Maja Pučić‐Baković

6.0k citations
47 papers · 2.3k indexed · h-index 24
Topics
Glycosylation and Glycoproteins Research (37 papers)Monoclonal and Polyclonal Antibodies Research (22 papers)Galectins and Cancer Biology (13 papers)

In The Last Decade

Maja Pučić‐Baković

46 papers receiving 2.3k citations

Peers

Maja Pučić‐Baković
Comparison fields: 5 of 110
  • Molecular Biology 1.9k
  • Immunology 999
  • Radiology, Nuclear Medicine and Imaging 922
  • Genetics 302
  • Organic Chemistry 261
Replace О. О. Фаворова with:
О. О. Фаворова Russia
Wouter Laroy Belgium
Patrick Bulau Germany
Lakshmi Amaravadi United States
Kebing Yu United States
David G. Williams United Kingdom
Martin Eggert Germany
David Chang United States
Kyunggon Kim South Korea
Christopher L. Reading United States
Maja Pučić‐Baković relative to О. О. Фаворова Russia О. О. Фаворова's profile →
Citations per field
00.5×10×15.4×
О. О. Фаворова · 1×
Citations per year

Countries citing papers authored by Maja Pučić‐Baković

Since Specialization
Citations

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

Fields of papers citing papers by Maja Pučić‐Baković

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maja Pučić‐Baković. 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 Maja Pučić‐Baković. The network helps show where Maja Pučić‐Baković may publish in the future.

Co-authorship network of co-authors of Maja Pučić‐Baković

This figure shows the co-authorship network connecting the top 25 collaborators of Maja Pučić‐Baković. A scholar is included among the top collaborators of Maja Pučić‐Baković 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 Maja Pučić‐Baković. Maja Pučić‐Baković 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
#WorkIndexed citations
1 0
2 9
3 10
4 32
5 6
6 15
7 17
8 13
9 45
10 109
11 6
12 10
13 136
14 53
15 6
16 53
17 16
18 57
19 199
20 40

About Maja Pučić‐Baković

Maja Pučić‐Baković is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 47 papers that have together received 2.3k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (37 papers), Monoclonal and Polyclonal Antibodies Research (22 papers) and Galectins and Cancer Biology (13 papers). The work is most often cited by research in Immunology (999 citations), Radiology, Nuclear Medicine and Imaging (922 citations) and Molecular Biology (1.9k citations). Maja Pučić‐Baković has collaborated with scholars based in Croatia, United Kingdom and United States. Frequent co-authors include Gordan Lauc, Igor Rudan, Mislav Novokmet, Olga Gornik, Pauline M. Rudd, Harry Campbell, Manfred Wuhrer, Ozren Polašek, Alan F. Wright and Ana Knežević. Their work appears in journals such as Nature Communications, Gastroenterology and PLoS ONE.

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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