Ozlem Senol-Cosar

1.1k total citations · 1 hit paper
6 papers, 543 citations indexed

About

Ozlem Senol-Cosar is a scholar working on Physiology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ozlem Senol-Cosar has authored 6 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Physiology, 3 papers in Genetics and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Ozlem Senol-Cosar's work include Adipose Tissue and Metabolism (3 papers), Genomics and Rare Diseases (2 papers) and Genetic Associations and Epidemiology (2 papers). Ozlem Senol-Cosar is often cited by papers focused on Adipose Tissue and Metabolism (3 papers), Genomics and Rare Diseases (2 papers) and Genetic Associations and Epidemiology (2 papers). Ozlem Senol-Cosar collaborates with scholars based in United States, Germany and United Kingdom. Ozlem Senol-Cosar's co-authors include Marina T. DiStefano, Heather Mason‐Suares, Matthew S. Lebo, Kaitlin H. Wade, Eric S. Lander, Myriam Fornage, Nicholas J. Timpson, Lee M. Kaplan, George Davey Smith and Sekar Kathiresan and has published in prestigious journals such as Cell, Nature Communications and American Journal of Physiology-Endocrinology and Metabolism.

In The Last Decade

Ozlem Senol-Cosar

6 papers receiving 528 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood

2019 432 citations Amit V. Khera, Mark Chaffin et al. Cell profile →

Peers

Ozlem Senol-Cosar

GENET

PHYSI

PHEOH

MB

PPCH

Yuvreet Kaur Canada

Lu Qi United States

Theresia M. Schnurr Denmark

Muagututi‘a Sefuiva Reupena United States

Paul Sack United States

Junling Fu China

Jaspal S. Kooner United Kingdom

Camilla Andreasen Denmark

Lynda M. Rose United States

Yuvreet Kaur Canada

Ozlem Senol-Cosar

150 ×0.6

GENET

136 ×0.8

PHYSI

113 ×0.8

PHEOH

117 ×0.9

MB

39 ×0.5

PPCH

Citations per year, relative to Ozlem Senol-Cosar Ozlem Senol-Cosar (= 1×) peers Yuvreet Kaur

Countries citing papers authored by Ozlem Senol-Cosar

Since Specialization

Citations

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

Fields of papers citing papers by Ozlem Senol-Cosar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ozlem Senol-Cosar. 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 Ozlem Senol-Cosar. The network helps show where Ozlem Senol-Cosar may publish in the future.

Co-authorship network of co-authors of Ozlem Senol-Cosar

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

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Senol-Cosar, Ozlem, Ryan J. Schmidt, Emily Qian, et al.. (2019). Considerations for clinical curation, classification, and reporting of low-penetrance and low effect size variants associated with disease risk. Genetics in Medicine. 21(12). 2765–2773. 15 indexed citations

2.

Khera, Amit V., Mark Chaffin, Kaitlin H. Wade, et al.. (2019). Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood. Cell. 177(3). 587–596.e9. 432 indexed citations breakdown →

3.

McGlaughon, Jennifer, Marzia Pasquali, Kathleen Wallace, et al.. (2019). Assessing the strength of evidence for genes implicated in fatty acid oxidation disorders using the ClinGen clinical validity framework. Molecular Genetics and Metabolism. 128(1-2). 122–128. 2 indexed citations

4.

Flach, Rachel J. Roth, Marina T. DiStefano, Laura V. Danai, et al.. (2017). Map4k4 impairs energy metabolism in endothelial cells and promotes insulin resistance in obesity. American Journal of Physiology-Endocrinology and Metabolism. 313(3). E303–E313. 12 indexed citations

5.

DiStefano, Marina T., Rachel J. Roth Flach, Ozlem Senol-Cosar, et al.. (2016). Adipocyte-specific Hypoxia-inducible gene 2 promotes fat deposition and diet-induced insulin resistance. Molecular Metabolism. 5(12). 1149–1161. 33 indexed citations

6.

Senol-Cosar, Ozlem, Rachel J. Roth Flach, Marina T. DiStefano, et al.. (2016). Tenomodulin promotes human adipocyte differentiation and beneficial visceral adipose tissue expansion. Nature Communications. 7(1). 10686–10686. 49 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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