-5-azaindole factor VIIa inhibitors. Bioorganic & Medicinal Chemistry Letters. 16(17). 4567–4570. 26 indexed citations
17.
Riggs, Jennifer R., Huiyong Hu, Aleksandr Kolesnikov, et al.. (2006). Novel 5-azaindole factor VIIa inhibitors. Bioorganic & Medicinal Chemistry Letters. 16(12). 3197–3200. 19 indexed citations
18.
Riggs, Jennifer R., Aleksandr Kolesnikov, Wendy B. Young, et al.. (2006). Factor VIIa inhibitors: A prodrug strategy to improve oral bioavailability. Bioorganic & Medicinal Chemistry Letters. 16(8). 2224–2228. 23 indexed citations
19.
Riggs, Jennifer R., et al.. (2006). Novel 5‐Azaindole Factor VIIa Inhibitors.. ChemInform. 37(38). 1 indexed citations
20.
Hansen, Marvin M. & Jennifer R. Riggs. (1998). A novel protecting group for hindered phenols. Tetrahedron Letters. 39(18). 2705–2706. 36 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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