Michael Timm

3.8k citations
78 papers · 2.5k · h-index 28

Impact in

Papers in

    • Multiple Myeloma Research and Treatments 31
    • Acute Myeloid Leukemia Research 6
    • Protein Degradation and Inhibitors 6

Michael Timm

74 papers receiving 2.5k citations

Peers

Michael Timm
Comparison fields: 5 of 135
  • Hematology 754
  • Health, Toxicology and Mutagenesis 404
  • Process Chemistry and Technology 81
  • Genetics 222
  • Oncology 478
Replace Pengda Liu with:
Pengda Liu United States
Thomas T. Kawabata United States
Jeffrey P. Shaw Switzerland
Zijiang Yang China
George Weinbaum United States
Dirk Eulberg Germany
Siyi Zhang China
Denise Glaise France
Chinmay K. Mukhopadhyay India
K Konno Japan
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Citations per field
00.5×9.3×
Pengda Liu · 1×
Citations per year

Countries citing papers authored by Michael Timm

Since Specialization
Citations

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

Fields of papers citing papers by Michael Timm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Timm, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Timm Line = papers co-authored together Michael Timm links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012229
2 2006169
3 2007140
4 2013140
5 2003128
6 2004124
7 2012111
8 2006110
9 201499
10 200980
11 200678
12 201466
13 201165
14 201264
15 201954
16 201053
17 201653
18 199951
19 200851
20 200849

About Michael Timm

Michael Timm is a scholar working on Hematology, Molecular Biology, Genetics, Oncology and Pathology and Forensic Medicine, having authored 78 papers that have together received 2.5k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (31 papers), Chronic Lymphocytic Leukemia Research (10 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Protein Degradation and Inhibitors (6 papers), Acute Myeloid Leukemia Research (6 papers), Chemokine receptors and signaling (6 papers) and Lymphoma Diagnosis and Treatment (6 papers). The work is most often cited by research in Hematology (754 citations), Health, Toxicology and Mutagenesis (404 citations), Process Chemistry and Technology (81 citations), Genetics (222 citations) and Oncology (478 citations). Michael Timm has collaborated with scholars based in United States, Denmark and Germany. Frequent co-authors include Erik W. Hansen, Shaji Kumar, S. Vincent Rajkumar, Philip R. Greipp, Thomas E. Witzig, Anne Mette Madsen, Mika Frankel, Teresa K. Kimlinger, Lise Moesby and Janine Haug. Their work appears in journals such as Blood, Leukemia, British Journal of Haematology, Experimental Hematology and Cancer Research.

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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