John J. Tyson

22.4k total citations · 3 hit papers
263 papers, 15.3k citations indexed

About

John J. Tyson is a scholar working on Molecular Biology, Cell Biology and Computer Networks and Communications. According to data from OpenAlex, John J. Tyson has authored 263 papers receiving a total of 15.3k indexed citations (citations by other indexed papers that have themselves been cited), including 176 papers in Molecular Biology, 74 papers in Cell Biology and 43 papers in Computer Networks and Communications. Recurrent topics in John J. Tyson's work include Gene Regulatory Network Analysis (123 papers), Microtubule and mitosis dynamics (69 papers) and Fungal and yeast genetics research (51 papers). John J. Tyson is often cited by papers focused on Gene Regulatory Network Analysis (123 papers), Microtubule and mitosis dynamics (69 papers) and Fungal and yeast genetics research (51 papers). John J. Tyson collaborates with scholars based in United States, United Kingdom and Hungary. John J. Tyson's co-authors include Béla Novák, Katherine Chen, James P. Keener, Attila Csikász‐Nagy, Paul C. Fife, Andrea Ciliberto, Kathy Chen, Béla Györffy, Robert Clarke and William T. Baumann and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

John J. Tyson

255 papers receiving 14.8k 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.

Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell

2003 1.1k citations John J. Tyson, Katherine Chen et al. profile →
Design principles of biochemical oscillators

2008 811 citations Béla Novák, John J. Tyson profile →
Singular perturbation theory of traveling waves in excitable media (a review)

1988 579 citations John J. Tyson et al. profile →

Peers

Countries citing papers authored by John J. Tyson

Since Specialization

Citations

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

Fields of papers citing papers by John J. Tyson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John J. Tyson

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Stochastic Boolean model of normal and aberrant cell cycles in budding yeast 2024 ·npj Systems Biology and Applications ·(unknown), John J. Tyson, Teeraphan Laomettachit, Pavel Kraikivski	0
2	Newton's cradle: Cell cycle regulation by two mutually inhibitory oscillators 2024 ·Mathematical Biosciences ·(unknown), John J. Tyson, Béla Novák	0
3	Evolutionary Stability of Small Molecular Regulatory Networks That Exhibit Near-Perfect Adaptation 2023 ·Biology ·Rajat Singhania, John J. Tyson	3
4	Feedback in the β-catenin destruction complex imparts bistability and cellular memory 2023 ·Proceedings of the National Academy of Sciences ·(unknown), Elaheh Alizadeh, Janani Ravi, (unknown), (unknown), (unknown), Arminja N. Kettenbach, Yashi Ahmed, Andrew L. Paek, John J. Tyson, Konstantin Doubrovinski, Ethan Lee, Curtis A. Thorne	9
5	Mathematical analysis of robustness of oscillations in models of the mammalian circadian clock 2022 ·PLoS Computational Biology ·(unknown), (unknown), Jing Chen, John J. Tyson	12
6	Natural antisense transcript of Period2, Per2AS, regulates the amplitude of the mouse circadian clock 2021 ·Genes & Development ·Rebecca Mosig, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Nobuya Koike, John J. Tyson, Carla B. Green, Joseph S. Takahashi, Shihoko Kojima	8
7	A hybrid stochastic model of the budding yeast cell cycle 2020 ·npj Systems Biology and Applications ·(unknown), John J. Tyson, Jean Peccoud, Yang Cao	10
8	Model-driven experimental approach reveals the complex regulatory distribution of p53 by the circadian factor Period 2 2016 ·Proceedings of the National Academy of Sciences ·Tetsuya Gotoh, Jae Kyoung Kim, Jingjing Liu, Marian Vila-Caballer, (unknown), John J. Tyson, Carla V. Finkielstein	72
9	Experimental testing of a new integrated model of the budding yeast Starttransition 2015 ·Molecular Biology of the Cell ·Neil Adames, (unknown), Katherine Chen, T. M. Murali, John J. Tyson, Jean Peccoud	16
10	Role for regulated phosphatase activity in generating mitotic oscillations in Xenopus cell-free extracts 2013 ·Proceedings of the National Academy of Sciences ·Tongli Zhang, John J. Tyson, Béla Novák	5
11	Modeling the estrogen receptor to growth factor receptor signaling switch in human breast cancer cells 2013 ·FEBS Letters ·Chun Chen, William T. Baumann, Robert Clarke, John J. Tyson	21
12	System‐level feedbacks control cell cycle progression 2009 ·FEBS Letters ·Orsolya Kapuy, (unknown), Sandra López‐Avilés, Frank Uhlmann, John J. Tyson, Béla Novák	28
13	Fusing and composing macromolecular regulatory network models 2007 ·Spring Simulation Multiconference ·Ranjit Randhawa, Clifford A. Shaffer, John J. Tyson	3
14	Challenges for modeling and simulation methods in systems biology 2006 ·Winter Simulation Conference ·Herbert M. Sauro, David Harel, Adelinde M. Uhrmacher, Michael Hucka, Marta Kwiatkowska, Clifford A. Shaffer, Pedro Mendes, Lena Strömbäck, John J. Tyson	13
15	The role of composition and aggregation in modeling macromolecular regulatory networks 2006 ·Winter Simulation Conference ·Clifford A. Shaffer, Ranjit Randhawa, John J. Tyson	6
16	Integrative Analysis of Cell Cycle Control in Budding Yeast 2004 ·Molecular Biology of the Cell ·Katherine Chen, Laurence Calzone, Attila Csikász‐Nagy, Frederick R. Cross, Béla Novák, John J. Tyson	444
17	Cómo los CEO gestionan sus agendas de crecimiento 2004 ·Harvard business review ·Ranjay Gulati, (unknown), (unknown), (unknown), John J. Tyson, (unknown)	14
18	A deterministic molecular model of the fission yeast cell cycle. 2003 ·Yeast ·Ákos Sveiczer, Attila Csikász‐Nagy, John J. Tyson, Béla Novák	1
19	Model scenarios for evolution of the eukaryotic cell cycle 1997 ·European Journal of Cell Biology ·Béla Novák, Attila Csikász‐Nagy, Béla Györffy, John J. Tyson	1
20	QWL Strategies: Quality Circles. 1983 ·The Journal of Academic Librarianship ·Charles Martell, John J. Tyson	2

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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