M Lemm

901 citations
25 papers · 730 · h-index 13

Impact in

Papers in

    • S100 Proteins and Annexins 4
    • RNA Interference and Gene Delivery 4
    • Cancer-related gene regulation 3
    • Cancer Cells and Metastasis 3
    • Peptidase Inhibition and Analysis 2

M Lemm

25 papers receiving 720 citations

Peers

M Lemm
Comparison fields: 5 of 82
  • Cancer Research 124
  • Oncology 219
  • Molecular Biology 437
  • Biotechnology 50
  • Genetics 59
Replace Kylie A. Hotchkiss with:
Kylie A. Hotchkiss United States
Mustafa Vali United States
Takahito Nakahara Japan
Natalie Grinshtein Canada
Shama Kajiji United States
Saiful Effendi Syafruddin Malaysia
Liqiang Pan China
Françoise Perron‐Sierra France
Yuan Rong China
Mira Stadler Austria
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Citations per field
00.5×2.6×
Kylie A. Hotchkiss · 1×
Citations per year

Countries citing papers authored by M Lemm

Since Specialization
Citations

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

Fields of papers citing papers by M Lemm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011171
2 201176
3 200968
4 200860
5 201158
6 201554
7 200150
8 199733
9 201226
10 200923
11 200923
12 201222
13 199716
14 199212
15 201411
16
Carboplatin-liposomes as activators of hematopoiesis.
19935
17 20125
18
Early macrophage and cytokine response during the growth of immunogenic and non-immunogenic murine tumors.
20024
19
Determination of antineoplastic activity and toxicity of tumor necrosis factor (TNF) in animal experiments. Correlation to clinical findings.
19903
20 19943

About M Lemm

M Lemm is a scholar working on Molecular Biology, Oncology, Immunology, Biomaterials and Biotechnology, having authored 25 papers that have together received 730 indexed citations. Recurring topics across this work include Nanoparticle-Based Drug Delivery (4 papers), S100 Proteins and Annexins (4 papers), RNA Interference and Gene Delivery (4 papers), Cancer Research and Treatments (3 papers), Cancer Cells and Metastasis (3 papers), Cancer-related gene regulation (3 papers), Glioma Diagnosis and Treatment (3 papers) and Peptidase Inhibition and Analysis (2 papers). The work is most often cited by research in Cancer Research (124 citations), Oncology (219 citations), Molecular Biology (437 citations), Biotechnology (50 citations) and Genetics (59 citations). M Lemm has collaborated with scholars based in Germany, United States and Cuba. Frequent co-authors include Iduna Fichtner, Ulrike Stein, Wolfgang Walther, Ulrike Sack, Dennis Kobelt, Robert H. Shoemaker, Dominic A. Scudiero, P. M. Schlag, Peter M. Schlag and Enrique Montero. Their work appears in journals such as Gene Therapy, Journal of Pharmaceutical Sciences, Molecular Oncology, JNCI Journal of the National Cancer Institute and Neoplasia.

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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