Shaul Mezan

1.2k total citations · 1 hit paper
8 papers, 1.0k citations indexed

About

Shaul Mezan is a scholar working on Molecular Biology, Cancer Research and Cellular and Molecular Neuroscience. According to data from OpenAlex, Shaul Mezan has authored 8 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Shaul Mezan's work include RNA modifications and cancer (3 papers), Cancer-related molecular mechanisms research (3 papers) and Neurobiology and Insect Physiology Research (3 papers). Shaul Mezan is often cited by papers focused on RNA modifications and cancer (3 papers), Cancer-related molecular mechanisms research (3 papers) and Neurobiology and Insect Physiology Research (3 papers). Shaul Mezan collaborates with scholars based in Israel, Switzerland and Germany. Shaul Mezan's co-authors include Abraham Hochberg, Rasha Abu-lail, Imad Matouk, Eithan Galun, N DEGROOT, Suhail Ayesh, Yakov Fellig, Patricia Ohana, Sebastián Kadener and Vladimir Sorin and has published in prestigious journals such as The Journal of Immunology, PLoS ONE and PLoS Genetics.

In The Last Decade

Shaul Mezan

8 papers receiving 1.0k 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.

The H19 Non-Coding RNA Is Essential for Human Tumor Growth

2007 555 citations Imad Matouk, N DEGROOT et al. PLoS ONE profile →

Peers

Shaul Mezan

MB

CR

EPIDE

ONCOL

SURGE

Tommaso Colangelo Italy

Xiaofang Ying China

Nancy L. Maas United States

Jacob Biesinger United States

Alejandro Athie United States

Xingying Guan China

Jiazhen Zhang United Kingdom

Chantal Depatie Canada

Alan J. Diehl United States

Selma El Messaoudi France

Tommaso Colangelo Italy

Shaul Mezan

376 ×0.4

MB

300 ×0.4

CR

41 ×0.4

EPIDE

115 ×2.1

ONCOL

29 ×0.6

SURGE

Citations per year, relative to Shaul Mezan Shaul Mezan (= 1×) peers Tommaso Colangelo

Countries citing papers authored by Shaul Mezan

Since Specialization

Citations

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

Fields of papers citing papers by Shaul Mezan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaul Mezan

This figure shows the co-authorship network connecting the top 25 collaborators of Shaul Mezan. A scholar is included among the top collaborators of Shaul Mezan 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 Shaul Mezan. Shaul Mezan 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:

8 of 8 papers shown

1.

Lerner, Immanuel, et al.. (2020). Discovery of Novel GABAAR Allosteric Modulators Through Reinforcement Learning. Current Pharmaceutical Design. 26(44). 5713–5719. 2 indexed citations

2.

Mezan, Shaul, Andreas Kühbacher, Doris Finkelmeier, et al.. (2018). Computationally Designed Bispecific MD2/CD14 Binding Peptides Show TLR4 Agonist Activity. The Journal of Immunology. 201(11). 3383–3391. 16 indexed citations

3.

Mezan, Shaul, et al.. (2016). PDF Signaling Is an Integral Part of the Drosophila Circadian Molecular Oscillator. Cell Reports. 17(3). 708–719. 40 indexed citations

4.

Weiss, Ron, et al.. (2014). Synergistic Interactions between the Molecular and Neuronal Circadian Networks Drive Robust Behavioral Circadian Rhythms in Drosophila melanogaster. PLoS Genetics. 10(4). e1004252–e1004252. 15 indexed citations

5.

Matouk, Imad, Eli Raveh, Rasha Abu-lail, et al.. (2014). Oncofetal H19 RNA promotes tumor metastasis. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1843(7). 1414–1426. 203 indexed citations

6.

Mezan, Shaul, et al.. (2013). Genome-wide assessment of post-transcriptional control in the fly brain. Frontiers in Molecular Neuroscience. 6. 49–49. 7 indexed citations

7.

Matouk, Imad, Shaul Mezan, Patricia Ohana, et al.. (2010). The oncofetal H19 RNA connection: Hypoxia, p53 and cancer. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1803(4). 443–451. 203 indexed citations

8.

Matouk, Imad, N DEGROOT, Shaul Mezan, et al.. (2007). The H19 Non-Coding RNA Is Essential for Human Tumor Growth. PLoS ONE. 2(9). e845–e845. 555 indexed citations breakdown →

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.

Explore authors with similar magnitude of impact