Tom Daniel

1.6k total citations · 1 hit paper
16 papers, 1.2k citations indexed

About

Tom Daniel is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Tom Daniel has authored 16 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 12 papers in Hematology and 3 papers in Genetics. Recurrent topics in Tom Daniel's work include Multiple Myeloma Research and Treatments (9 papers), Protein Degradation and Inhibitors (9 papers) and Ubiquitin and proteasome pathways (6 papers). Tom Daniel is often cited by papers focused on Multiple Myeloma Research and Treatments (9 papers), Protein Degradation and Inhibitors (9 papers) and Ubiquitin and proteasome pathways (6 papers). Tom Daniel collaborates with scholars based in Switzerland, Canada and United States. Tom Daniel's co-authors include Rajesh Chopra, Anita K. Gandhi, Derek Mendy, Antonia Lopez‐Girona, Svetlana Gaidarova, Peter Schäfer, Jian Kang, Mahan Abbasian, Emily Rychak and Pilgrim J. Jackson and has published in prestigious journals such as Blood, Molecular and Cellular Biology and Biochemical and Biophysical Research Communications.

In The Last Decade

Tom Daniel

16 papers receiving 1.2k citations

Hit Papers

Cereblon is a direct protein target for immunomodulatory ... 2012 2026 2016 2021 2012 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Daniel Switzerland 9 937 724 363 147 128 16 1.2k
Sabrina Manni Italy 19 626 0.7× 217 0.3× 197 0.5× 177 1.2× 103 0.8× 43 907
Huajun Yan United States 11 872 0.9× 208 0.3× 188 0.5× 53 0.4× 112 0.9× 13 1.0k
Susan Jones‐Bolin United States 9 424 0.5× 339 0.5× 184 0.5× 185 1.3× 52 0.4× 14 769
Nicole E. Carlson United States 9 816 0.9× 129 0.2× 319 0.9× 96 0.7× 119 0.9× 10 1.0k
Lolita Banerji United Kingdom 13 753 0.8× 264 0.4× 286 0.8× 211 1.4× 125 1.0× 15 1.1k
Lars Anders United States 7 1.1k 1.1× 129 0.2× 497 1.4× 88 0.6× 94 0.7× 12 1.5k
Jyh-Rong Chao United States 8 823 0.9× 98 0.1× 367 1.0× 179 1.2× 99 0.8× 9 1.2k
Victoria Weston United Kingdom 13 671 0.7× 101 0.1× 337 0.9× 175 1.2× 116 0.9× 19 958
Niranjan Yanamandra United States 18 441 0.5× 155 0.2× 265 0.7× 76 0.5× 51 0.4× 28 823
Francesca Pellicano United Kingdom 17 458 0.5× 570 0.8× 157 0.4× 352 2.4× 40 0.3× 27 992

Countries citing papers authored by Tom Daniel

Since Specialization
Citations

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

Fields of papers citing papers by Tom Daniel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Daniel

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

All Works

16 of 16 papers shown
1.
Bjorklund, Chad C., Ling Lu, Jian Kang, et al.. (2015). Rate of CRL4CRBN substrate Ikaros and Aiolos degradation underlies differential activity of lenalidomide and pomalidomide in multiple myeloma cells by regulation of c-Myc and IRF4. Blood Cancer Journal. 5(10). e354–e354. 154 indexed citations
2.
Amatangelo, Michael, Paola Neri, María Ortiz, et al.. (2015). Resistance to Lenalidomide in Multiple Myeloma Is Associated with a Switch in Gene Expression Profile. Blood. 126(23). 1789–1789. 4 indexed citations
3.
Carrancio, Soraya, Jennifer A. Markovics, Piu Wong, et al.. (2014). An activin receptor IIA ligand trap promotes erythropoiesis resulting in a rapid induction of red blood cells and haemoglobin. British Journal of Haematology. 165(6). 870–882. 91 indexed citations
4.
Hagner, Patrick R., Maria Wang, Suzana S. Couto, et al.. (2014). CC-122 Has Potent Anti-Lymphoma Activity through Destruction of the Aiolos and Ikaros Transcription Factors and Induction of Interferon Response Pathways. Blood. 124(21). 3035–3035. 11 indexed citations
5.
Gandhi, Anita K., Derek Mendy, Michelle F. Waldman, et al.. (2013). Measuring cereblon as a biomarker of response or resistance to lenalidomide and pomalidomide requires use of standardized reagents and understanding of gene complexity. British Journal of Haematology. 164(2). 233–244. 71 indexed citations
6.
Heise, Carla, et al.. (2013). Sotatercept, An Activin Receptor-2a Ligand Trap, Modulates Hepcidin Levels In Primary Human Hepatocytes. Blood. 122(21). 3441–3441. 1 indexed citations
7.
Lopez‐Girona, Antonia, Derek Mendy, Takumi Ito, et al.. (2012). Cereblon is a direct protein target for immunomodulatory and antiproliferative activities of lenalidomide and pomalidomide. Leukemia. 26(11). 2326–2335. 606 indexed citations breakdown →
9.
Dussiot, Michaël, Thiago Trovati Maciel, Aurélie Fricot, et al.. (2012). Modulation of Activin Signaling by RAP-011 (ActRIIA-IgG1) Improve Anemia, Increases Hemoglobin Levels and Corrects Ineffective Erythropoiesis in β-Thalassemia. Blood. 120(21). 247–247. 1 indexed citations
10.
Gandhi, Anita K., Hervé Avet‐Loiseau, Michelle F. Waldman, et al.. (2012). Detection and Quantification of Cereblon Protein and mRNA in Multiple Myeloma Cell Lines and Primary CD138+multiple Myeloma Cells. Blood. 120(21). 4043–4043. 1 indexed citations
11.
Schäfer, Peter, Emily Rychak, Derek Mendy, et al.. (2012). Targeting Cereblon with the High Affinity Immunomodulatory Compound CC-220: A Novel Therapeutic Agent for B Cell Dyscrasias. Blood. 120(21). 1055–1055. 1 indexed citations
12.
Lopez‐Girona, Antonia, Daniel Heintel, Derek Mendy, et al.. (2011). Lenalidomide downregulates the cell survival factor, interferon regulatory factor‐4, providing a potential mechanistic link for predicting response. British Journal of Haematology. 154(3). 325–336. 137 indexed citations
13.
Lopez‐Girona, Antonia, Derek Mendy, Karen Miller, et al.. (2011). Direct Binding with Cereblon Mediates the Antiproliferative and Immunomodulatory Action of Lenalidomide and Pomalidomide. Blood. 118(21). 738–738. 4 indexed citations
14.
Gaidarova, Svetlana, Derek Mendy, Carla Heise, et al.. (2010). Lenalidomide Induces Capping of CD20 and Cytoskeleton Proteins to Enhance Rituximab Immune Recognition of Malignant B-Cells. Blood. 116(21). 2845–2845. 9 indexed citations
15.
Roberts, Richard, et al.. (2004). Reverse endocytosis of transmembrane ephrin-B ligands via a clathrin-mediated pathway. Biochemical and Biophysical Research Communications. 323(1). 17–23. 34 indexed citations
16.
Becker, Elena, Uyen Huynh‐Do, Sacha J. Holland, et al.. (2000). Nck-Interacting Ste20 Kinase Couples Eph Receptors to c-Jun N-Terminal Kinase and Integrin Activation. Molecular and Cellular Biology. 20(5). 1537–1545. 115 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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