David Roodman

4.3k total citations · 1 hit paper
33 papers, 2.3k citations indexed

About

David Roodman is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, David Roodman has authored 33 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 18 papers in Hematology and 17 papers in Oncology. Recurrent topics in David Roodman's work include Multiple Myeloma Research and Treatments (18 papers), Bone health and treatments (9 papers) and Bone Metabolism and Diseases (6 papers). David Roodman is often cited by papers focused on Multiple Myeloma Research and Treatments (18 papers), Bone health and treatments (9 papers) and Bone Metabolism and Diseases (6 papers). David Roodman collaborates with scholars based in United States, Germany and Switzerland. David Roodman's co-authors include Gregory R. Mundy, Brendan F. Boyce, Toshiyuki Yoneda, D. E. Hughes, Akira Sasaki, Kenneth R. Wright, Johannes Pfeilschifter, Andrew Bird, Chantal Chenu and Robert A. Kyle and has published in prestigious journals such as Journal of Clinical Oncology, The Journal of Cell Biology and Blood.

In The Last Decade

David Roodman

32 papers receiving 2.2k citations

Hit Papers

Bisphosphonates promote apoptosis in murine osteoclasts i... 1995 2026 2005 2015 1995 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Roodman United States 13 1.4k 1.0k 569 430 278 33 2.3k
Samantha Pozzi Italy 27 1.1k 0.8× 853 0.8× 129 0.2× 536 1.2× 120 0.4× 91 2.3k
C M Shipman United Kingdom 14 1.6k 1.1× 774 0.8× 344 0.6× 481 1.1× 533 1.9× 31 2.0k
Bertha Frisch Israel 26 472 0.3× 529 0.5× 388 0.7× 841 2.0× 105 0.4× 72 2.2k
Marc Baud’huin France 26 706 0.5× 1.2k 1.1× 171 0.3× 205 0.5× 77 0.3× 50 2.1k
Jan Elliott Australia 15 1.4k 1.0× 1.8k 1.8× 337 0.6× 109 0.3× 121 0.4× 18 2.4k
Vincent Castronovo Belgium 21 1.1k 0.8× 930 0.9× 419 0.7× 79 0.2× 418 1.5× 28 2.3k
Mark Tometsko United States 13 2.6k 1.8× 3.0k 3.0× 560 1.0× 131 0.3× 222 0.8× 18 4.3k
Julie C. Frith United Kingdom 13 2.3k 1.6× 928 0.9× 1.1k 2.0× 70 0.2× 659 2.4× 17 2.9k
Rowena D. Devlin United States 17 696 0.5× 830 0.8× 251 0.4× 261 0.6× 50 0.2× 20 1.6k
Magne Børset Norway 38 1.6k 1.1× 2.3k 2.2× 106 0.2× 1.9k 4.4× 155 0.6× 107 4.3k

Countries citing papers authored by David Roodman

Since Specialization
Citations

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

Fields of papers citing papers by David Roodman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Roodman

This figure shows the co-authorship network connecting the top 25 collaborators of David Roodman. A scholar is included among the top collaborators of David Roodman 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 David Roodman. David Roodman 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.
Meo, Francesco Di, Rujin Cheng, Christina Y. Yu, et al.. (2023). A target discovery pipeline identified ILT3 as a target for immunotherapy of multiple myeloma. Cell Reports Medicine. 4(7). 101110–101110. 17 indexed citations
2.
Meo, Francesco Di, Christina Y. Yu, Rujin Cheng, et al.. (2022). A Novel Bi-Specific T-Cell Engager Targeting ILT3 Is Potently Effective in Multiple Myeloma. Blood. 140(Supplement 1). 671–672. 2 indexed citations
3.
Meo, Francesco Di, Rujin Cheng, Christina Y. Yu, et al.. (2022). A Target Discovery Pipeline Identified ILT3 as a Target for Immunotherapy of Multiple Myeloma. SSRN Electronic Journal. 5 indexed citations
5.
Kovács, János, Chong Li, Qin Yang, et al.. (2011). Autophagy promotes T-cell survival through degradation of proteins of the cell death machinery. Cell Death and Differentiation. 19(1). 144–152. 182 indexed citations
6.
7.
Teramachi, Jumpei, Jolene J. Windle, David Roodman, & Noriyoshi Kurihara. (2010). The ZZ Domain of Sequestosome-1/p62 Plays An Important Role In Stromal Cell Support of Myeloma Cell Growth and Osteoclast Formation. Blood. 116(21). 128–128. 3 indexed citations
8.
Hussein, M. A., Frank D. Vrionis, Robert D. Allison, et al.. (2008). The role of vertebral augmentation in multiple myeloma: International Myeloma Working Group Consensus Statement. Leukemia. 22(8). 1479–1484. 46 indexed citations
9.
Hiruma, Yuko, Noriyoshi Kurihara, Diane F. Jelinek, & David Roodman. (2008). Increased Signaling through p62 in the Marrow Microenvironment Increases Myeloma Cell Growth and Osteoclast Formation. Blood. 112(11). 642–642. 1 indexed citations
10.
Grant, Steven, Daniel M. Sullivan, David Roodman, et al.. (2008). Phase I Trial of Bortezomib (NSC 681239) and Flavopiridol (NSC 649890) in Patients with Recurrent or Refractory Indolent B-Cell Neoplasms.. Blood. 112(11). 1573–1573. 4 indexed citations
11.
Kyle, Robert A., Gary C. Yee, Mark R. Somerfield, et al.. (2007). American Society of Clinical Oncology 2007 Clinical Practice Guideline Update on the Role of Bisphosphonates in Multiple Myeloma. Journal of Clinical Oncology. 25(17). 2464–2472. 295 indexed citations
12.
Roodman, David. (2007). E06-01: Pathogenesis of lung cancer bone metastasis. Journal of Thoracic Oncology. 2(8). S231–S231. 2 indexed citations
15.
Masih‐Khan, Esther, Suzanne Trudel, Carla Heise, et al.. (2006). MIP-1α (CCL3) is a downstream target of FGFR3 and RAS-MAPK signaling in multiple myeloma. Blood. 108(10). 3465–3471. 54 indexed citations
16.
Kurihara, Noriyoshi, Yuko Hiruma, Jolene J. Windle, et al.. (2006). Targeting p62 in Marrow Stromal Cells Is Effective at Inhibiting Myeloma Cell Growth.. Blood. 108(11). 513–513. 2 indexed citations
17.
Kurihara, Noriyoshi, Tadashi Honjo, Judy M. Anderson, et al.. (2005). Thalidomide derivative CC-4047 inhibits osteoclast formation by down-regulation of PU.1. Blood. 107(8). 3098–3105. 114 indexed citations
18.
Mbalaviele, Gabriel, Riko Nishimura, Maria Niewolna, et al.. (1998). Cadherin-6 Mediates the Heterotypic Interactions between the Hemopoietic Osteoclast Cell Lineage and Stromal Cells in a Murine Model of Osteoclast Differentiation. The Journal of Cell Biology. 141(6). 1467–1476. 40 indexed citations
19.
Dallas, Mark, et al.. (1995). Use of an in vivo model to determine the effects of interleukin-1 on cells at different stages in the osteoclast lineage. Journal of Bone and Mineral Research. 10(2). 295–301. 41 indexed citations
20.
Hughes, D. E., Kenneth R. Wright, Akira Sasaki, et al.. (1995). Bisphosphonates promote apoptosis in murine osteoclasts in vitro and in vivo. Journal of Bone and Mineral Research. 10(10). 1478–1487. 846 indexed citations breakdown →

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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