Carsten Peterson

14.8k total citations · 2 hit papers
157 papers, 10.1k citations indexed

About

Carsten Peterson is a scholar working on Molecular Biology, Nuclear and High Energy Physics and Artificial Intelligence. According to data from OpenAlex, Carsten Peterson has authored 157 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Molecular Biology, 42 papers in Nuclear and High Energy Physics and 29 papers in Artificial Intelligence. Recurrent topics in Carsten Peterson's work include Quantum Chromodynamics and Particle Interactions (36 papers), Particle physics theoretical and experimental studies (33 papers) and High-Energy Particle Collisions Research (25 papers). Carsten Peterson is often cited by papers focused on Quantum Chromodynamics and Particle Interactions (36 papers), Particle physics theoretical and experimental studies (33 papers) and High-Energy Particle Collisions Research (25 papers). Carsten Peterson collaborates with scholars based in Sweden, United States and Denmark. Carsten Peterson's co-authors include Lao H. Saal, Markus Ringnér, Carl Troein, Bo Söderberg, Paul S. Meltzer, Javed Khan, Marc Ladanyi, Cristina R. Antonescu, Frank Berthold and Manfred Schwab and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nucleic Acids Research.

In The Last Decade

Carsten Peterson

154 papers receiving 9.7k citations

Hit Papers

Classification and diagno... 2001 2026 2009 2017 2001 2001 500 1000 1.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Carsten Peterson 4.4k 2.2k 1.5k 743 713 157 10.1k
Yuval Kluger 7.2k 1.6× 774 0.3× 859 0.6× 706 1.0× 1.6k 2.3× 155 12.4k
Roderick V. Jensen 2.0k 0.5× 855 0.4× 956 0.6× 232 0.3× 381 0.5× 120 8.1k
Kim Sneppen 4.3k 1.0× 1.3k 0.6× 338 0.2× 1.7k 2.3× 111 0.2× 262 11.4k
Herschel Rabitz 2.6k 0.6× 462 0.2× 5.8k 3.9× 258 0.3× 278 0.4× 942 30.9k
Gyan Bhanot 2.8k 0.6× 1.7k 0.7× 514 0.3× 204 0.3× 1.3k 1.8× 162 7.5k
Eytan Domany 8.2k 1.9× 99 0.0× 1.2k 0.8× 974 1.3× 2.2k 3.1× 275 17.0k
C. Barnes 1.9k 0.4× 942 0.4× 181 0.1× 774 1.0× 614 0.9× 84 5.0k
A. Arnéodo 3.5k 0.8× 129 0.1× 402 0.3× 489 0.7× 133 0.2× 228 10.7k
Gastón H. Gonnet 3.5k 0.8× 271 0.1× 2.0k 1.4× 758 1.0× 60 0.1× 129 11.0k
Stephen T. Smale 11.8k 2.7× 128 0.1× 199 0.1× 2.1k 2.9× 3.1k 4.3× 236 25.7k

Countries citing papers authored by Carsten Peterson

Since Specialization
Citations

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

Fields of papers citing papers by Carsten Peterson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carsten Peterson

This figure shows the co-authorship network connecting the top 25 collaborators of Carsten Peterson. A scholar is included among the top collaborators of Carsten Peterson 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 Carsten Peterson. Carsten Peterson 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.
Rothenberg, Ellen V., et al.. (2024). T-cell commitment inheritance—an agent-based multi-scale model. npj Systems Biology and Applications. 10(1). 40–40. 1 indexed citations
2.
Irbäck, Anders, et al.. (2024). Using quantum annealing to design lattice proteins. Physical Review Research. 6(1). 7 indexed citations
3.
Anguita, Eduardo, Rajeev Gupta, Victor Olariu, et al.. (2016). A somatic mutation of GFI1B identified in leukemia alters cell fate via a SPI1 (PU.1) centered genetic regulatory network. Developmental Biology. 411(2). 277–286. 15 indexed citations
4.
Manesso, Erica, et al.. (2016). Irreversibility of T-Cell Specification: Insights from Computational Modelling of a Minimal Network Architecture. PLoS ONE. 11(8). e0161260–e0161260. 6 indexed citations
5.
May, Gillian, Shamit Soneji, Alex J. Tipping, et al.. (2013). Dynamic Analysis of Gene Expression and Genome-wide Transcription Factor Binding during Lineage Specification of Multipotent Progenitors. Cell stem cell. 13(6). 754–768. 58 indexed citations
6.
Krupinski, Pawel, Vijay Chickarmane, & Carsten Peterson. (2012). Computational multiscale modeling of embryo development. Current Opinion in Genetics & Development. 22(6). 613–618. 12 indexed citations
7.
Gruvberger-Saal, Sofia K., Pär‐Ola Bendahl, Lao H. Saal, et al.. (2007). Estrogen Receptor β Expression Is Associated with Tamoxifen Response in ERα-Negative Breast Carcinoma. Clinical Cancer Research. 13(7). 1987–1994. 154 indexed citations
8.
Jönsson, Henrik, et al.. (2006). A Rate Equation Approach to Elucidate the Kinetics and Robustness of the TGF-β Pathway. Biophysical Journal. 91(12). 4368–4380. 41 indexed citations
9.
Niméus, Emma, Patrik Edén, Anders Johnsson, et al.. (2006). Gene expression profilers and conventional clinical markers to predict distant recurrences for premenopausal breast cancer patients after adjuvant chemotherapy. European Journal of Cancer. 42(16). 2729–2737. 20 indexed citations
10.
Chickarmane, Vijay, Carl Troein, Ulrike A. Nuber, Herbert M. Sauro, & Carsten Peterson. (2006). Transcriptional Dynamics of the Embryonic Stem Cell Switch. PLoS Computational Biology. 2(9). e123–e123. 190 indexed citations
11.
Gruvberger-Saal, Sofia K., Patrik Edén, Markus Ringnér, et al.. (2004). Predicting continuous values of prognostic markers in breast cancer from microarray gene expression profiles. Molecular Cancer Therapeutics. 3(2). 161–168. 25 indexed citations
13.
Ohlsson, Mattias, et al.. (1999). A confident decision support system for interpreting electrocardiograms. Clinical Physiology. 19(5). 410–418. 45 indexed citations
14.
Irbäck, Anders, Carsten Peterson, & Frańk Potthast. (1996). Identification of Amino Acid Sequences with Good Folding Properties. arXiv (Cornell University). 3 indexed citations
15.
Ohlsson, Mattias, et al.. (1996). Agreement between Artificial Neural Networks and Human Expert for the Electrocardiographic Diagnosis of Healed Myocardial Infarction. 3 indexed citations
17.
Ohlsson, Mattias, et al.. (1995). Artificial neural networks for recognition of electrocardiographic lead reversal. The American Journal of Cardiology. 75(14). 929–933. 49 indexed citations
18.
Ohlsson, Mattias, Carsten Peterson, Hong Pi, Thorsteinn Rögnvaldsson, & Bo Söderberg. (1994). Predicting System loads with Artificial Neural Networks : Method and Result from "the Great Energy Predictor Shootout". Lund University Publications (Lund University). 33 indexed citations
19.
Peterson, Carsten & James R. Anderson. (1988). Neural networks and NP-complete optimization problems; a performance study on the graph bisection problem. Complex Systems. 2(1). 59–89. 72 indexed citations
20.
Peterson, Carsten. (1987). A Mean Field Theory Learning Algorithm for N e u r al N e t wo r ks. Complex Systems. 1. 995–1019. 28 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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