Richard Zang

1.7k total citations
10 papers, 424 citations indexed

About

Richard Zang is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Richard Zang has authored 10 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Oncology and 3 papers in Computational Theory and Mathematics. Recurrent topics in Richard Zang's work include Computational Drug Discovery Methods (3 papers), Cancer Mechanisms and Therapy (2 papers) and Drug Transport and Resistance Mechanisms (2 papers). Richard Zang is often cited by papers focused on Computational Drug Discovery Methods (3 papers), Cancer Mechanisms and Therapy (2 papers) and Drug Transport and Resistance Mechanisms (2 papers). Richard Zang collaborates with scholars based in United States, Switzerland and Canada. Richard Zang's co-authors include Tove Tuntland, Ty Gould, Takatoshi Kosaka, Brian Ethell, Keith Hoffmaster, Francesca Blasco, Monish Jain, Donglu Zhang, Gautham Gampa and Yurong Lai and has published in prestigious journals such as Blood, Cancer Research and Journal of Medicinal Chemistry.

In The Last Decade

Richard Zang

10 papers receiving 410 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Richard Zang United States 7 161 104 72 49 34 10 424
Benjamin Zeskind Israel 7 202 1.3× 44 0.4× 105 1.5× 25 0.5× 58 1.7× 17 507
Jyotika Varshney United States 15 207 1.3× 54 0.5× 67 0.9× 24 0.5× 39 1.1× 25 493
Piush Sharma India 6 186 1.2× 135 1.3× 34 0.5× 23 0.5× 25 0.7× 9 571
Naiem T. Issa United States 11 323 2.0× 74 0.7× 194 2.7× 54 1.1× 87 2.6× 49 749
Giovanni Bocci United States 11 400 2.5× 62 0.6× 225 3.1× 57 1.2× 46 1.4× 14 785
Hiroshi Sugimoto Japan 11 128 0.8× 111 1.1× 69 1.0× 26 0.5× 24 0.7× 24 363
Ishrat Jabeen Pakistan 14 234 1.5× 114 1.1× 111 1.5× 45 0.9× 9 0.3× 50 559
Natalia Khuri United States 11 312 1.9× 236 2.3× 89 1.2× 46 0.9× 32 0.9× 32 685
Víctor Mangas‐Sanjuán Spain 10 101 0.6× 54 0.5× 75 1.0× 39 0.8× 39 1.1× 45 425
Soma Barman India 16 412 2.6× 71 0.7× 109 1.5× 20 0.4× 27 0.8× 57 771

Countries citing papers authored by Richard Zang

Since Specialization
Citations

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

Fields of papers citing papers by Richard Zang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard Zang. 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 Richard Zang. The network helps show where Richard Zang may publish in the future.

Co-authorship network of co-authors of Richard Zang

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

All Works

10 of 10 papers shown
1.
Yu, Ming, et al.. (2024). The search for pyruvate kinase-R activators; from a HTS screening hit via an impurity to the discovery of a lead series. Bioorganic & Medicinal Chemistry Letters. 110. 129865–129865. 1 indexed citations
2.
Zang, Richard, Harvey Wong, Jan Mařı́k, et al.. (2022). Design and Measurement of Drug Tissue Concentration Asymmetry and Tissue Exposure-Effect (Tissue PK-PD) Evaluation. Journal of Medicinal Chemistry. 65(13). 8713–8734. 17 indexed citations
3.
Chen, A., Andy H.F. Chow, Aaron Davidson, et al.. (2020). Developments in MLflow. 1–4. 54 indexed citations
4.
Han, Wooseok, Yu Ding, Zheng Chen, et al.. (2020). Synthesis and Structure–Activity Relationship of Tetra-Substituted Cyclohexyl Diol Inhibitors of Proviral Insertion of Moloney Virus (PIM) Kinases. Journal of Medicinal Chemistry. 63(23). 14885–14904. 4 indexed citations
5.
Zhang, Donglu, Cornelis E. C. A. Hop, Gabriela I. Patilea‐Vrana, et al.. (2019). Special Section on Pharmacokinetic and Drug Metabolism Properties of Novel Therapeutic Modalities–Minireview. Drug Metabolism and Disposition. 47(10). 1122–1135. 81 indexed citations
6.
Spilker, Mary E., Richard Zang, Handan He, et al.. (2019). Applications of Quantitative Systems Pharmacology in Model‐Informed Drug Discovery: Perspective on Impact and Opportunities. CPT Pharmacometrics & Systems Pharmacology. 8(11). 777–791. 60 indexed citations
7.
Tuntland, Tove, Brian Ethell, Takatoshi Kosaka, et al.. (2014). Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research. Frontiers in Pharmacology. 5. 174–174. 152 indexed citations
8.
Zang, Richard, et al.. (2014). A Typology of Revenue Models for Community Health Worker Programs. 9(2). 93–105. 3 indexed citations
9.
García, Pablo D., John L. Langowski, Jocelyn Holash, et al.. (2013). The Pan-PIM Kinase Inhibitor LGH447 Shows Activity In PIM2-Dependent Multiple Myeloma and In AML Models. Blood. 122(21). 1666–1666. 11 indexed citations
10.
Stuart, Darrin D., Nanxin Li, Daniel J. Poon, et al.. (2012). Abstract 3790: Preclinical profile of LGX818: A potent and selective RAF kinase inhibitor. Cancer Research. 72(8_Supplement). 3790–3790. 41 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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2026