Matthias Mack

37.5k citations
259 papers · 25.3k indexed · 13 hit papers · h-index 84

Matthias Mack

257 papers receiving 25.0k citations

Hit Papers

Human neutralizing an...18320072026201320192505007501000

Peers

Matthias Mack
Comparison fields: 5 of 168
  • Immunology 13.3k
  • Neurology 3.2k
  • Oncology 4.7k
  • Virology 793
  • Immunology and Allergy 992
Replace Hans‐Dieter Volk with:
Hans‐Dieter Volk Germany
Frédéric Geissmann France
Thomas A. Wynn United States
John D. Lambris United States
David A. Hafler United States
Yoichiro Iwakura Japan
Gwendalyn J. Randolph United States
Israel Charo United States
Steven L. Kunkel United States
Massimo Locati Italy
Matthias Mack relative to Hans‐Dieter Volk Germany Hans‐Dieter Volk's profile →
Citations per field
00.5×1.5×1.8×
Hans‐Dieter Volk · 1×
Citations per year

Countries citing papers authored by Matthias Mack

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Mack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20244
3 202314
4 202283
5 202177
6
Human neutralizing antibodies against SARS-CoV-2 require intact Fc effector functions for optimal therapeutic protectionbreakdown →
2021183
7 20211
8 20203
9 201958
10 201843
11 2017305
12 2014109
13 201392
14 201346
15 2011159
16
Different Tumor Microenvironments Contain Functionally Distinct Subsets of Macrophages Derived from Ly6C(high) Monocytesbreakdown →
2010964
17 2008298
18 20026
19 200117
20 2001226

About Matthias Mack

Matthias Mack is a scholar working on Immunology, Immunology and Allergy and Neurology, having authored 259 papers that have together received 25.3k indexed citations. Recurring topics across this work include Chemokine receptors and signaling (57 papers), Immune Response and Inflammation (52 papers), Immune cells in cancer (49 papers), Immune Cell Function and Interaction (43 papers), T-cell and B-cell Immunology (42 papers), Immunotherapy and Immune Responses (31 papers), Neuroinflammation and Neurodegeneration Mechanisms (23 papers) and Monoclonal and Polyclonal Antibodies Research (14 papers). The work is most often cited by research in Immunology (13.3k citations), Neurology (3.2k citations) and Oncology (4.7k citations). Matthias Mack has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Detlef Schlöndorff, Stanley Perlman, David K. Meyerholz, Rudragouda Channappanavar, M. Stangassinger, Josef Cihak, Anthony R. Fehr, Hilke Brühl, Steffen Jung and Amanda E. I. Proudfoot. Their work appears in journals such as The Journal of Immunology, Journal of Clinical Investigation, The Journal of Experimental Medicine, European Journal of Immunology and Nature Communications.

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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