Heiko A. Hofmann

568 total citations
9 papers, 351 citations indexed

About

Heiko A. Hofmann is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Heiko A. Hofmann has authored 9 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 3 papers in Physiology. Recurrent topics in Heiko A. Hofmann's work include Pain Mechanisms and Treatments (3 papers), Neuroscience and Neuropharmacology Research (3 papers) and S100 Proteins and Annexins (3 papers). Heiko A. Hofmann is often cited by papers focused on Pain Mechanisms and Treatments (3 papers), Neuroscience and Neuropharmacology Research (3 papers) and S100 Proteins and Annexins (3 papers). Heiko A. Hofmann collaborates with scholars based in Germany. Heiko A. Hofmann's co-authors include Angela Siegling, Jean De Vry, Frank Mauler, Harutyun Melkonyan, Martin Klempt, Clemens Sorg, P. Spreyer, Volker Hinz, Ervin Horváth and Joachim Schuhmacher and has published in prestigious journals such as Journal of Biological Chemistry, Blood and European Journal of Neuroscience.

In The Last Decade

Heiko A. Hofmann

9 papers receiving 337 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Heiko A. Hofmann Germany 9 135 118 104 100 65 9 351
E. Postler Germany 7 128 0.9× 35 0.3× 32 0.3× 53 0.5× 58 0.9× 11 285
Lisa Flint United States 8 199 1.5× 99 0.8× 59 0.6× 96 1.0× 22 0.3× 9 514
A. Garcı́a-Merino Spain 11 82 0.6× 20 0.2× 131 1.3× 114 1.1× 105 1.6× 18 480
Lucas Vicuña Chile 7 129 1.0× 95 0.8× 21 0.2× 66 0.7× 106 1.6× 11 328
Michela Zattoni Switzerland 7 108 0.8× 86 0.7× 23 0.2× 151 1.5× 49 0.8× 7 467
Anthony Fernández-Castañeda United States 7 238 1.8× 36 0.3× 18 0.2× 79 0.8× 87 1.3× 8 495
Yasutomi Kuroki Japan 8 158 1.2× 42 0.4× 11 0.1× 90 0.9× 20 0.3× 13 365
Fai Tsang Singapore 10 149 1.1× 107 0.9× 14 0.1× 87 0.9× 51 0.8× 13 414
Adriana D. Benavides United States 5 196 1.5× 123 1.0× 41 0.4× 32 0.3× 53 0.8× 5 387
Chunmei Yang United States 11 300 2.2× 117 1.0× 18 0.2× 39 0.4× 35 0.5× 15 501

Countries citing papers authored by Heiko A. Hofmann

Since Specialization
Citations

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

Fields of papers citing papers by Heiko A. Hofmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heiko A. Hofmann

This figure shows the co-authorship network connecting the top 25 collaborators of Heiko A. Hofmann. A scholar is included among the top collaborators of Heiko A. Hofmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Heiko A. Hofmann. Heiko A. Hofmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
2.
Hofmann, Heiko A., et al.. (2003). Pharmacological sensitivity and gene expression analysis of the tibial nerve injury model of neuropathic pain. European Journal of Pharmacology. 470(1-2). 17–25. 61 indexed citations
3.
Kerkhoff, Claus, Heiko A. Hofmann, Josef Vormoor, et al.. (2002). Binding of Two Nuclear Complexes to a Novel Regulatory Element within the Human S100A9 Promoter Drives the S100A9 Gene Expression. Journal of Biological Chemistry. 277(44). 41879–41887. 29 indexed citations
4.
Hofmann, Heiko A., et al.. (2001). Metabotropic glutamate mGlu1 receptor mRNA expression in dorsal root ganglia of rats after peripheral nerve injury. European Journal of Pharmacology. 429(1-3). 135–138. 8 indexed citations
5.
Siegling, Angela, et al.. (2001). Cannabinoid CB1 receptor upregulation in a rat model of chronic neuropathic pain. European Journal of Pharmacology. 415(1). R5–R7. 88 indexed citations
6.
Klempt, Martin, Harutyun Melkonyan, Heiko A. Hofmann, & Clemens Sorg. (1999). Identification of epithelial and myeloid-specific DNA elements regulating MRP14 gene transcription. Journal of Cellular Biochemistry. 73(1). 49–55. 10 indexed citations
7.
Santoso, Sentot, Heiko A. Hofmann, Ulrich J. Sachs, et al.. (1999). A Point Mutation Thr799Met on the 2 Integrin Leads to the Formation of New Human Platelet Alloantigen Sita and Affects Collagen-Induced Aggregation. Blood. 94(12). 4103–4111. 43 indexed citations
8.
Klempt, Martin, Harutyun Melkonyan, Heiko A. Hofmann, Ines Eue, & Clemens Sorg. (1998). The Transcription Factors c-myb and C/EBPα Regulate the Monocytic/Myeloic Gene MRP14. Immunobiology. 199(1). 148–151. 25 indexed citations
9.
Melkonyan, Harutyun, Heiko A. Hofmann, Wolfgang Nacken, Clemens Sorg, & Martin Klempt. (1998). The Gene Encoding the Myeloid-related Protein 14 (MRP14), a Calcium-binding Protein Expressed in Granulocytes and Monocytes, Contains a Potent Enhancer Element in the First Intron. Journal of Biological Chemistry. 273(41). 27026–27032. 25 indexed citations

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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