Maja Galić

51 total papers · 953 total citations
27 papers, 654 citations indexed

About

Maja Galić is a scholar working on Psychiatry and Mental health, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Maja Galić has authored 27 papers receiving a total of 654 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Psychiatry and Mental health, 5 papers in Molecular Biology and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Maja Galić's work include Migraine and Headache Studies (13 papers), Trigeminal Neuralgia and Treatments (4 papers) and Sympathectomy and Hyperhidrosis Treatments (3 papers). Maja Galić is often cited by papers focused on Migraine and Headache Studies (13 papers), Trigeminal Neuralgia and Treatments (4 papers) and Sympathectomy and Hyperhidrosis Treatments (3 papers). Maja Galić collaborates with scholars based in United States, Australia and Israel. Maja Galić's co-authors include Peter H. Janssen, Richard A. Strugnell, Joshua M. Cohen, Leanne Sait, Xiaoping Ning, Lindsay Janka, Messoud Ashina, Ronghua Yang, Melissa Grozinski‐Wolff and Michel D. Ferrari and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and Applied and Environmental Microbiology.

In The Last Decade

Maja Galić

23 papers receiving 632 citations

Hit Papers

Fremanezumab versus place... 2019 2026 2021 2023 2019 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Maja Galić 344 240 132 123 70 27 654
Manuel Ramos-Kuri 93 0.3× 85 0.4× 141 1.1× 80 0.7× 92 1.3× 20 592
I. M. S. Sawhney 316 0.9× 199 0.8× 81 0.6× 59 0.5× 129 1.8× 45 788
Mianwang He 507 1.5× 253 1.1× 45 0.3× 118 1.0× 58 0.8× 31 749
Işıl Fidan 123 0.4× 89 0.4× 65 0.5× 45 0.4× 24 0.3× 46 570
Ali Daneshmand 85 0.2× 79 0.3× 184 1.4× 76 0.6× 66 0.9× 28 757
Fatemeh Asgari 133 0.4× 68 0.3× 130 1.0× 30 0.2× 70 1.0× 45 729
Christine Robinson 104 0.3× 130 0.5× 137 1.0× 41 0.3× 120 1.7× 25 675
Norbert Mueller 90 0.3× 82 0.3× 78 0.6× 62 0.5× 138 2.0× 15 676
Birgit Keller 70 0.2× 148 0.6× 109 0.8× 14 0.1× 91 1.3× 46 775
Redda Tekle Haimanot 202 0.6× 107 0.4× 28 0.2× 52 0.4× 47 0.7× 22 678

Countries citing papers authored by Maja Galić

Since Specialization
Citations

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

Fields of papers citing papers by Maja Galić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maja Galić

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

All Works

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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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