Iva Kulić

991 total citations
10 papers, 744 citations indexed

About

Iva Kulić is a scholar working on Physiology, Molecular Biology and Oncology. According to data from OpenAlex, Iva Kulić has authored 10 papers receiving a total of 744 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Physiology, 4 papers in Molecular Biology and 4 papers in Oncology. Recurrent topics in Iva Kulić's work include Alzheimer's disease research and treatments (5 papers), Cholesterol and Lipid Metabolism (3 papers) and Drug Transport and Resistance Mechanisms (2 papers). Iva Kulić is often cited by papers focused on Alzheimer's disease research and treatments (5 papers), Cholesterol and Lipid Metabolism (3 papers) and Drug Transport and Resistance Mechanisms (2 papers). Iva Kulić collaborates with scholars based in Canada, United States and Australia. Iva Kulić's co-authors include Aly Karsan, Connie J. Eaves, Ingrid L. Pollet, Kevin G. Leong, Kyle Niessen, Afshin Raouf, Cheryl L. Wellington, Jérôme Robert, Sophie Stukas and Emily B. Button and has published in prestigious journals such as The Journal of Experimental Medicine, The Journal of Cell Biology and PLoS ONE.

In The Last Decade

Iva Kulić

9 papers receiving 718 citations

Peers

Iva Kulić

MB

ONCOL

PHYSI

CR

SURGE

Dan Ye China

Mikhail A. Kolpakov United States

Ludger Hauck Canada

Mita Das United States

Claire E. Walters United Kingdom

Pauline de Zeeuw Belgium

Xin‐Sheng Deng United States

Hansjörg Habisch Austria

Tahira Lemtalsi United States

Sebastian A. Lewandowski Sweden

Dan Ye China

Iva Kulić

527 ×1.2

MB

133 ×0.6

ONCOL

86 ×0.5

PHYSI

106 ×0.8

CR

177 ×1.7

SURGE

Citations per year, relative to Iva Kulić Iva Kulić (= 1×) peers Dan Ye

Countries citing papers authored by Iva Kulić

Since Specialization

Citations

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

Fields of papers citing papers by Iva Kulić

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iva Kulić

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

All Works

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10 of 10 papers shown

1.

Kulić, Iva, et al.. (2024). Abstract 6028: Preferential tumor-to-normal tissue biodistribution and single-dose efficacy with ABD147, a DLL3-targeted engineered antibody-based radiotherapeutic, in preclinical small cell lung cancer models. Cancer Research. 84(6_Supplement). 6028–6028.

2.

Robertson, A. Gordon, Iva Kulić, Yu‐Hsuan Huang, et al.. (2023). Tumor-derived GCSF Alters Tumor and Systemic Immune System Cell Subset Composition and Signaling. Cancer Research Communications. 3(3). 404–419. 3 indexed citations

3.

Fan, Jianjia, Wenchen Zhao, Jérôme Robert, et al.. (2018). Small molecule inducers of ABCA1 and apoE that act through indirect activation of the LXR pathway. Journal of Lipid Research. 59(5). 830–842. 37 indexed citations

4.

Robert, Jérôme, Emily B. Button, Sophie Stukas, et al.. (2017). Clearance of beta-amyloid is facilitated by apolipoprotein E and circulating high-density lipoproteins in bioengineered human vessels. eLife. 6. 95 indexed citations

5.

Robert, Jérôme, Emily B. Button, Sophie Stukas, et al.. (2017). High-density lipoproteins suppress Aβ-induced PBMC adhesion to human endothelial cells in bioengineered vessels and in monoculture. Molecular Neurodegeneration. 12(1). 60–60. 44 indexed citations

6.

Fan, Jianjia, Wenchen Zhao, Yoko Shimizu, et al.. (2016). Identification of a Chrysanthemic Ester as an Apolipoprotein E Inducer in Astrocytes. PLoS ONE. 11(9). e0162384–e0162384. 18 indexed citations

7.

Robert, Jérôme, Sophie Stukas, Emily B. Button, et al.. (2015). Reconstituted high-density lipoproteins acutely reduce soluble brain Aβ levels in symptomatic APP/PS1 mice. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1862(5). 1027–1036. 66 indexed citations

8.

Stukas, Sophie, Jérôme Robert, Michael Lee, et al.. (2014). Intravenously Injected Human Apolipoprotein A‐I Rapidly Enters the Central Nervous System via the Choroid Plexus. Journal of the American Heart Association. 3(6). e001156–e001156. 76 indexed citations

9.

Leong, Kevin G., Kyle Niessen, Iva Kulić, et al.. (2007). Jagged1-mediated Notch activation induces epithelial-to-mesenchymal transition through Slug-induced repression of E-cadherin. The Journal of Experimental Medicine. 204(12). 2935–2948. 389 indexed citations

10.

Leong, Kevin G., Kyle Niessen, Iva Kulić, et al.. (2007). Jagged1-mediated Notch activation induces epithelial-to-mesenchymal transition through Slug-induced repression of E-cadherin. The Journal of Cell Biology. 179(4). i6–i6. 16 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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