Markus A. Seeliger

6.0k citations
74 papers · 4.5k indexed · 2 hit papers · h-index 33

Impact in

  • Hematology top 1%
    • Chronic Myeloid Leukemia Treatments
  • Genetics top 2%
    • Chronic Lymphocytic Leukemia Research

Papers in

    • Chronic Myeloid Leukemia Treatments 16
    • Chronic Lymphocytic Leukemia Research 7

Markus A. Seeliger

74 papers receiving 4.4k citations

Hit Papers

Structural mechanism of a drug-binding process involving a large conformational change of the protein target 2023 · 59 citations
592011202620162021100200300400

Peers

Markus A. Seeliger
Comparison fields: 5 of 128
  • Hematology 760
  • Genetics 513
  • Molecular Biology 3.1k
  • Computational Theory and Mathematics 650
  • Cell Biology 654
Replace Patrick P. Zarrinkar with:
Patrick P. Zarrinkar United States
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Markus A. Seeliger relative to Patrick P. Zarrinkar United States Patrick P. Zarrinkar's profile →
Citations per field
00.5×1.5×2.5×
Patrick P. Zarrinkar · 1×
Citations per year

Countries citing papers authored by Markus A. Seeliger

Since Specialization
Citations

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

Fields of papers citing papers by Markus A. Seeliger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus A. Seeliger. 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 Markus A. Seeliger. The network helps show where Markus A. Seeliger may publish in the future.

Co-authors

The 25 scholars most cited alongside Markus A. Seeliger, 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 Markus A. Seeliger Line = papers co-authored together Markus A. Seeliger links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20246
3 20248
4 20241
5 20247
6 20233
7 202236
8 202140
9 202018
10 201931
11 201835
12 20167
13 201614
14 201562
15 201358
16 2009127
17 200945
18 2008216
19 2008103
20 2007181

About Markus A. Seeliger

Markus A. Seeliger is a scholar working on Hematology, Genetics, Molecular Biology, Rheumatology and Cell Biology, having authored 74 papers that have together received 4.5k indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (16 papers), Protein Kinase Regulation and GTPase Signaling (14 papers), Monoclonal and Polyclonal Antibodies Research (12 papers), Protein Structure and Dynamics (11 papers), Eosinophilic Disorders and Syndromes (10 papers), Computational Drug Discovery Methods (8 papers), Chronic Lymphocytic Leukemia Research (7 papers) and PI3K/AKT/mTOR signaling in cancer (6 papers). The work is most often cited by research in Hematology (760 citations), Genetics (513 citations), Molecular Biology (3.1k citations), Computational Theory and Mathematics (650 citations) and Cell Biology (654 citations). Markus A. Seeliger has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include John Kuriyan, Yibing Shan, David E. Shaw, Michael P. Eastwood, Ron O. Dror, Eric T. Kim, Nathanael S. Gray, Mohammad Azam, George Q. Daley and Michael Tong. Their work appears in journals such as ACS Chemical Biology, Journal of Molecular Biology, Nature Communications, Journal of Biological Chemistry and Biochemistry.

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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