Miriam Kull

790 citations
16 papers · 348 · h-index 8

Impact in

  • Hematology top 10%
    • Multiple Myeloma Research and Treatments
    • Protein Degradation and Inhibitors
    • Advanced biosensing and bioanalysis techniques
    • Ubiquitin and proteasome pathways
    • RNA Interference and Gene Delivery
    • RNA Research and Splicing

Papers in

    • Multiple Myeloma Research and Treatments 12
    • Acute Myeloid Leukemia Research 1
    • Protein Degradation and Inhibitors 5
    • PI3K/AKT/mTOR signaling in cancer 2
    • DNA Repair Mechanisms 1

Miriam Kull

14 papers receiving 346 citations

Peers

Miriam Kull
Comparison fields: 5 of 42
  • Hematology 129
  • Molecular Biology 265
  • Physiology 86
  • Genetics 23
  • Oncology 55
Replace Lai-Fong Poon with:
Lai-Fong Poon Singapore
OI Olopade United States
Le Xuan Truong Nguyen United States
Purvi M. Kakadia Germany
David Posocco United States
Katherine S. Bridge United Kingdom
Chandrika Gowda United States
Gabriele Migliorini United Kingdom
Scott E. Millman United States
Takao Morinaga Japan
Miriam Kull relative to Lai-Fong Poon Singapore Lai-Fong Poon's profile →
Citations per field
00.5×3.2×
Lai-Fong Poon · 1×
Citations per year

Countries citing papers authored by Miriam Kull

Since Specialization
Citations

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

Fields of papers citing papers by Miriam Kull

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2004123
2 201451
3 202249
4 201536
5 201636
6 202116
7 201811
8 20237
9 20236
10 20226
11 20164
12 20171
13 20241
14 20251
15 20180
16 20240

About Miriam Kull

Miriam Kull is a scholar working on Hematology, Molecular Biology, Genetics, Oncology and Infectious Diseases, having authored 16 papers that have together received 348 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (12 papers), Protein Degradation and Inhibitors (5 papers), Chronic Lymphocytic Leukemia Research (2 papers), PI3K/AKT/mTOR signaling in cancer (2 papers), Acute Myeloid Leukemia Research (1 paper), Inflammatory Biomarkers in Disease Prognosis (1 paper), Bone and Joint Diseases (1 paper) and DNA Repair Mechanisms (1 paper). The work is most often cited by research in Hematology (129 citations), Molecular Biology (265 citations), Physiology (86 citations), Genetics (23 citations) and Oncology (55 citations). Miriam Kull has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Uwe M. Martens, Hesham Eldaly, Milena Pantić, Stefan Zimmermann, Cornelius F. Waller, Christian Langer, Stefan Knop, Lars Bullinger, Hermann Einsele and Ralf C. Bargou. Their work appears in journals such as Blood, Journal of Clinical Oncology, Nature Communications, Acta Haematologica and HemaSphere.

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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