John G. Albeck

6.8k total citations · 1 hit paper
55 papers, 4.8k citations indexed

About

John G. Albeck is a scholar working on Molecular Biology, Biophysics and Computational Theory and Mathematics. According to data from OpenAlex, John G. Albeck has authored 55 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 9 papers in Biophysics and 7 papers in Computational Theory and Mathematics. Recurrent topics in John G. Albeck's work include Gene Regulatory Network Analysis (12 papers), Cell Image Analysis Techniques (8 papers) and Melanoma and MAPK Pathways (7 papers). John G. Albeck is often cited by papers focused on Gene Regulatory Network Analysis (12 papers), Cell Image Analysis Techniques (8 papers) and Melanoma and MAPK Pathways (7 papers). John G. Albeck collaborates with scholars based in United States, China and South Korea. John G. Albeck's co-authors include Peter K. Sorger, Suzanne Gaudet, John M. Burke, Douglas A. Lauffenburger, Sabrina L. Spencer, Kevin A. Janes, Joan S. Brugge, Yin P. Hung, Gordon B. Mills and Gary Yellen and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

John G. Albeck

54 papers receiving 4.8k citations

Hit Papers

Non-genetic origins of ce... 2009 2026 2014 2020 2009 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John G. Albeck United States 29 3.7k 661 612 576 570 55 4.8k
Lani F. Wu United States 30 4.5k 1.2× 525 0.8× 401 0.7× 1.2k 2.1× 343 0.6× 68 6.5k
Sabrina L. Spencer United States 25 2.6k 0.7× 855 1.3× 442 0.7× 435 0.8× 336 0.6× 45 3.7k
Emma Lundberg Sweden 35 4.0k 1.1× 468 0.7× 461 0.8× 550 1.0× 372 0.7× 93 5.6k
Chris Bakal United Kingdom 30 1.9k 0.5× 733 1.1× 585 1.0× 539 0.9× 496 0.9× 74 3.3k
Galit Lahav United States 37 5.8k 1.6× 2.5k 3.7× 842 1.4× 699 1.2× 417 0.7× 62 7.3k
Nikolas K. Haass Australia 36 2.8k 0.8× 1.7k 2.5× 579 0.9× 169 0.3× 572 1.0× 99 4.3k
Martin Kampmann United States 43 6.6k 1.8× 580 0.9× 601 1.0× 207 0.4× 541 0.9× 96 8.7k
Berend Snijder Switzerland 23 2.4k 0.7× 508 0.8× 729 1.2× 321 0.6× 522 0.9× 56 3.9k
Li V. Yang United States 32 2.3k 0.6× 624 0.9× 582 1.0× 175 0.3× 866 1.5× 91 4.2k
Suzanne Gaudet United States 19 2.0k 0.5× 327 0.5× 279 0.5× 267 0.5× 401 0.7× 33 2.9k

Countries citing papers authored by John G. Albeck

Since Specialization
Citations

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

Fields of papers citing papers by John G. Albeck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John G. Albeck. 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 John G. Albeck. The network helps show where John G. Albeck may publish in the future.

Co-authorship network of co-authors of John G. Albeck

This figure shows the co-authorship network connecting the top 25 collaborators of John G. Albeck. A scholar is included among the top collaborators of John G. Albeck 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 John G. Albeck. John G. Albeck 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.
Pargett, Michael, et al.. (2025). Monitoring Cellular Energy Balance in Single Cells Using Fluorescent Biosensors for AMPK. Methods in molecular biology. 2882. 47–79.
2.
Paul, Debasish, Hualong Yan, Sudipto Das, et al.. (2025). Transient APC/C inactivation by mTOR boosts glycolysis during cell cycle entry. Nature. 646(8083). 198–207. 1 indexed citations
3.
Pacifici, Noah, et al.. (2025). Identification of signaling networks associated with lactate modulation of macrophages and dendritic cells. Heliyon. 11(3). e42098–e42098. 4 indexed citations
4.
Pargett, Michael, et al.. (2024). Spatiotemporal Clusters of Extracellular Signal-Regulated Kinase Activity Coordinate Cytokine-induced Inflammatory Responses in Human Airway Epithelial Cells. American Journal of Respiratory Cell and Molecular Biology. 72(5). 520–532. 3 indexed citations
5.
Berg, Anastasia L., Megan R. Showalter, Michelle Hu, et al.. (2023). Cellular transformation promotes the incorporation of docosahexaenoic acid into the endolysosome-specific lipid bis(monoacylglycerol)phosphate in breast cancer. Cancer Letters. 557. 216090–216090. 4 indexed citations
6.
Jia, Junjing, Asuka Nishimura, Kazuaki Ohara, et al.. (2023). Applications of Plant-Made Fibroblast Growth Factor for Human Pluripotent Stem Cells. Stem Cells and Development. 33(3-4). 57–66. 2 indexed citations
7.
Albeck, John G., et al.. (2021). Entosis is induced by ultraviolet radiation. iScience. 24(8). 102902–102902. 16 indexed citations
8.
Zhu, Kan, Michael Pargett, Quan Qing, et al.. (2021). Electrically synchronizing and modulating the dynamics of ERK activation to regulate cell fate. iScience. 24(11). 103240–103240. 8 indexed citations
9.
Gillies, Taryn E., Michael Pargett, Jillian M. Silva, et al.. (2020). Oncogenic mutant RAS signaling activity is rescaled by the ERK/MAPK pathway. Molecular Systems Biology. 16(10). e9518–e9518. 39 indexed citations
10.
Sampattavanich, Somponnat, et al.. (2018). Encoding Growth Factor Identity in the Temporal Dynamics of FOXO3 under the Combinatorial Control of ERK and AKT Kinases. Cell Systems. 6(6). 664–678.e9. 33 indexed citations
11.
Kochańczyk, Marek, Paweł Kocieniewski, Michael Pargett, et al.. (2017). Relaxation oscillations and hierarchy of feedbacks in MAPK signaling. Scientific Reports. 7(1). 38244–38244. 40 indexed citations
12.
Pargett, Michael, et al.. (2017). Single-Cell Imaging of ERK Signaling Using Fluorescent Biosensors. Methods in molecular biology. 1636. 35–59. 23 indexed citations
13.
Rodriguez, Raymond L., John G. Albeck, Ameer Y. Taha, et al.. (2017). Impact of diet-derived signaling molecules on human cognition: exploring the food–brain axis. npj Science of Food. 1(1). 2–2. 14 indexed citations
14.
Selimkhanov, Jangir, Brooks Taylor, Jason Yao, et al.. (2014). Accurate information transmission through dynamic biochemical signaling networks. Science. 346(6215). 1370–1373. 262 indexed citations
15.
Hu, Hai, Ashish Juvekar, Costas A. Lyssiotis, et al.. (2014). Phosphoinositide 3-Kinase regulates glycolysis through mobilization of Aldolase A from the actin cytoskeleton. Cancer & Metabolism. 2(S1). 23 indexed citations
16.
Dey‐Guha, Ipsita, Anita Wolfer, Albert C. Yeh, et al.. (2011). Asymmetric cancer cell division regulated by AKT. Proceedings of the National Academy of Sciences. 108(31). 12845–12850. 101 indexed citations
17.
Hung, Yin P., John G. Albeck, Mathew Tantama, & Gary Yellen. (2011). Imaging Cytosolic NADH-NAD+ Redox State with a Genetically Encoded Fluorescent Biosensor. Cell Metabolism. 14(4). 545–554. 394 indexed citations
18.
Janes, Kevin A., Suzanne Gaudet, John G. Albeck, et al.. (2006). The Response of Human Epithelial Cells to TNF Involves an Inducible Autocrine Cascade. Cell. 124(6). 1225–1239. 166 indexed citations
19.
Janes, Kevin A., John G. Albeck, Lili Peng, et al.. (2003). A High-throughput Quantitative Multiplex Kinase Assay for Monitoring Information Flow in Signaling Networks. Molecular & Cellular Proteomics. 2(7). 463–473. 85 indexed citations
20.
Feng, Qiyu, John G. Albeck, Richard A. Cerione, & Wannian Yang. (2002). Regulation of the Cool/Pix Proteins. Journal of Biological Chemistry. 277(7). 5644–5650. 90 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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