Mihaela Žigman

1.2k total citations · 1 hit paper
31 papers, 811 citations indexed

About

Mihaela Žigman is a scholar working on Biophysics, Molecular Biology and Analytical Chemistry. According to data from OpenAlex, Mihaela Žigman has authored 31 papers receiving a total of 811 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Biophysics, 16 papers in Molecular Biology and 11 papers in Analytical Chemistry. Recurrent topics in Mihaela Žigman's work include Spectroscopy Techniques in Biomedical and Chemical Research (20 papers), Spectroscopy and Chemometric Analyses (11 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Mihaela Žigman is often cited by papers focused on Spectroscopy Techniques in Biomedical and Chemical Research (20 papers), Spectroscopy and Chemometric Analyses (11 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Mihaela Žigman collaborates with scholars based in Germany, Saudi Arabia and Austria. Mihaela Žigman's co-authors include Juergen A. Knoblich, Alexander Schleiffer, Frederik Wirtz‐Peitz, Daniela Berdnik, Marinus Huber, Kosmas V. Kepesidis, Ferenc Krausz, Michael K. Trubetskov, Cecilia B. Moens and Le A. Trinh and has published in prestigious journals such as Nature, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Mihaela Žigman

28 papers receiving 796 citations

Hit Papers

Field-resolved infrared spectroscopy of biological systems 2020 2026 2022 2024 2020 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mihaela Žigman Germany 14 412 244 148 145 94 31 811
Srinjan Basu United Kingdom 13 628 1.5× 110 0.5× 55 0.4× 584 4.0× 40 0.4× 21 1.2k
Eugene Novikov France 13 413 1.0× 96 0.4× 73 0.5× 117 0.8× 25 0.3× 55 678
Leonel Malacrida Uruguay 21 725 1.8× 117 0.5× 109 0.7× 481 3.3× 16 0.2× 57 1.4k
Kimara L. Targoff United States 13 488 1.2× 114 0.5× 33 0.2× 359 2.5× 46 0.5× 18 937
Gil G. Westmeyer Germany 23 476 1.2× 110 0.5× 51 0.3× 128 0.9× 48 0.5× 48 1.6k
Alessandro Ustione United States 22 771 1.9× 108 0.4× 30 0.2× 311 2.1× 48 0.5× 45 1.5k
David Ackerman United States 11 369 0.9× 87 0.4× 107 0.7× 76 0.5× 17 0.2× 13 667
Luca Lanzanò Italy 25 549 1.3× 117 0.5× 219 1.5× 771 5.3× 130 1.4× 92 1.6k
Monica X. Li Canada 27 1.3k 3.3× 90 0.4× 283 1.9× 72 0.5× 64 0.7× 43 2.3k
Montserrat Samsó United States 24 1.5k 3.5× 338 1.4× 86 0.6× 54 0.4× 28 0.3× 56 1.8k

Countries citing papers authored by Mihaela Žigman

Since Specialization
Citations

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

Fields of papers citing papers by Mihaela Žigman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mihaela Žigman

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

All Works

20 of 20 papers shown
1.
Kepesidis, Kosmas V., Frank Fleischmann, Ina Koch, et al.. (2025). Assessing lung cancer progression and survival with infrared spectroscopy of blood serum. BMC Medicine. 23(1). 101–101.
2.
Fleischmann, Frank, et al.. (2024). Probing Blood Plasma Protein Glycosylation with Infrared Spectroscopy. Analytical Chemistry. 9 indexed citations
3.
Huber, Marinus, Michael K. Trubetskov, Wolfgang Schweinberger, et al.. (2024). Standardized Electric-Field-Resolved Molecular Fingerprinting. Analytical Chemistry. 96(32). 13110–13119. 3 indexed citations
4.
Huber, Marinus, et al.. (2024). The Perils of Molecular Interpretations from Vibrational Spectra of Complex Samples. Angewandte Chemie International Edition. 63(50). e202411596–e202411596. 3 indexed citations
5.
Kepesidis, Kosmas V., Frank Fleischmann, Birgit Linkohr, et al.. (2024). Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening. Cell Reports Medicine. 5(7). 101625–101625. 5 indexed citations
6.
Huber, Marinus, Alexander Weigel, Mark Kielpinski, et al.. (2023). High-Speed Field-Resolved Infrared Fingerprinting of Particles in Flow. The HKU Scholars Hub (University of Hong Kong). 1–1.
7.
Huber, Marinus, Michael K. Trubetskov, Wolfgang Schweinberger, et al.. (2023). Standardising Electric-Field-Resolved Molecular Fingerprints. The HKU Scholars Hub (University of Hong Kong). 1–1. 1 indexed citations
8.
Huber, Marinus, Kosmas V. Kepesidis, Frank Fleischmann, et al.. (2021). Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer. eLife. 10. 26 indexed citations
9.
Mueller‐Reif, Johannes B., Philipp E. Geyer, Marinus Huber, et al.. (2021). Molecular Origin of Blood‐Based Infrared Spectroscopic Fingerprints**. Angewandte Chemie International Edition. 60(31). 17060–17069. 21 indexed citations
10.
Mueller‐Reif, Johannes B., Philipp E. Geyer, Marinus Huber, et al.. (2021). Molecular Origin of Blood‐Based Infrared Spectroscopic Fingerprints**. Angewandte Chemie. 133(31). 17197–17206. 4 indexed citations
11.
Huber, Marinus, Kosmas V. Kepesidis, Michael K. Trubetskov, et al.. (2021). Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring. Nature Communications. 12(1). 1511–1511. 46 indexed citations
12.
Kepesidis, Kosmas V., Marinus Huber, Sharif Kullab, et al.. (2021). Breast-cancer detection using blood-based infrared molecular fingerprints. BMC Cancer. 21(1). 1287–1287. 13 indexed citations
13.
Pupeza, Ioachim, Marinus Huber, Michael K. Trubetskov, et al.. (2020). Field-resolved infrared spectroscopy of biological systems. Nature. 577(7788). 52–59. 190 indexed citations breakdown →
14.
Huber, Marinus, Wolfgang Schweinberger, Michael K. Trubetskov, et al.. (2017). Detection sensitivity of field-resolved spectroscopy in the molecular fingerprint region. 11. 1–1. 3 indexed citations
15.
Žigman, Mihaela, Trushar R. Patel, Julia Christina Gross, et al.. (2014). Molecular dissection of Wnt3a-Frizzled8 interaction reveals essential and modulatory determinants of Wnt signaling activity. BMC Biology. 12(1). 44–44. 27 indexed citations
16.
Žigman, Mihaela, et al.. (2014). Hoxb1b controls oriented cell division, cell shape and microtubule dynamics in neural tube morphogenesis. Development. 141(3). 639–649. 18 indexed citations
17.
Žigman, Mihaela, Le A. Trinh, Scott E. Fraser, & Cecilia B. Moens. (2010). Zebrafish Neural Tube Morphogenesis Requires Scribble-Dependent Oriented Cell Divisions. Current Biology. 21(1). 79–86. 55 indexed citations
18.
Žigman, Mihaela, Michel Cayouette, C. Charalambous, et al.. (2005). Mammalian Inscuteable Regulates Spindle Orientation and Cell Fate in the Developing Retina. Neuron. 48(4). 539–545. 101 indexed citations
19.
Weinhofer, Isabelle, Sonja Forss‐Petter, Markus Kunze, Mihaela Žigman, & Johannes Berger. (2005). X‐linked adrenoleukodystrophy mice demonstrate abnormalities in cholesterol metabolism. FEBS Letters. 579(25). 5512–5516. 26 indexed citations
20.

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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