Gordan Lauc

16.9k total citations
298 papers, 8.4k citations indexed

About

Gordan Lauc is a scholar working on Molecular Biology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Gordan Lauc has authored 298 papers receiving a total of 8.4k indexed citations (citations by other indexed papers that have themselves been cited), including 232 papers in Molecular Biology, 108 papers in Immunology and 92 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Gordan Lauc's work include Glycosylation and Glycoproteins Research (196 papers), Monoclonal and Polyclonal Antibodies Research (92 papers) and Galectins and Cancer Biology (79 papers). Gordan Lauc is often cited by papers focused on Glycosylation and Glycoproteins Research (196 papers), Monoclonal and Polyclonal Antibodies Research (92 papers) and Galectins and Cancer Biology (79 papers). Gordan Lauc collaborates with scholars based in Croatia, United States and United Kingdom. Gordan Lauc's co-authors include Olga Gornik, Igor Rudan, Irena Trbojević‐Akmačić, Marija Pezer, Ivan Gudelj, Maja Pučić‐Baković, Harry Campbell, Pauline M. Rudd, Mislav Novokmet and Vlatka Zoldoš and has published in prestigious journals such as Chemical Reviews, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Gordan Lauc

289 papers receiving 8.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gordan Lauc Croatia 48 6.4k 3.2k 2.6k 1.2k 954 298 8.4k
Alice L. Yu United States 56 6.1k 1.0× 2.1k 0.7× 815 0.3× 692 0.6× 449 0.5× 297 11.9k
Tamao Endo Japan 47 5.8k 0.9× 1.4k 0.4× 644 0.3× 545 0.5× 1.0k 1.1× 201 7.5k
James W. Dennis Canada 63 10.8k 1.7× 5.5k 1.7× 1.3k 0.5× 633 0.5× 2.7k 2.8× 206 15.8k
Roy A. Black United States 50 7.3k 1.1× 3.9k 1.2× 901 0.4× 873 0.7× 271 0.3× 95 14.8k
Menachem Rubinstein Israel 54 5.0k 0.8× 4.3k 1.4× 994 0.4× 807 0.7× 147 0.2× 161 10.8k
Corrado Baglioni United States 64 6.5k 1.0× 3.3k 1.0× 944 0.4× 1.2k 1.0× 437 0.5× 256 12.3k
Frank R. Jirik Canada 52 4.1k 0.6× 2.7k 0.8× 545 0.2× 601 0.5× 132 0.1× 153 8.0k
Pierre A. Henkart United States 58 4.5k 0.7× 4.8k 1.5× 762 0.3× 460 0.4× 311 0.3× 135 9.7k
Bradly G. Wouters Canada 62 7.2k 1.1× 968 0.3× 1.8k 0.7× 695 0.6× 401 0.4× 225 14.9k
Stefano Iacobelli Italy 46 3.4k 0.5× 2.5k 0.8× 593 0.2× 504 0.4× 210 0.2× 221 8.7k

Countries citing papers authored by Gordan Lauc

Since Specialization
Citations

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

Fields of papers citing papers by Gordan Lauc

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gordan Lauc

This figure shows the co-authorship network connecting the top 25 collaborators of Gordan Lauc. A scholar is included among the top collaborators of Gordan Lauc 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 Gordan Lauc. Gordan Lauc 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.
Tzartos, John, Maja Pučić‐Baković, Gordan Lauc, et al.. (2025). Humoral correlates of clinical response to thymectomy in myasthenia gravis. Journal of Autoimmunity. 158. 103517–103517.
2.
3.
Vujić, Ana, Marija Klasić, Gordan Lauc, et al.. (2024). Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition. International Journal of Molecular Sciences. 25(18). 9988–9988. 1 indexed citations
4.
Lauc, Gordan, et al.. (2024). High-throughput N-glycan analysis in aging and inflammaging: State of the art and future directions. Seminars in Immunology. 73. 101890–101890. 5 indexed citations
5.
Krištić, Jasminka, et al.. (2023). Long-Term Culturing of FreeStyle 293-F Cells Affects Immunoglobulin G Glycome Composition. Biomolecules. 13(8). 1245–1245. 1 indexed citations
6.
Knjaz, Damir, et al.. (2023). Regular moderate physical exercise decreases Glycan Age index of biological age and reduces inflammatory potential of Immunoglobulin G. Glycoconjugate Journal. 41(1). 67–76. 3 indexed citations
7.
Gudelj, Ivan, Gabriel Santpere, Mislav Novokmet, et al.. (2023). Human-specific features and developmental dynamics of the brain N-glycome. Science Advances. 9(49). eadg2615–eadg2615. 9 indexed citations
8.
Trbojević‐Akmačić, Irena, Frano Vučković, Marija Vilaj, et al.. (2023). Comparative analysis of transferrin and IgG N-glycosylation in two human populations. Communications Biology. 6(1). 312–312. 10 indexed citations
9.
Haan, Noortje de, Maja Pučić‐Baković, Mislav Novokmet, et al.. (2022). Developments and perspectives in high-throughput protein glycomics: enabling the analysis of thousands of samples. Glycobiology. 32(8). 651–663. 32 indexed citations
10.
Birukov, Anna, Fabian Eichelmann, Olga Kuxhaus, et al.. (2022). Immunoglobulin G N-Glycosylation Signatures in Incident Type 2 Diabetes and Cardiovascular Disease. Diabetes Care. 45(11). 2729–2736. 30 indexed citations
11.
Trbojević‐Akmačić, Irena, Pau Navarro, Yakov A. Tsepilov, et al.. (2022). Genetic regulation of post-translational modification of two distinct proteins. Nature Communications. 13(1). 1586–1586. 23 indexed citations
12.
Polančec, Denis, Damir Hudetz, Željko Jeleč, et al.. (2021). Polychromatic Flow Cytometric Analysis of Stromal Vascular Fraction from Lipoaspirate and Microfragmented Counterparts Reveals Sex-Related Immunophenotype Differences. Genes. 12(12). 1999–1999. 9 indexed citations
13.
Uh, Hae‐Won, Lucija Klarić, Ivo Ugrina, et al.. (2020). Choosing proper normalization is essential for discovery of sparse glycan biomarkers. Molecular Omics. 16(3). 231–242. 15 indexed citations
14.
Benedetti, Elisa, Maja Pučić‐Baković, Toma Keser, et al.. (2020). Systematic Evaluation of Normalization Methods for Glycomics Data Based on Performance of Network Inference. Metabolites. 10(7). 271–271. 15 indexed citations
15.
Igonet, Sébastien, Erika Cecon, Maja Pučić‐Baković, et al.. (2018). Enabling STD-NMR fragment screening using stabilized native GPCR: A case study of adenosine receptor. Scientific Reports. 8(1). 45 indexed citations
16.
Vučković, Frano, Evropi Τheodoratou, Maria Timofeeva, et al.. (2016). IgG Glycome in Colorectal Cancer. Clinical Cancer Research. 22(12). 3078–3086. 109 indexed citations
17.
Perović, Darko, Damir Hudetz, Eduard Rod, et al.. (2016). Personalizirana medicina u modernoj radiologiji, neurologiji, neurokirurgiji, ortopediji, anesteziologiji, fizikalnoj medicini i rehabilitaciji te pedijatriji: Model Specijalne bolnice Sv. Katarina. 60. 1–17.
18.
Lauc, Gordan & Vlatka Zoldoš. (2010). Protein glycosylation—an evolutionary crossroad between genes and environment. Molecular BioSystems. 6(12). 2373–2379. 32 indexed citations
19.
Lauc, Gordan, Igor Rudan, Harry Campbell, & Pauline M. Rudd. (2009). Complex genetic regulation of proteinglycosylation. Molecular BioSystems. 6(2). 329–335. 59 indexed citations
20.
Lauc, Gordan, et al.. (2002). Lectins Labelled with Digoxin as a Novel Tool to Study Glycoconjugates. SHILAP Revista de lepidopterología. 1 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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