Suhasini Iyer

3.0k total citations
54 papers, 2.2k citations indexed

About

Suhasini Iyer is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Immunology. According to data from OpenAlex, Suhasini Iyer has authored 54 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 24 papers in Radiology, Nuclear Medicine and Imaging and 17 papers in Immunology. Recurrent topics in Suhasini Iyer's work include Monoclonal and Polyclonal Antibodies Research (23 papers), Heme Oxygenase-1 and Carbon Monoxide (17 papers) and CAR-T cell therapy research (11 papers). Suhasini Iyer is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (23 papers), Heme Oxygenase-1 and Carbon Monoxide (17 papers) and CAR-T cell therapy research (11 papers). Suhasini Iyer collaborates with scholars based in United States, France and Switzerland. Suhasini Iyer's co-authors include Roland Buelow, Rong Deng, Saileta Prabhu, Paul J. Fielder, Amrita V. Kamath, Jacky Woo, Frank‐Peter Theil, Deborah L. Mortensen, Laura DeForge and Kyra J. Cowan and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Blood.

In The Last Decade

Suhasini Iyer

53 papers receiving 2.1k citations

Peers

Suhasini Iyer
Nina Grosser Germany
D. Neumeier Germany
Keith N. Stewart United Kingdom
Uma Sinha United States
Ashish Saxena United States
Nina Grosser Germany
Suhasini Iyer
Citations per year, relative to Suhasini Iyer Suhasini Iyer (= 1×) peers Nina Grosser

Countries citing papers authored by Suhasini Iyer

Since Specialization
Citations

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

Fields of papers citing papers by Suhasini Iyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suhasini Iyer

This figure shows the co-authorship network connecting the top 25 collaborators of Suhasini Iyer. A scholar is included among the top collaborators of Suhasini Iyer 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 Suhasini Iyer. Suhasini Iyer 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.
Dalvi, Pranjali, Kevin Dang, James P. Allison, et al.. (2025). Inhibition of CD38 enzyme activity on engrafted human immune cells enhances NAD+ metabolism and inhibits inflammation in an in-vivo model of xeno-GvHD. Frontiers in Immunology. 16. 1640611–1640611.
2.
Dang, Kevin, Laure‐Hélène Ouisse, Benjamin Buelow, et al.. (2022). TNB-738, a biparatopic antibody, boosts intracellular NAD+ by inhibiting CD38 ecto-enzyme activity. mAbs. 14(1). 2095949–2095949. 19 indexed citations
3.
Leabman, Maya K., Y. Gloria Meng, Robert F. Kelley, et al.. (2013). Effects of altered FcγR binding on antibody pharmacokinetics in cynomolgus monkeys. mAbs. 5(6). 896–903. 83 indexed citations
4.
Ng, Chee M., Kelly M. Loyet, Suhasini Iyer, Paul J. Fielder, & Rong Deng. (2013). Modeling approach to investigate the effect of neonatal Fc receptor binding affinity and anti-therapeutic antibody on the pharmacokinetic of humanized monoclonal anti-tumor necrosis factor-α IgG antibody in cynomolgus monkey. European Journal of Pharmaceutical Sciences. 51. 51–58. 24 indexed citations
5.
Marathe, Anshu, Suhasini Iyer, Zhihua Qiu, Jennifer Visich, & Donald E. Mager. (2012). Pharmacokinetics and Pharmacodynamics of Anti-BR3 Monoclonal Antibody in Mice. Pharmaceutical Research. 29(11). 3180–3187. 1 indexed citations
6.
Deng, Rong, Y. Gloria Meng, Kwame Hoyte, et al.. (2012). Subcutaneous bioavailability of therapeutic antibodies as a function 
of FcRn binding affinity in mice. mAbs. 4(1). 101–109. 66 indexed citations
7.
Jackman, Janet, Yongmei Chen, Arthur Huang, et al.. (2010). Development of a Two-part Strategy to Identify a Therapeutic Human Bispecific Antibody That Inhibits IgE Receptor Signaling. Journal of Biological Chemistry. 285(27). 20850–20859. 68 indexed citations
8.
Deng, Rong, Kelly M. Loyet, Samantha Lien, et al.. (2010). Pharmacokinetics of Humanized Monoclonal Anti-Tumor Necrosis Factor-α Antibody and Its Neonatal Fc Receptor Variants in Mice and Cynomolgus Monkeys. Drug Metabolism and Disposition. 38(4). 600–605. 92 indexed citations
9.
Stefanich, Eric, et al.. (2008). Evidence for an Asialoglycoprotein Receptor on Nonparenchymal Cells for O-Linked Glycoproteins. Journal of Pharmacology and Experimental Therapeutics. 327(2). 308–315. 23 indexed citations
10.
Lazarov, Mirella, et al.. (2005). Topical Application of A Novel Immunomodulatory Peptide, RDP58, Reduces Skin Inflammation in the Phorbol Ester-Induced Dermatitis Model. Journal of Investigative Dermatology. 125(3). 473–481. 63 indexed citations
11.
Gao, Lan, Jing Wang, Katja Kotsch, et al.. (2004). RDP58, a novel immunomodulatory peptide, ameliorates clinical signs of disease in the Lewis rat model of acute experimental autoimmune encephalomyelitis. Journal of Neuroimmunology. 152(1-2). 33–43. 17 indexed citations
12.
Araujo, Jesús A., Lingzhong Meng, Aaron D. Tward, et al.. (2003). Systemic Rather Than Local Heme Oxygenase-1 Overexpression Improves Cardiac Allograft Outcomes in a New Transgenic Mouse. The Journal of Immunology. 171(3). 1572–1580. 73 indexed citations
13.
Katori, Masamichi, Roland Buelow, Bibo Ke, et al.. (2002). HEME OXYGENASE-1 OVEREXPRESSION PROTECTS RAT HEARTS FROM COLD ISCHEMIA/REPERFUSION INJURY VIA AN ANTIAPOPTOTIC PATHWAY1. Transplantation. 73(2). 287–292. 141 indexed citations
14.
Iyer, Suhasini, Roger Lahana, & Roland Buelow. (2002). Rational Design and Development of RDP58. Current Pharmaceutical Design. 8(24). 2217–2229. 20 indexed citations
15.
Li, Wei, Suhasini Iyer, Lina Lü, et al.. (2002). Attenuation of aortic graft arteriosclerosis by systemic administration of Allotrap peptide RDP58. Transplant International. 16(12). 849–856. 8 indexed citations
16.
Woo, Jacky, et al.. (2000). ALLEVIATION OF GRAFT-VERSUS-HOST DISEASE AFTER CONDITIONING WITH COBALT-PROTOPORPHYRIN, AN INDUCER OF HEME OXYGENASE-1. Transplantation. 69(4). 623–633. 43 indexed citations
17.
Iyer, Suhasini, et al.. (2000). Inhibition of Tumor Necrosis Factor mRNA Translation by a Rationally Designed Immunomodulatory Peptide. Journal of Biological Chemistry. 275(22). 17051–17057. 37 indexed citations
18.
Iyer, Suhasini, Jacky Woo, Lan Gao, et al.. (1998). Characterization and Biological Significance of Immunosuppressive Peptide D2702.75–84(E → V) Binding Protein. Journal of Biological Chemistry. 273(5). 2692–2697. 49 indexed citations
19.
Grassy, Gérard, Bernard Calas, Abdelaziz Yasri, et al.. (1998). Computer-assisted rational design of immunosuppressive compounds. Nature Biotechnology. 16(8). 748–752. 75 indexed citations
20.
Woo, Jacky, et al.. (1997). Immunosuppression By D-Isomers Of Hla Class I Heavy Chain (Amino Acid 75 To 84)-Derived Peptides Is Independent Of Binding To Hsc70. Transplantation. 64(10). 1460–1467. 19 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026