Marcelo Behar

1.7k total citations
23 papers, 1.3k citations indexed

About

Marcelo Behar is a scholar working on Molecular Biology, Cancer Research and Immunology. According to data from OpenAlex, Marcelo Behar has authored 23 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 10 papers in Cancer Research and 7 papers in Immunology. Recurrent topics in Marcelo Behar's work include NF-κB Signaling Pathways (10 papers), Immune Response and Inflammation (6 papers) and Fungal and yeast genetics research (6 papers). Marcelo Behar is often cited by papers focused on NF-κB Signaling Pathways (10 papers), Immune Response and Inflammation (6 papers) and Fungal and yeast genetics research (6 papers). Marcelo Behar collaborates with scholars based in United States, Japan and Russia. Marcelo Behar's co-authors include Alexander Hoffmann, Timothy C. Elston, Henrik Dohlman, Nan Hao, Gourisankar Ghosh, Soumen Basak, Shannon L. Werner, Derren Barken, Peter E. Wright and Beverly Errede and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Marcelo Behar

21 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcelo Behar United States 20 902 344 261 145 94 23 1.3k
Adaoha Ihekwaba United Kingdom 7 854 0.9× 324 0.9× 300 1.1× 152 1.0× 70 0.7× 20 1.4k
Elaine Sullivan United Kingdom 9 883 1.0× 372 1.1× 330 1.3× 190 1.3× 64 0.7× 13 1.4k
Caroline A. Horton United Kingdom 8 974 1.1× 516 1.5× 468 1.8× 206 1.4× 86 0.9× 9 1.6k
Shengbao Suo China 22 1.8k 2.0× 372 1.1× 197 0.8× 405 2.8× 86 0.9× 44 2.3k
Pawel Paszek United Kingdom 22 1.2k 1.3× 724 2.1× 498 1.9× 239 1.6× 97 1.0× 41 2.0k
Benjamin Emert United States 14 1.3k 1.4× 155 0.5× 293 1.1× 290 2.0× 98 1.0× 19 1.6k
Fedor Kolpakov Russia 18 1.4k 1.6× 147 0.4× 242 0.9× 107 0.7× 78 0.8× 75 1.9k
Melinda Halász Ireland 17 724 0.8× 321 0.9× 196 0.8× 162 1.1× 108 1.1× 41 1.3k
Ina Rothenaigner Germany 16 463 0.5× 114 0.3× 137 0.5× 101 0.7× 101 1.1× 27 1.0k
Peter Thul Germany 6 925 1.0× 104 0.3× 222 0.9× 97 0.7× 144 1.5× 7 1.3k

Countries citing papers authored by Marcelo Behar

Since Specialization
Citations

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

Fields of papers citing papers by Marcelo Behar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcelo Behar

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

All Works

20 of 20 papers shown
1.
Iwakiri, Ryuichi, Zhen Qi, Yuki Sato, et al.. (2022). A Computational Platform Integrating a Mechanistic Model of Crohn’s Disease for Predicting Temporal Progression of Mucosal Damage and Healing. Advances in Therapy. 39(7). 3225–3247. 24 indexed citations
2.
Parnell, Stephen, Nan Hao, Christoph H. Borchers, et al.. (2021). A Systems-Biology Analysis of Feedback Inhibition in the Sho1 Osmotic-Stress-Response Pathway. UNC Libraries.
3.
Behar, Marcelo, et al.. (2018). The effects of IKK-beta inhibition on early NF-kappa-B activation and transcription of downstream genes. Cellular Signalling. 55. 17–25. 29 indexed citations
4.
Busch, David J., et al.. (2018). Entropic Control of Receptor Recycling Using Engineered Ligands. Biophysical Journal. 114(6). 1377–1388. 19 indexed citations
5.
Cheng, Christine S., et al.. (2017). Iterative Modeling Reveals Evidence of Sequential Transcriptional Control Mechanisms. Cell Systems. 4(3). 330–343.e5. 40 indexed citations
6.
Inoue, Kentaro, Hisaaki Shinohara, Marcelo Behar, et al.. (2016). Oscillation dynamics underlie functional switching of NF-κB for B-cell activation. npj Systems Biology and Applications. 2(1). 16024–16024. 24 indexed citations
7.
Fagerlund, Riku, et al.. (2015). Anatomy of a negative feedback loop: the case of I κ B α. Journal of The Royal Society Interface. 12(110). 20150262–20150262. 25 indexed citations
8.
Behar, Marcelo, et al.. (2015). Topology, dynamics, and heterogeneity in immune signaling. WIREs Systems Biology and Medicine. 7(5). 285–300. 5 indexed citations
9.
Behar, Marcelo & Alexander Hoffmann. (2013). Tunable Signal Processing through a Kinase Control Cycle: the IKK Signaling Node. Biophysical Journal. 105(1). 231–241. 22 indexed citations
10.
Behar, Marcelo, Derren Barken, Shannon L. Werner, & Alexander Hoffmann. (2013). The Dynamics of Signaling as a Pharmacological Target. Cell. 155(2). 448–461. 104 indexed citations
11.
Behar, Marcelo, et al.. (2013). Analysis of the RelA:CBP/p300 Interaction Reveals Its Involvement in NF-κB-Driven Transcription. PLoS Biology. 11(9). e1001647–e1001647. 116 indexed citations
12.
Schröfelbauer, Bärbel, Smarajit Polley, Marcelo Behar, Gourisankar Ghosh, & Alexander Hoffmann. (2012). NEMO Ensures Signaling Specificity of the Pleiotropic IKKβ by Directing Its Kinase Activity toward IκBα. Molecular Cell. 47(1). 111–121. 81 indexed citations
13.
Basak, Soumen, Marcelo Behar, & Alexander Hoffmann. (2012). Lessons from mathematically modeling the NF‐κB pathway. Immunological Reviews. 246(1). 221–238. 104 indexed citations
14.
Behar, Marcelo & Alexander Hoffmann. (2010). Understanding the temporal codes of intra-cellular signals. Current Opinion in Genetics & Development. 20(6). 684–693. 129 indexed citations
15.
Hao, Nan, Sujata Nayak, Marcelo Behar, et al.. (2008). Regulation of Cell Signaling Dynamics by the Protein Kinase-Scaffold Ste5. Molecular Cell. 30(5). 649–656. 102 indexed citations
16.
Behar, Marcelo, Nan Hao, Henrik Dohlman, & Timothy C. Elston. (2008). Dose-to-Duration Encoding and Signaling beyond Saturation in Intracellular Signaling Networks. PLoS Computational Biology. 4(10). e1000197–e1000197. 45 indexed citations
17.
Hao, Nan, Marcelo Behar, Timothy C. Elston, & Henrik Dohlman. (2007). Systems biology analysis of G protein and MAP kinase signaling in yeast. Oncogene. 26(22). 3254–3266. 31 indexed citations
18.
Hao, Nan, Marcelo Behar, Stephen C. Parnell, et al.. (2007). A Systems-Biology Analysis of Feedback Inhibition in the Sho1 Osmotic-Stress-Response Pathway. Current Biology. 17(8). 659–667. 87 indexed citations
19.
Behar, Marcelo, Nan Hao, Henrik Dohlman, & Timothy C. Elston. (2007). Mathematical and Computational Analysis of Adaptation via Feedback Inhibition in Signal Transduction Pathways. Biophysical Journal. 93(3). 806–821. 89 indexed citations
20.
Behar, Marcelo, Henrik Dohlman, & Timothy C. Elston. (2007). Kinetic insulation as an effective mechanism for achieving pathway specificity in intracellular signaling networks. Proceedings of the National Academy of Sciences. 104(41). 16146–16151. 63 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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