Thomas Chittenden

4.4k total citations · 1 hit paper
25 papers, 3.4k citations indexed

About

Thomas Chittenden is a scholar working on Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Thomas Chittenden has authored 25 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Oncology, 11 papers in Molecular Biology and 11 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Thomas Chittenden's work include HER2/EGFR in Cancer Research (13 papers), Monoclonal and Polyclonal Antibodies Research (11 papers) and CAR-T cell therapy research (4 papers). Thomas Chittenden is often cited by papers focused on HER2/EGFR in Cancer Research (13 papers), Monoclonal and Polyclonal Antibodies Research (11 papers) and CAR-T cell therapy research (4 papers). Thomas Chittenden collaborates with scholars based in United States, France and Czechia. Thomas Chittenden's co-authors include Alexander Zaika, Ute M. Moll, Oleksi Petrenko, Motohiro Mihara, Petr Pančoška, Susan Erster, Victor S. Goldmacher, Laura M. Bartle, Anna Skaletskaya and Edward S. Mocarski and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and Molecular Cell.

In The Last Decade

Thomas Chittenden

25 papers receiving 3.4k citations

Hit Papers

align trajectories

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.

p53 Has a Direct Apoptogenic Role at the Mitochondria

2003 1.4k citations Motohiro Mihara, Susan Erster et al. Molecular Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas Chittenden United States	11	1.8k	1.5k	712	525	500	25	3.4k
Mark Rolfe United States	31	4.6k 2.5×	2.5k 1.6×	463 0.7×	407 0.8×	191 0.4×	55	6.0k
Hsing‐Jien Kung United States	36	2.1k 1.1×	1.1k 0.7×	529 0.7×	514 1.0×	256 0.5×	91	3.9k
Hannah Rabinowich United States	37	2.0k 1.1×	1.1k 0.7×	782 1.1×	2.0k 3.8×	163 0.3×	63	4.0k
Debra T. Chao United States	18	2.9k 1.6×	1.1k 0.7×	352 0.5×	1.2k 2.3×	209 0.4×	28	4.3k
Colin Nixon United Kingdom	38	3.0k 1.6×	1.4k 0.9×	837 1.2×	727 1.4×	105 0.2×	94	5.1k
Lyudmila G. Burdelya United States	22	1.2k 0.7×	1.3k 0.9×	198 0.3×	1.3k 2.4×	455 0.9×	35	3.1k
Laura M. Bartle United States	17	892 0.5×	530 0.4×	845 1.2×	544 1.0×	256 0.5×	27	2.2k
José Antonio Rodríguez Spain	36	2.9k 1.6×	1.5k 1.0×	309 0.4×	239 0.5×	100 0.2×	102	4.5k
Mikhail A. Nikiforov United States	30	2.1k 1.1×	580 0.4×	269 0.4×	274 0.5×	140 0.3×	69	2.8k
Kelvin P. Lee United States	40	2.3k 1.2×	1.5k 1.0×	473 0.7×	3.1k 5.9×	259 0.5×	106	5.7k

Countries citing papers authored by Thomas Chittenden

Since Specialization

Citations

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

Fields of papers citing papers by Thomas Chittenden

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Chittenden

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Chittenden. A scholar is included among the top collaborators of Thomas Chittenden 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 Thomas Chittenden. Thomas Chittenden 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

Gera, Nimish, Vijay Ramesh, Deepak Kanojia, et al.. (2024). MYTX-011: A pH-Dependent Anti–c-MET Antibody–Drug Conjugate Designed for Enhanced Payload Delivery to c-MET–Expressing Tumor Cells. Molecular Cancer Therapeutics. 23(9). 1282–1293. 8 indexed citations

Kovtun, Yelena, Gregory E. Jones, Sharlene Adams, et al.. (2018). A CD123-targeting antibody-drug conjugate, IMGN632, designed to eradicate AML while sparing normal bone marrow cells. Blood Advances. 2(8). 848–858. 129 indexed citations

Liu, Yimao, Katharine C. Lai, Luke Harris, et al.. (2018). Abstract 2900: Evaluation of endoglin/CD105 as a tumor vasculature target with antibody drug conjugates. Cancer Research. 78(13_Supplement). 2900–2900. 2 indexed citations

Adams, Sharlene, Alan Wilhelm, Lauren Harvey, et al.. (2016). IMGN632: A CD123-Targeting Antibody-Drug Conjugate (ADC) with a Novel DNA-Alkylating Payload, Is Highly Active and Prolongs Survival in Acute Myeloid Leukemia (AML) Xenograft Models. Blood. 128(22). 2832–2832. 13 indexed citations

Ab, Olga, Kathleen R. Whiteman, Laura M. Bartle, et al.. (2015). IMGN853, a Folate Receptor-α (FRα)–Targeting Antibody–Drug Conjugate, Exhibits Potent Targeted Antitumor Activity against FRα-Expressing Tumors. Molecular Cancer Therapeutics. 14(7). 1605–1613. 160 indexed citations

Deckert, Jutta, Marie-Cécile Wetzel, Laura M. Bartle, et al.. (2014). SAR650984, A Novel Humanized CD38-Targeting Antibody, Demonstrates Potent Antitumor Activity in Models of Multiple Myeloma and Other CD38+ Hematologic Malignancies. Clinical Cancer Research. 20(17). 4574–4583. 245 indexed citations

Setiady, Yulius Y., Ling Dong, Anna Skaletskaya, et al.. (2014). Abstract 4513: IMGN289, an EGFR-targeting antibody-drug conjugate, is effective against tumor cells that are resistant to EGFR tyrosine kinase inhibitors. Cancer Research. 74(19_Supplement). 4513–4513. 3 indexed citations

Deckert, Jutta, Peter U. Park, Yong Weon Yi, et al.. (2013). A novel anti-CD37 antibody-drug conjugate with multiple anti-tumor mechanisms for the treatment of B-cell malignancies. Blood. 122(20). 3500–3510. 67 indexed citations

Chittenden, Thomas, Yulius Y. Setiady, Peter U. Park, et al.. (2013). Abstract 5467: IMGN289, an EGFR-targeting antibody-maytansinoid conjugate with potent activity against non-small cell lung cancer (NSCLC) regardless of dependency on EGFR pathway.. Cancer Research. 73(8_Supplement). 5467–5467. 3 indexed citations

10.

Setiady, Yulius Y., Peter U. Park, Jose F. Ponte, et al.. (2013). Abstract 5463: Development of a novel antibody-maytansinoid conjugate, IMGN289, for the treatment of EGFR-expressing solid tumors.. Cancer Research. 73(8_Supplement). 5463–5463. 2 indexed citations

11.

Deckert, Jutta, Michele Mayo, Yong Weon Yi, et al.. (2011). Abstract 4565: IMGN529: A therapeutic maytansinoid conjugate of an anti-CD37 antibody with multiple mechanisms of action for B-cell lymphoma and leukemia. Cancer Research. 71(8_Supplement). 4565–4565. 4 indexed citations

12.

Setiady, Yulius Y., Anna Skaletskaya, Jennifer A. Coccia, et al.. (2011). Abstract 4564: huHER3-8, a novel humanized anti-HER3 antibody that inhibits exogeneous ligand-independent proliferation of tumor cells. Cancer Research. 71(8_Supplement). 4564–4564. 4 indexed citations

13.

Park, Peter U., Yong Weon Yi, Min Li, et al.. (2011). Abstract 2830: Antibody and linker selection for the anti-CD37 antibody-maytansinoid conjugate IMGN529 for the treatment of B-cell malignancies. Cancer Research. 71(8_Supplement). 2830–2830. 4 indexed citations

14.

Park, Peter U., Véronique Blanc, Jutta Deckert, et al.. (2008). SAR650984: A Potent Anti-CD38 Therapeutic Antibody with Three Mechanisms of Action (Apoptosis, ADCC, CDC) for Hematological Malignancies. Blood. 112(11). 2756–2756. 3 indexed citations

15.

Bladt, Friedhelm, Patricia Vrignaud, Marielle Chiron, et al.. (2006). Pre-clinical evaluation of the anti-tumor activity of the IGF1R - specific anitbody AVE1642. 66. 289–290. 4 indexed citations

16.

Mihara, Motohiro, Susan Erster, Alexander Zaika, et al.. (2003). p53 Has a Direct Apoptogenic Role at the Mitochondria. Molecular Cell. 11(3). 577–590. 1403 indexed citations breakdown →

17.

Maloney, Erin K., Lisa M. Garrett, Katherine M. Connors, et al.. (2003). An anti-insulin-like growth factor I receptor antibody that is a potent inhibitor of cancer cell proliferation.. PubMed. 63(16). 5073–83. 260 indexed citations

18.

Chittenden, Thomas. (2002). BH3 domains: intracellular death-ligands critical for initiating apoptosis. Cancer Cell. 2(3). 165–166. 57 indexed citations

19.

Skaletskaya, Anna, Laura M. Bartle, Thomas Chittenden, et al.. (2001). A cytomegalovirus-encoded inhibitor of apoptosis that suppresses caspase-8 activation. Proceedings of the National Academy of Sciences. 98(14). 7829–7834. 351 indexed citations

20.

Goldmacher, Victor S., Laura M. Bartle, Anna Skaletskaya, et al.. (1999). A cytomegalovirus-encoded mitochondria-localized inhibitor of apoptosis structurally unrelated to Bcl-2. Proceedings of the National Academy of Sciences. 96(22). 12536–12541. 354 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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