Michael Kirberger

1.0k total citations
22 papers, 746 citations indexed

About

Michael Kirberger is a scholar working on Molecular Biology, Nutrition and Dietetics and Materials Chemistry. According to data from OpenAlex, Michael Kirberger has authored 22 papers receiving a total of 746 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Nutrition and Dietetics and 4 papers in Materials Chemistry. Recurrent topics in Michael Kirberger's work include Protein Structure and Dynamics (7 papers), Trace Elements in Health (5 papers) and Machine Learning in Bioinformatics (4 papers). Michael Kirberger is often cited by papers focused on Protein Structure and Dynamics (7 papers), Trace Elements in Health (5 papers) and Machine Learning in Bioinformatics (4 papers). Michael Kirberger collaborates with scholars based in United States, China and Israel. Michael Kirberger's co-authors include Jenny J. Yang, Wei Yang, Ning Chen, Guantao Chen, Hing C. Wong, Yubin Zhou, Hsiau‐Wei Lee, Jie Jiang, Yi Yang and Xue Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Molecular Sciences and Molecules.

In The Last Decade

Michael Kirberger

20 papers receiving 712 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Kirberger United States	14	411	115	90	78	71	22	746
Daijiro Ohmori Japan	18	455 1.1×	55 0.5×	42 0.5×	74 0.9×	55 0.8×	50	925
Kaituo Wang Denmark	13	317 0.8×	108 0.9×	43 0.5×	32 0.4×	30 0.4×	34	567
Dexin Sui United States	20	411 1.0×	270 2.3×	134 1.5×	47 0.6×	194 2.7×	32	1.1k
Jaya Bandyopadhyay India	19	373 0.9×	86 0.7×	40 0.4×	195 2.5×	91 1.3×	51	958
Thomas G. Huggins United States	11	317 0.8×	160 1.4×	53 0.6×	41 0.5×	115 1.6×	11	638
Marilene Demasi Brazil	23	918 2.2×	176 1.5×	99 1.1×	49 0.6×	121 1.7×	49	1.5k
Monika Šrámková Slovakia	18	406 1.0×	50 0.4×	96 1.1×	73 0.9×	99 1.4×	58	1.1k
Gareth S. A. Wright United Kingdom	19	421 1.0×	90 0.8×	30 0.3×	42 0.5×	93 1.3×	31	881
M. Moosmayer Switzerland	12	405 1.0×	58 0.5×	86 1.0×	37 0.5×	36 0.5×	22	679

Countries citing papers authored by Michael Kirberger

Since Specialization

Citations

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

Fields of papers citing papers by Michael Kirberger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Kirberger

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

All Works

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20 of 20 papers shown

Kirberger, Michael, Jingjuan Qiao, Shenghui Xue, et al.. (2024). Protein MRI Contrast Agents as an Effective Approach for Precision Molecular Imaging. Investigative Radiology. 59(2). 170–186. 8 indexed citations

Guo, Ying, et al.. (2023). Incorporating Virtual Problem-Based Learning in Instrumental Chemistry during the COVID-19 Pandemic. SHILAP Revista de lepidopterología. 3(12). 1733–1745. 1 indexed citations

Zhang, Hu, et al.. (2022). Irisin, an exercise-induced bioactive peptide beneficial for health promotion during aging process. Ageing Research Reviews. 80. 101680–101680. 53 indexed citations

Guo, Ying, et al.. (2022). Affective Elements of the Student Experience That Contribute to Withdrawal Rates in the General Chemistry Sequence: A Multimethod Study. Journal of Chemical Education. 99(6). 2217–2230. 10 indexed citations

Kirberger, Michael. (2022). Defining a Molecular Mechanism for Lead Toxicity via Calcium-Binding Proteins. Digital Archive @ GSU.

Xin, Yao, Cassandra Miller, Donald Hamelberg, et al.. (2020). Structural mechanism of cooperative regulation of calcium-sensing receptor-mediated cellular signaling. Current Opinion in Physiology. 17. 269–277. 10 indexed citations

Tang, Shen, et al.. (2020). Design of Calcium-Binding Proteins to Sense Calcium. Molecules. 25(9). 2148–2148. 14 indexed citations

Xu, Yiting, et al.. (2020). Structural Aspects and Prediction of Calmodulin-Binding Proteins. International Journal of Molecular Sciences. 22(1). 308–308. 55 indexed citations

Huang, Kenneth, et al.. (2016). Defining potential roles of Pb²⁺in neurotoxicity from a calciomics approach. Metallomics. 8(6). 563–578. 46 indexed citations

10.

Liu, Yang, Wen Li, Michael Kirberger, Wenzhen Liao, & Jiaoyan Ren. (2016). Design of nanomaterial based systems for novel vaccine development. Biomaterials Science. 4(5). 785–802. 53 indexed citations

11.

Zhao, Kun, et al.. (2015). Next generation sequencing technologies in cancer diagnostics and therapeutics: A mini review.. PubMed. 61(5). 91–102. 15 indexed citations

12.

Liu, Jianjun, et al.. (2014). Lunasin as a promising health-beneficial peptide.. PubMed. 18(14). 2070–5. 19 indexed citations

13.

Kirberger, Michael, Hing C. Wong, Jie Jiang, & Jenny J. Yang. (2013). Metal toxicity and opportunistic binding of Pb2+ in proteins. Journal of Inorganic Biochemistry. 125. 40–49. 65 indexed citations

14.

Zhao, Kun, Xue Wang, Hing C. Wong, et al.. (2012). Predicting Ca²⁺‐binding sites using refined carbon clusters. Proteins Structure Function and Bioinformatics. 80(12). 2666–2679. 12 indexed citations

15.

Kirberger, Michael, Xue Wang, Kun Zhao, et al.. (2010). Integration of Diverse Research Methods to Analyze and Engineer Ca2+- Binding Proteins: From Prediction to Production. Current Bioinformatics. 5(1). 68–80. 9 indexed citations

16.

Wang, Xue, Kun Zhao, Michael Kirberger, et al.. (2010). Analysis and prediction of calcium‐binding pockets from apo‐protein structures exhibiting calcium‐induced localized conformational changes. Protein Science. 19(6). 1180–1190. 26 indexed citations

17.

Wang, Xue, et al.. (2008). Towards predicting Ca²⁺‐binding sites with different coordination numbers in proteins with atomic resolution. Proteins Structure Function and Bioinformatics. 75(4). 787–798. 46 indexed citations

18.

Kirberger, Michael & Jenny J. Yang. (2008). Structural differences between Pb2+- and Ca2+-binding sites in proteins: Implications with respect to toxicity. Journal of Inorganic Biochemistry. 102(10). 1901–1909. 66 indexed citations

19.

Kirberger, Michael, et al.. (2008). Statistical analysis of structural characteristics of protein Ca2+-binding sites. JBIC Journal of Biological Inorganic Chemistry. 13(7). 1169–1181. 53 indexed citations

20.

Zhou, Yubin, et al.. (2006). Prediction of EF‐hand calcium‐binding proteins and analysis of bacterial EF‐hand proteins. Proteins Structure Function and Bioinformatics. 65(3). 643–655. 127 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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