Holger Maier

2.1k total citations
14 papers, 554 citations indexed

About

Holger Maier is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Holger Maier has authored 14 papers receiving a total of 554 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Immunology and 4 papers in Oncology. Recurrent topics in Holger Maier's work include Biomedical Text Mining and Ontologies (3 papers), Chemokine receptors and signaling (3 papers) and RNA and protein synthesis mechanisms (3 papers). Holger Maier is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), Chemokine receptors and signaling (3 papers) and RNA and protein synthesis mechanisms (3 papers). Holger Maier collaborates with scholars based in Germany, United States and Switzerland. Holger Maier's co-authors include Bruno Luckow, Guillermo Pérez de Lema, Detlef SchloCombining Diaeresisndorff, F Mampaso, Volker Vielhauer, Elena Nieto, Thomas Werner, Peter J. Nelson, Sabine Fessele and Silvia Chilla and has published in prestigious journals such as Nucleic Acids Research, Analytical Biochemistry and Journal of the American Society of Nephrology.

In The Last Decade

Holger Maier

14 papers receiving 546 citations

Peers

Holger Maier
J D Mountz United States
Ruiqiong Wu United States
John Whoriskey United States
Greg P. Bertenshaw United States
Claude Tschopp Switzerland
Tom Sculley Australia
D Laugier France
J D Mountz United States
Holger Maier
Citations per year, relative to Holger Maier Holger Maier (= 1×) peers J D Mountz

Countries citing papers authored by Holger Maier

Since Specialization
Citations

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

Fields of papers citing papers by Holger Maier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Holger Maier

This figure shows the co-authorship network connecting the top 25 collaborators of Holger Maier. A scholar is included among the top collaborators of Holger Maier 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 Holger Maier. Holger Maier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Silva‐Buttkus, Patricia da, Helmut Fuchs, Holger Maier, et al.. (2023). Echo2Pheno: a deep-learning application to uncover echocardiographic phenotypes in conscious mice. Mammalian Genome. 34(2). 200–215. 2 indexed citations
2.
3.
Stoeger, Claudia, Holger Maier, Helmut Fuchs, et al.. (2019). Costs of Implementing Quality in Research Practice. Handbook of experimental pharmacology. 257. 399–423. 2 indexed citations
4.
Maier, Holger, Stefanie Leuchtenberger, Helmut Fuchs, Valérie Gailus‐Durner, & Martin Hrabě de Angelis. (2017). Big data in large-scale systemic mouse phenotyping. Current Opinion in Systems Biology. 4. 97–104. 1 indexed citations
6.
Morgan, Hugh W., Tim Beck, Andrew Blake, et al.. (2009). EuroPhenome: a repository for high-throughput mouse phenotyping data. Nucleic Acids Research. 38(suppl_1). D577–D585. 51 indexed citations
7.
Maier, Holger, et al.. (2008). MausDB: An open source application for phenotype data and mouse colony management in large-scale mouse phenotyping projects. BMC Bioinformatics. 9(1). 169–169. 8 indexed citations
8.
Maier, Holger, et al.. (2005). LitMiner and WikiGene: identifying problem-related key players of gene regulation using publication abstracts. Nucleic Acids Research. 33(Web Server). W779–W782. 38 indexed citations
9.
Lema, Guillermo Pérez de, Holger Maier, Tobias Franz, et al.. (2005). Chemokine Receptor Ccr2 Deficiency Reduces Renal Disease and Prolongs Survival in MRL/lpr Lupus-Prone Mice. Journal of the American Society of Nephrology. 16(12). 3592–3601. 86 indexed citations
10.
Luckow, Bruno, Joanne Joergensen, Silvia Chilla, et al.. (2004). Reduced intragraft mRNA expression of matrix metalloproteinases Mmp3, Mmp12, Mmp13 and Adam8, and diminished transplant arteriosclerosis in Ccr5‐deficient mice. European Journal of Immunology. 34(9). 2568–2578. 37 indexed citations
11.
Fessele, Sabine, et al.. (2002). Regulatory context is a crucial part of gene function. Trends in Genetics. 18(2). 60–63. 79 indexed citations
12.
Lema, Guillermo Pérez de, Holger Maier, Elena Nieto, et al.. (2001). Chemokine Expression Precedes Inflammatory Cell Infiltration and Chemokine Receptor and Cytokine Expression during the Initiation of Murine Lupus Nephritis. Journal of the American Society of Nephrology. 12(7). 1369–1382. 206 indexed citations
13.
Luckow, Bruno, Holger Maier, Silvia Chilla, & Guillermo Pérez de Lema. (2000). The mCK-5 Multiprobe RNase Protection Assay Kit Can Yield Erroneous Results for the Murine Chemokines IP-10 and MCP-1. Analytical Biochemistry. 286(2). 193–197. 9 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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