Arina Hadziselimovic

1.3k total citations
17 papers, 999 citations indexed

About

Arina Hadziselimovic is a scholar working on Molecular Biology, Physiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Arina Hadziselimovic has authored 17 papers receiving a total of 999 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 7 papers in Physiology and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Arina Hadziselimovic's work include Alzheimer's disease research and treatments (6 papers), Protein Structure and Dynamics (5 papers) and Lipid Membrane Structure and Behavior (4 papers). Arina Hadziselimovic is often cited by papers focused on Alzheimer's disease research and treatments (6 papers), Protein Structure and Dynamics (5 papers) and Lipid Membrane Structure and Behavior (4 papers). Arina Hadziselimovic collaborates with scholars based in United States, Germany and South Korea. Arina Hadziselimovic's co-authors include Charles R. Sanders, Wade D. Van Horn, Andrew J. Beel, Johanna M. Schafer, Eric J. Hustedt, Yuanli Song, Paul J. Barrett, Hak Jun Kim, Charles D. Ellis and Charles K. Mobley and has published in prestigious journals such as Science, Journal of Biological Chemistry and Molecular and Cellular Biology.

In The Last Decade

Arina Hadziselimovic

17 papers receiving 987 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arina Hadziselimovic United States 13 728 368 168 155 89 17 999
Taraneh Mirzadegan United States 16 660 0.9× 241 0.7× 78 0.5× 232 1.5× 61 0.7× 32 1.2k
Andrew J. Beel United States 7 672 0.9× 545 1.5× 145 0.9× 88 0.6× 121 1.4× 10 988
Yvonne M. Newhouse United States 19 776 1.1× 313 0.9× 120 0.7× 129 0.8× 376 4.2× 28 1.3k
Jillian Madine United Kingdom 19 564 0.8× 471 1.3× 88 0.5× 66 0.4× 23 0.3× 68 1.0k
François‐Xavier Cantrelle France 23 929 1.3× 549 1.5× 228 1.4× 178 1.1× 17 0.2× 71 1.4k
Isabelle Huvent France 21 779 1.1× 489 1.3× 163 1.0× 127 0.8× 24 0.3× 38 1.2k
Markus Koglin Germany 17 826 1.1× 214 0.6× 59 0.4× 352 2.3× 56 0.6× 22 1.1k
Mayumi Shindo Japan 16 722 1.0× 348 0.9× 200 1.2× 81 0.5× 29 0.3× 25 979
Jesper Søndergaard Pedersen Denmark 15 830 1.1× 467 1.3× 120 0.7× 80 0.5× 59 0.7× 17 1.3k
Yihong Yao United States 13 724 1.0× 103 0.3× 138 0.8× 255 1.6× 33 0.4× 18 969

Countries citing papers authored by Arina Hadziselimovic

Since Specialization
Citations

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

Fields of papers citing papers by Arina Hadziselimovic

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arina Hadziselimovic

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

All Works

17 of 17 papers shown
1.
Hutchison, J.M.S., et al.. (2021). Recombinant SARS-CoV-2 envelope protein traffics to the trans-Golgi network following amphipol-mediated delivery into human cells. Journal of Biological Chemistry. 297(2). 100940–100940. 4 indexed citations
2.
Capone, Ricardo, Ajit Tiwari, Arina Hadziselimovic, et al.. (2021). The C99 domain of the amyloid precursor protein resides in the disordered membrane phase. Journal of Biological Chemistry. 296. 100652–100652. 18 indexed citations
3.
Capone, Ricardo, Ajit Tiwari, Nico Fricke, et al.. (2020). Use of Giant Plasma Membrane Vesicles (GPMV) to Examine the Lo/Ld Phase Preference of the C99 Domain of the Amyloid Precursor Protein. Biophysical Journal. 118(3). 392a–392a. 1 indexed citations
4.
Castro, Manuel, Arina Hadziselimovic, & Charles R. Sanders. (2019). The vexing complexity of the amyloidogenic pathway. Protein Science. 28(7). 1177–1193. 25 indexed citations
5.
Huang, Hui, Georg Kuenze, Jarrod A. Smith, et al.. (2018). Mechanisms of KCNQ1 channel dysfunction in long QT syndrome involving voltage sensor domain mutations. Science Advances. 4(3). eaar2631–eaar2631. 65 indexed citations
6.
Mittendorf, Kathleen F., Justin T. Marinko, Cheri M. Hampton, et al.. (2017). Peripheral myelin protein 22 alters membrane architecture. Science Advances. 3(7). e1700220–e1700220. 42 indexed citations
7.
Lu, Zhenwei, S. Mathew, Jiang Chen, et al.. (2016). Implications of the differing roles of the β1 and β3 transmembrane and cytoplasmic domains for integrin function. eLife. 5. 26 indexed citations
8.
Kim, Ji-Hun, Dungeng Peng, Jonathan P. Schlebach, Arina Hadziselimovic, & Charles R. Sanders. (2014). Modest Effects of Lipid Modifications on the Structure of Caveolin-3. Biochemistry. 53(27). 4320–4322. 22 indexed citations
9.
Barrett, Paul J., Yuanli Song, Wade D. Van Horn, et al.. (2012). The Amyloid Precursor Protein Has a Flexible Transmembrane Domain and Binds Cholesterol. Science. 336(6085). 1168–1171. 387 indexed citations
10.
Hadziselimovic, Arina, et al.. (2012). Purification and Characterization of the Human γ-Secretase Activating Protein. Biochemistry. 51(25). 5153–5159. 14 indexed citations
11.
Mathew, S., Zhenwei Lu, Glenda Mernaugh, et al.. (2012). β1 Integrin NPXY Motifs Regulate Kidney Collecting-Duct Development and Maintenance by Induced-Fit Interactions with Cytosolic Proteins. Molecular and Cellular Biology. 32(20). 4080–4091. 9 indexed citations
12.
Sakakura, Masayoshi, Arina Hadziselimovic, Zhen Wang, Kevin L. Schey, & Charles R. Sanders. (2011). Structural Basis for the Trembler-J Phenotype of Charcot-Marie-Tooth Disease. Structure. 19(8). 1160–1169. 34 indexed citations
13.
Hadziselimovic, Arina, et al.. (2010). Look and See if It Is Time To Induce Protein Expression in Escherichia coli Cultures. Biochemistry. 49(26). 5405–5407. 7 indexed citations
14.
Horn, Wade D. Van, Hak Jun Kim, Charles D. Ellis, et al.. (2009). Solution Nuclear Magnetic Resonance Structure of Membrane-Integral Diacylglycerol Kinase. Science. 324(5935). 1726–1729. 168 indexed citations
15.
Beel, Andrew J., Charles K. Mobley, Hak Jun Kim, et al.. (2008). Structural Studies of the Transmembrane C-Terminal Domain of the Amyloid Precursor Protein (APP): Does APP Function as a Cholesterol Sensor?. Biochemistry. 47(36). 9428–9446. 145 indexed citations
16.
Mobley, Charles K., Jeffrey K. Myers, Arina Hadziselimovic, Charles D. Ellis, & Charles R. Sanders. (2007). Purification and Initiation of Structural Characterization of Human Peripheral Myelin Protein 22, an Integral Membrane Protein Linked to Peripheral Neuropathies. Biochemistry. 46(39). 11185–11195. 19 indexed citations
17.

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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