Publications - Carsten Peterson
Computational Biology & Biological Physics, Lund University

For publications in collaboration with biomedical groups, my name appears last or next-to-last
in the list of authors, whereas when collaborating with other theorists, alphabetical orderings are used.

Quantum Computing

Functional Genomics and Systems Biology

    Regulation of fungal decomposition at single-cell level
    M. Op De Beeck, C. Troein, S. Siregar, L. Gentile, G. Abbondanza, C. Peterson, P. Persson and A. Tunlid
    The ISME Journal 14, 896-905 (2020)
    [abs] [pdf]

    Haematopoietic stem cells: entropic landscapes of differentiation
    K. Wiesner, J. Teles, M. Hartnor and C. Peterson
    Royal Society Interface Focus 8, 20180040 (2018)
    [abs] [pdf]

    Kinetic models of hematopoietic differentiation
    V. Olariu and C. Peterson
    WIREs System Biology and Medicine, e1424 (2018)
    [abs] [pdf]

    A Fenton reaction facilitates organic nitrogen acquisition by an ectomycorrhizal fungus
    M. Op De Beeck, C. Troein, C. Peterson, P. Persson and A. Tunlid
    New Phytologist 218, 335-43 (2018)
    [abs] [pdf]

    A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths
    V. Olariu, E. Manesso and C. Peterson
    Editor's suggestion Royal Society Open Science 4, 160765 (2017)
    [abs] [pdf]

    Different reprogramming propensities in plants and mammals: Are small variations in the core network wirings responsible?
    V. Olariu, J. Nilsson, H. Jönsson and C. Peterson
    PLoS ONE 12, e0175251 (2017)
    [abs] [pdf]

    Irreversibility of T-cell specification: insights from computational modelling of a minimal network architecture
    E. Manesso, H.Y. Kueh, G. Freedman, E.V. Rothenberg and C. Peterson
    PLoS ONE 11, e0161260 (2016)
    [abs] [pdf]

Access the recommendation on F1000Prime
    Selection shapes transcriptional logic and regulatory specialization in genetic networks
    K. Fogelmark, C. Peterson and C. Troein
    PLoS ONE 11, e0150340 (2016)
    [abs] [pdf]

    A somatic mutation of GFI1B identified in leukemia alters cell fate via a SPI1 (PU.1) centered genetic regulatory network
    E. Anguita, R. Gupta, V. Olariu, P.J. Valk, C. Peterson, R. Delwel and T. Enver
    Developmental Biology 411, 277-86 (2016)
    [abs] [pdf]

    Single-cell network analysis identifies DDIT3 as a nodal lineage regulator in hematopoiesis
    C. Pina, J. Teles, C. Fugazza, G. May, D. Wang, Y. Guo, S. Soneji, J. Brown, P. Edén, M. Ohlsson, C. Peterson and T. Enver
    Cell Reports 11, 1-8 (2015)
    [abs] [pdf]

    Dynamic analysis of gene expression and genome-wide transcription factor binding during lineage specification of multipotent progenitors
    G. May, S. Soneji, A.J. Tipping, J. Teles, S.J. McGowan, M. Wu, Y. Guo, C. Fugazza, J. Brown, G. Karlsson, C. Pina, V. Olariu, S. Taylor, D.G. Tenen, C. Peterson and T. Enver
    Cell Stem Cell 6, 754-768 (2013)
    [abs] [pdf]

    Transcriptional regulation of lineage commitment - a stochastic model of cell fate decisions
    J. Teles, C. Pina, P. Edén, M. Ohlsson, T. Enver and C. Peterson
    PLoS Computational Biology 9, e1003197 (2013)
    [abs] [pdf]

    Dynamical modelling of haematopoiesis: an integrated view over the system in homeostasis and under perturbation
    E. Manesso, J. Teles, D. Bryder and C. Peterson
    Journal of the Royal Society Interface 10, 20120817 (2013)
    [abs] [pdf]

    Computational modeling of T-cell formation kinetics: output regulated by initial proliferation-linked deferral of developmental competence
    E. Manesso, V. Chickarmane, H.Y. Kueh, E.V. Rothenberg and C. Peterson
    Journal of the Royal Society Interface 10, 20120774 (2013)
    [abs] [pdf]

    Computational multiscale modelling of embryo development
    P. Krupinski, V. Chickarmane and C. Peterson
    Current Opinion in Genetics & Development 22, 613-618 (2012)
    [abs] [pdf]

    Probing the role of stochasticity in a model of the embryonic stem cell -- heterogeneous gene expression and reprogramming efficiency
    V. Chickarmane, V. Olariu and C. Peterson
    BMC Systems Biology 6, 98 (2012)
    [abs] [pdf]

    Inferring rules of lineage commitment in haematopoiesis
    C. Pina, C. Fugazza, A.J. Tipping, J.Brown, S. Soneji, J. Teles, C. Peterson and T. Enver
    Nature Cell Biology 14, 287-294 (2012)
    [abs] [pdf] [highlight] [Faculty of 1000]

    Revisiting the erythroid-myeloid lineage decision - a data-driven dynamical model analysis
    J. Teles, V. Olariu and C. Peterson
    bioRxiv doi: https://doi.org/10.1101/197822 (2012)
    [abs] [pdf]

    Molecular serum portraits in patients with primary breast cancer predict the development of distant metastases
    A. Carlsson, C. Wingren, M. Kristensson, C. Rose, M. Fernö, H. Olsson, H. Jernström, S. Ek, E. Gustavsson, C. Ingvar, M. Ohlsson, C. Peterson and C.A.K. Borrebaeck
    Proceedings of the National Academy of Sciences USA 108, 14252-14257 (2011)
    [abs] [pdf]

    Simulating the mammalian blastocyst - molecular and mechanical interactions pattern the embryo
    P. Krupinski, V. Chickarmane and C. Peterson
    PLoS Computational Biology 7, e1001128 (2011)
    [abs] [pdf]

    Identification of uniquely expressed transcription factors in highly purified B-cell lymphoma samples
    U. Andréasson, P. Edén, C. Peterson, C-M Högerkorp, M. Jerkeman, N. Andersen, M. Berglund, C. Sundström, R. Rosenquist, C.A.K. Borrebaeck and S. Ek
    American Journal of Hematology 85, 418-425 (2010)
    [abs] [pdf]

    Tissue-Specific Regulatory Network Extractor (TS-REX): A database and software resource for the tissue and cell type-specific investigation of transcription factor-gene networks
    F. Colecchia, D. Kottwitz, M. Wagner, C. Pfenninger, G. Thiel, I. Tamm, C. Peterson and U. Nuber
    Nucleic Acids Research 37, e82 (2009)
    [abs] [pdf]

    Stem cell states, fates and the rules of attraction
    T. Enver, M. Pera, C. Peterson and P.W. Andrews
    Cell Stem Cell 4, 387-397 (2009)
    [abs] [pdf]

    Computational modeling of the hematopoietic erythroid-myeloid switch reveals insights into co-operativity, priming and irreversibility
    V. Chickarmane, T. Enver and C. Peterson
    PLoS Computational Biology 5, e1000268 (2009)
    [abs] [pdf]

    A computational model for understanding stem cell, trophectoderm and endoderm lineage determination
    V. Chickarmane and C. Peterson
    PLoS ONE 3, e3478 (2008)
    [abs] [pdf]

    Detection of pancreatic cancer using antibody microarray-based serum protein profiling
    J. Ingvarsson, C. Wingren, A. Carlsson, P. Ellmark, B. Wahren, G. Engström, U. Harmenberg, M. Krogh, C. Peterson and C. Borrebaeck
    Proteomics 8, 2211-2219 (2008)
    [abs] [pdf]

    Gene expression profiling in primary breast cancer distinguishes patients developing local recurrence after breast conservation surgery with or without postoperative radiotherapy
    E. Niméus, M. Krogh, P. Malmström, C. Strand, I. Fredriksson, P. Karlsson, B. Nordenskjöld, O. Stål, G. Östberg, C. Peterson and M. Fernö
    Breast Cancer Research 10, R34 (2008)
    [abs] [pdf]

    Is transcriptional regulation of metabolic pathways an optimal strategy for fitness?
    C. Troein, D. Ahrén, M. Krogh and C. Peterson
    PLoS ONE 2, e855 (2007)
    [abs] [pdf]

    Estrogen receptor beta predicts tamoxifen sensitivity for estrogen receptor alpha negative breast cancer
    S.K. Gruvberger-Saal, P-O. Bendahl, L.H. Saal, M. Laakso, P. Edén, C. Peterson, P. Malmström, J. Isola, Å. Borg and M. Fernö
    Clinical Cancer Research 13, 1987-1994 (2007)
    [abs] [pdf]

    Transcriptional dynamics of the embryonic stem cell switch
    V. Chickarmane, C. Troein, U. Nuber, H.M. Sauro and C. Peterson
    PLoS Computational Biology 2, e123 (2006)
    [abs] [pdf] [supplement]

    A rate equation approach to elucidate the kinetics and robustness of the TGF-β pathway
    P. Melke, H. Jönsson, P. ten Dijke, E. Pardali and C. Peterson
    Biophysical Journal 91, 4368-4380 (2006)
    [abs] [pdf]

    Gene expression profilers and conventional clinical markers to predict distant recurrences for premenopausal breast cancer patients after adjuvant chemotherapy
    E. Niméus-Malmström, C. Ritz, P. Edén, A. Johnsson, M. Ohlsson, C. Strand, G. Östberg, M. Fernö and C. Peterson
    European Journal of Cancer 42, 2729-2737 (2006)
    [abs] [pdf]

    Signal transduction pathway profiling of individual tumor samples
    T. Breslin, M. Krogh, C. Peterson and C. Troein
    BMC Bioinformatics 6, 163 (2005)
    [abs] [pdf]

    Genetic networks with canalyzing Boolean rules are always stable
    S. Kauffman, C. Peterson, B. Samuelsson and C. Troein
    Proceedings of the National Academy of Sciences USA 101, 17102-17107 (2004)
    [abs] [pdf] [supplement]

    ''Good old'' clinical markers have similar power in breast cancer prognosis as microarray gene expression profilers
    P. Edén, C. Ritz, C. Rose, M. Fernö and C. Peterson
    European Journal of Cancer 40, 1837-1841 (2004)
    [abs] [pdf] [editorial]

    Predicting continuous values of prognostic markers in breast cancer from microarray gene expression profiles
    S.K. Gruvberger-Saal, P. Edén, M. Ringnér, B. Baldetorp, G. Chebil, Å. Borg, M. Fernö, C. Peterson and P.S. Meltzer
    Molecular Cancer Therapeutics 3, 161-168 (2004)
    [abs] [pdf]

    Genomic signal processing
    X. Wang, Y. Chen, E.R. Dougherty and C. Peterson (eds.)
    Journal of Applied Signal Processing 2004:1, 3-4 (2004)
    [pdf]

    Random Boolean network models and the yeast transcriptional network
    S. Kauffman, C. Peterson, B. Samuelsson and C. Troein
    Proceedings of the National Academy of Sciences USA 100, 14796-14799 (2003)
    [abs] [pdf] [supplement]

    Computational biology -- opportunities and challenges for theoretical physicists
    C. Peterson
    Proceedings of the Seventh Workshop on Quantum Chromodynamics, H.M Fried, B. Muller and Y. Gabellini (eds.),
    Singapore, World Scientific (2003)
    [abs]

    Predicting the future of breast cancer
    Å. Borg, M. Fernö and C. Peterson
    Nature Medicine 9, 16-18 (2003)
    [pdf]

    RNA analysis of B-cell lines arrested at defined stages of differentiation allows for an approximation of
    gene expression patterns during B-cell development

    P. Tsapogas, T. Breslin, S. Bilke, A. Lagergren, R. Månsson, D. Liberg, C. Peterson and M. Sigvardsson
    Journal of Leukocyte Biology 74, 102-110 (2003)
    [abs] [pdf] [supplement]

    Microarray-based cancer diagnosis with artificial neural networks
    M. Ringnér and C. Peterson
    Biotechniques 34, S30-S35 (2003)
    [abs] [pdf]

    Expression profiling to predict outcome in breast cancer: the influence of sample selection
    S. Gruvberger, M. Ringnér, P. Edén, Å. Borg, M. Fernö, C. Peterson and P.S. Meltzer
    Breast Cancer Research 5, 23-26 (2003)
    [abs] [pdf]

    Analyzing tumor gene expression profiles
    C. Peterson and M. Ringnér
    Artificial Intelligence in Medicine 28, 59-74 (2003)
    [abs] [pdf]

    Bioarray software environment: a platform for comprehensive management and analysis of microarray data
    L.H. Saal, C. Troein, J. Vallon-Christersson, S. Gruvberger, Å. Borg and C. Peterson
    Genome Biology 3, software0003.1-software0003.6 (2002)
    [abs] [pdf]

    Analysing array data using supervised methods
    M. Ringnér, C. Peterson and J. Khan
    Pharmacogenomics 3, 403-415 (2002)
    [abs] [pdf]

    Topological properties of citation and metabolic networks
    S. Bilke and C. Peterson
    Physical Review E64, 036106 (2001)
    [abs] [pdf]

    Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns
    S. Gruvberger, M. Ringnér, Y. Chen, S. Panavally, L.H. Saal, Å. Borg, M. Fernö, C. Peterson and P.S. Meltzer
    Cancer Research 61, 5979-5984 (2001)
    [abs] [pdf]

    Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks
    J. Khan, J.S. Wei, M. Ringnér, L.H. Saal, M. Ladanyi, F. Westermann,
    F. Berthold, M. Schwab, C.R. Atonescu, C. Peterson and P.S. Meltzer
    Nature Medicine 7, 673-679 (2001) [cover article]
    [abs] [pdf] [supplement] [cover] [reviews]

Protein Folding/Design and Structure Alignment

    Matching protein structures with fuzzy alignments
    R. Blankenbecler, M. Ohlsson, C. Peterson and M. Ringnér
    Proceedings of the National Academy of Sciences USA 100, 11936-11940 (2003)
    [abs] [pdf] [supplement]

    Design of sequences with good folding properties in coarse-grained protein models
    A. Irbäck, C. Peterson, F. Potthast and E. Sandelin
    Structure with Folding & Design 7, 347-360 (1999)
    [abs] [pdf]

    Monte Carlo procedure for protein design
    A. Irbäck, C. Peterson, F. Potthast and E. Sandelin
    Physical Review E 58, R5249-R5252 (1998)
    [abs] [pdf]

    Local interactions and protein folding: a 3d off-lattice approach
    A. Irbäck, C. Peterson, F. Potthast and O. Sommelius
    Journal of Chemical Physics 107, 273-282 (1997)
    [abs] [pdf]

    Identification of amino acid sequences with good folding properties in an off-lattice model
    A. Irbäck, C. Peterson and F. Potthast
    Physical Review E 55, 860-867 (1997)
    [abs] [pdf]

    Evidence for non-random hydrophobicity structures in protein chains
    A. Irbäck, C. Peterson and F. Potthast
    Proceedings of the National Academy of Sciences, USA 93, 9533-9538 (1996)
    [abs] [pdf]

    Folding and design in coarse-grained protein models
    C. Peterson
    Proceedings of the XVIIth International Symposium on Lattice Field Theory, eds. M. Campostrini et al.,
    Nuclear Physics B (Proc. Suppl) 83-84, 712-714 (2000)
    [abs] [pdf]


Thermodynamics of Macromolecules

    The electrostatic persistence length calculated from Monte Carlo, variational and perturbation methods
    M. Ullner, B. Jönsson, C. Peterson, O. Sommelius and B. Söderberg
    Journal of Chemical Physics 107, 1279-1287 (1997)
    [abs] [pdf]

    Scaling and scale breaking in polyelectrolytes
    C. Peterson, O. Sommelius and B. Söderberg
    Journal of Chemical Physics 105, 5233-5241 (1996)
    [abs] [pdf]

    A blocking technique for emulating very large polyelectrolytes
    C. Peterson, O. Sommelius and B. Söderberg
    Physical Review Letters 76, 1079-1082 (1996)
    [abs] [pdf]

    A Monte Carlo study of titrating polyelectrolytes
    M. Ullner, B. Jönsson, B. Söderberg and C. Peterson
    Journal of Chemical Physics 104, 3048-3057 (1996)
    [abs] [pdf]

    Titrating polyelectrolytes - variational calculations and Monte Carlo simulations
    B. Jönsson, M. Ullner, C. Peterson, O. Sommelius and B. Söderberg
    Journal of Physical Chemistry 100, 409-417 (1996)
    [abs] [pdf]

    A variational approach for minimizing Lennard-Jones energies
    C. Peterson, O. Sommelius and B. Söderberg
    Physical Review E 53, 1725-1731 (1996)
    [abs] [pdf]

    A variational approach to the structure and thermodynamics of linear polyelectrolytes with Coulomb and screened Coulomb interactions
    B. Jönsson, C. Peterson and B. Söderberg
    Journal of Physical Chemistry 99, 1251-1266 (1995)
    [abs] [pdf]

    Variational approach to correlations in polymers
    B. Jönsson, C. Peterson and B. Söderberg
    Physical Review Letters 71, 376-379 (1993)
    [abs] [pdf]


Resource Allocation Algorithms

    An efficient mean field approach to the set covering problem
    M. Ohlsson, C. Peterson and B. Söderberg
    European Journal of Operations Research 133, 583-595 (2001)
    [abs] [pdf]

    Airline crew scheduling using Potts mean field techniques
    M. Lagerholm, C. Peterson and B.Söderberg
    European Journal of Operations Research 120, 81-96 (2000)
    [abs] [pdf]

    Local routing algorithms based on Potts neural networks
    J. Häkkinen, M. Lagerholm, C. Peterson and B. Söderberg
    IEEE Transactions on Neural Networks 11, 970-977 (2000)
    [abs] [pdf]

    A Potts neuron approach to communication routing
    J. Häkkinen, M. Lagerholm, C. Peterson and B. Söderberg
    Neural Computation 10, 1587-1599 (1998)
    [abs] [pdf]

    Statistical properties of unrestricted crew scheduling problems
    M. Lagerholm, C. Peterson and B.Söderberg
    LU TP 97-11
    [abs] [pdf]

    Airline crew scheduling with Potts neurons
    M. Lagerholm, C. Peterson and B. Söderberg
    Neural Computation 9, 1589-1599 (1997)
    [abs] [pdf]

    Neural networks for optimization problems with inequality constrains - the knapsack problem
    M. Ohlsson, C. Peterson and B. Söderberg
    Neural Computation 5, 331-339 (1993)
    [abs] [pdf]

    Solving optimization problems with mean field methods
    C. Peterson
    Physica A 200, 570-580 (1993)
    [abs] [pdf]

    Track finding with deformable templates - the elastic arms approach
    M. Ohlsson, C. Peterson and A. L. Yuille
    Computer Physics Communications 71, 77-98 (1992)
    [abs] [pdf]

    Rotor neurons - formalism and dynamics
    L. Gislén, C. Peterson and B. Söderberg
    Neural Computation 4, 737-745 (1992)
    [abs] [pdf]

    Complex scheduling with Potts neural networks
    L. Gislén, C. Peterson and B. Söderberg
    Neural Computation 4, 805-831 (1992)
    [abs] [pdf]

    Parallel distributed approaches to combinatorial optimization - benchmark studies on traveling salesman problem
    Carsten Peterson
    Neural Computation 2, 261-269 (1990)
    [abs] [pdf]

    Teachers and classes with neural networks
    L. Gislén, B. Söderberg and C. Peterson
    International Journal of Neural Systems 1, 167-176 (1989)
    [abs] [pdf]

    A new method for mapping optimization problems onto neural networks
    C. Peterson and B. Söderberg
    International Journal of Neural Systems 1, 3-22 (1989)
    [abs] [pdf]

    Track finding with neural networks
    C. Peterson
    Nuclear Instruments and Methods A279, 537-545 (1989)
    [abs] [pdf]

    Neural networks and NP-complete problems; a performance study of the graph bisectioning problem
    C. Peterson and J.R. Anderson
    Complex Systems 2, 59-89 (1989)
    [pdf]

    Neural optimization [substantially revised new version]
    C. Peterson and B. Söderberg
    The Handbook of Brain Theory and Neural Networks (2nd edition), pp. 822-27, ed. M.A. Arbib, Cambridge 2002: Bradford Books/The MIT Press
    [abs] [pdf]

    Artificial neural networks and combinatorial optimization problems
    C. Peterson and B. Söderberg
    Local Search in Combinatorial Optimization, pp. 173-214, eds. E.H.L. Aarts and J.K. Lenstra, New York 1997: John Wiley & Sons
    [pdf] [bibliography]

    Neural optimization
    C. Peterson and B. Söderberg
    The Handbook of Brain Research and Neural Networks, ed. M.A. Arbib, Cambridge 1995: MIT Press
    [postscript]

    Combinatorial optimization with neural networks
    C. Peterson and B. Söderberg
    Modern Heuristic Techniques for Combinatorial Problems, pp. 197-242, ed. C. Reeves, London 1992: Blackwell

    Combinatorial optimization with feedback artificial neural networks
    C. Peterson
    Proceedings of ICANN '95 International Conference on Artificial Neural Networks, October 1995, Paris, France , eds. F. Fogelman-Soulie and P. Gallinari, EC2 & Cie (Paris 1995)
    [abs] [pdf]


Computerized Interpretation of ECG Images

    Clustering ECG complexes using Hermite functions and self-organizing maps
    M. Lagerholm, C. Peterson, G. Braccini, L. Edenbrandt and L. Sörnmo
    IEEE Transactions on Biomedical Engineering 47, 838-848 (2000)
    [abs] [pdf]

    A confident decision support system for interpreting electrocardiograms
    H. Holst, M. Ohlsson, C. Peterson and L. Edenbrandt
    Clinical Physiology 19, 410-418 (1999)
    [abs] [pdf]

    Intelligent computer reporting "lack of experience": a confidence measure for decision support systems
    H. Holst, M. Ohlsson, C. Peterson and L. Edenbrandt
    Clinical Physiology 18, 139-148 (1998)
    [abs] [pdf]

    Automated interpretation of myocardial SPECT perfusion images using artificial neural networks
    D. Lindahl, J. Palmer, M. Ohlsson, C. Peterson, A. Lundin and L.Edenbrandt
    The Journal of Nuclear Medicine 38, 1870-1875 (1997)
    [abs] [pdf]

    Agreement between artificial neural networks and human expert for the electrocardiographic diagnosis of healed myocardial infarction
    B. Hedén, M. Ohlsson, R. Rittner, O. Pahlm, W.K. Haisty Jr., C. Peterson and L. Edenbrandt
    Journal of the American College of Cardiology 28, 1012-1016 (1996)
    [abs] [pdf]

    Detection of frequently occuring electrocardiographic lead reversals using artificial neural networks
    B. Hedén, M. Ohlsson, H. Holst, M. Mjöman, R. Rittner, O. Pahlm, C. Peterson and L. Edenbrandt
    American Journal of Cardiology 78, 600-604 (1996)
    [abs] [pdf]

    Artificial neural networks for recognition of electrocardiographic electrode misplacement
    B. Hedén, M. Ohlsson, L. Edenbrandt, R. Rittner, O. Pahlm and C. Peterson
    American Journal of Cardiology 75, 929-933 (1995)
    [abs] [pdf]


Machine Learning and Data Mining Algorithms

    Using hidden Markov models to characterize disease trajectories
    M. Ohlsson, C. Peterson and M. Dictor
    Proceedings of the Neural Networks and Expert Systems in Medicine and Healthcare Conference, 324-326 (2001), eds. G.M. Papadourakis
    [abs] [pdf]

    Determining dependency structures and estimating nonlinear regression errors without doing regression
    C. Peterson
    Proceedings of the Fourth International Workshop on Software Engineering and Artificial Intelligence for High Energy and Nuclear Physics, eds. B. Denby and D. Perret-Gallix, International Journal of Modern Physics 6, 611-616 (1995)
    [abs] [pdf]

    Estimating nonlinear regression errors without doing regression
    H. Pi and C. Peterson
    arXiv:1404.3219 [LU TP 94-19]
    [abs] [pdf]

    Predicting system loads with artificial neural networks - method and result from "the great energy predictor shootout"
    M. Ohlsson, C. Petersson, H. Pi, T. Rögnvaldsson and B. Söderberg
    1994 Annual Proceedings of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., 1063-1074 (1994)
    [abs][ pdf]

    Delta 2.0 - A program for finding dependencies in tables of data
    H. Pi and C. Peterson
    Computer Physics Communications 83, 293-306 (1994)
    [abs] [pdf]

    Finding the embedding dimension and variable dependences in time series
    H. Pi and C. Peterson
    Neural Computation 6, 509-520 (1994)
    [abs] [pdf]

    JETNET 3.0 - A versatile artificial neural network package
    L. Lönnblad, C. Peterson, and T. Rögnvaldsson
    Computer Physics Communications 81, 185-220 (1994)
    [pdf] [HTML manual]

    Mass reconstruction with a neural network
    L. Lönnblad, C. Peterson and T. Rögnvaldsson
    Physics Letters B 278, 181-186 (1992)
    [abs] [pdf]

    An introduction to artificial neural networks
    C. Peterson and T. Rögnvaldsson
    Proc. 1991 CERN Summer School of Computing, CERN Yellow Report 92-02, 113-170 (1992)
    [abs] [postscript] [pdf]

    Pattern recognition in high energy physics with artificial neural networks - JETNET 2.0
    L. Lönnblad, C. Peterson and T. Rögnvaldsson
    Computer Physics Communications 70, 167-182 (1992)
    [abs] [pdf]

    Self-organizing networks for extracting jet features
    L. Lönnblad, C. Peterson, H. Pi and T. Rögnvaldsson
    Computer Physics Communications 67, 193-209 (1991)
    [abs] [pdf]

    Using neural networks to identify jets
    L. Lönnblad, C. Peterson and T. Rögnvaldsson
    Nuclear Physics B 349, 675-702 (1991)
    [abs] [pdf]

    Neural networks as classifiers in subatomic physics
    C. Peterson
    Nuclear Physics News 2, 14-17 (1992)
    [pdf]

    Mean field theory neural networks for feature recognition, content addressable memory and optimization
    C. Peterson
    Connection Science 3, 3-33 (1991)
    [abs] [pdf]

    Finding gluon jets with a neural trigger
    L. Lönnblad, C. Peterson and T. Rögnvaldsson
    Physical Review Letters 65, 1321-1324 (1990)
    [abs] [pdf]

    An optoelectronic architecture for multilayer learning in a single photorefractive crystal
    C. Peterson, S. Redfield, J.D. Keeler and E. Hartman
    Neural Computation 2, 25-34 (1990)
    [abs] [pdf]

    Optoelectronic implementations of multi-layer neural networks in a single photorefractive crystal
    C. Peterson, S. Redfield, J.D. Keeler and E. Hartman
    Optical Engineering 29, 359-368 (1990)
    [abs]

    Explorations of the mean field theory learning algorithm
    E. Hartman and C. Peterson
    Neural Networks 2, 475-494 (1989)
    [abs] [pdf]

    A mean field theory learning algorithm for neural networks
    C. Peterson and J.R. Anderson
    Complex Systems 1, 995-1019 (1987)
    [abs] [pdf]


New Monte Carlo Algorithms

    The complex Langevin equation and Monte Carlo simulations of actions with static charges
    J. Ambjørn, M. Flensburg and C. Peterson
    Nuclear Physics B275 [FS17], 375-397 (1986)

    Langevin simulations of configurations with static charges
    J. Ambjørn, M. Flensburg and C. Peterson
    Physics Letters 159B, 335-340 (1985)

    Direct observation of string vibrations in compact QED
    C. Peterson and L. Sköld
    Nuclear Physics B255, 365-382 (1985)


Lattice Gauge Theories

    Compact U(1) in three dimensions reexamined
    A. Irbäck and C. Peterson
    Physical Review D36, 3804-3808 (1987)
    [abs] [pdf]

    The effective string and SU(2) lattice Monte Carlo data
    A. Irbäck, M. Flensburg and C. Peterson
    Zeitschrift f Physik C36, 629-637 (1987)
    [abs] [pdf]

    Finite size effects for lattice glueball masses
    T. DeGrand and C. Peterson
    Physical Review D34, 3180-3185 (1986)
    [abs] [pdf]

    Numerical evidence for a mass gap in (2+1) dimensional SU(2)
    A. Irbäck and C. Peterson
    Physics Letters 174B, 99-103 (1986)
    [abs] [pdf]

    Do results from lattice gauge theories distinguish between different fragmentation models?
    C. Peterson
    Physical Review D34, 1631-1633 (1986)
    [abs] [pdf]

    String model potentials and lattice gauge theories
    M. Flensburg and C. Peterson
    Nuclear Physics B283, 141-164 (1987)
    [abs] [pdf]

    Strings and SU(3) lattice gauge theory
    M. Flensburg and C. Peterson
    Physics Letters 153B, 412-416 (1985)
    [abs] [pdf]

    Three dimensional lattice gauge theory and strings
    J. Ambjørn, P. Olesen and C. Peterson
    Nuclear Physics B244, 262-276 (1984)
    [abs] [pdf]

    Observation of a string in three dimensional gauge theory
    J. Ambjørn, P. Olesen and C. Peterson
    Physics Letters 142B, 410-414 (1984)
    [abs] [pdf]

    Stochastic confinement and dimensional reduction (II). Three dimensional lattice gauge theory
    J. Ambjørn, P. Olesen and C. Peterson
    Nuclear Physics B240 [FS12], 533-542 (1984)
    [abs] [pdf]

    Stochastic confinement and dimensional reduction (I). Four dimensional lattice gauge theory
    J. Ambjørn, P. Olesen and C. Peterson
    Nuclear Physics B240 [FS12], 189-212 (1984)
    [abs] [pdf]

    The physics of the axial anomaly and the lattice Dirac sea
    J. Ambjørn, J. Greensite and C. Peterson
    Nuclear Physics B221, 381-408 (1983)
    [abs] [pdf]

    Hadronic production of glueballs
    C. Peterson
    Physics Letters 141B, 251-254 (1984)
    [abs] [pdf]


Bag Models

    Pseudoscalar density of states; evidence for valance glue
    C.E. Carlson and C. Peterson
    Physical Review Letters 55, 355-358 (1985)

    Glueball spectrum in the bag model and in lattice gauge theories
    C.E. Carlson. T.H. Hansson and C. Peterson
    Physical Review D30, 1594-1595 (1984)

    Applications of an improved bag model
    M. Flensburg. C. Peterson and L. Sköld
    Zeitschrift f. Physik C22, 293-300 (1984)

    Meson, baryon and glueball masses in the MIT bag model
    C.E. Carlson. T.H. Hansson and C. Peterson
    Physical Review D27, 1556-1564 (1983)

    Gluon-gluon interactions in the bag model
    C.E. Carlson. T.H. Hansson and C. Peterson
    Physical Review D27 2167-2181 (1983)

    Loop diagrams in boxes
    T.H. Hansson. K. Johnson and C. Peterson
    Physical Review D26, 415-428 (1982)


Quantum Chromodynamics

    Assessing QCD in deep inelastic electron-photon scattering
    C. Peterson, P. Zerwas and T.F. Walsh
    Nuclear Physics B229, 301-316 (1983)

    Scaling violations in inclusive e+e- annihilation spectra
    C. Peterson, D. Schlatter, P.M. Zerwas and I. Schmitt
    Physical Review D27, 105-111 (1983)

    The QCD vacuum as a glueball condensate
    T.H. Hansson. K. Johnson and C. Peterson
    Physical Review D26, 2069-2085 (1982)

    Intrinsic heavy quark states
    S.J. Brodsky. P. Hoyer. C. Peterson and N. Sakai
    Physical Review D23, 2745-2757 (1981)

    The intrinsic charm of the proton
    S.J. Brodsky. P. Hoyer. C. Peterson and N. Sakai
    Physics Letters 93B, 451-455 (1980)

    Deep inelastic electron-photon scattering
    C. Peterson, P. Zerwas and T.F. Walsh
    Nuclear Physics B174, 424-444 (1980)


Quark Fragmentation and Multiparticle Dynamics

    Model of a nonperturbative gluon jet
    C. Peterson and T.F. Walsh
    Physics Letters 91B, 455-458 (1980)

    Opposite side quantum number correlations in e+e- annihilation
    C. Peterson
    Zeitschrift f. Physik C3, 271-273 (1980)

    Hadron distributions in quark jets
    P. Hoyer. C.-H. Lai. J.L. Petersen and C. Peterson
    Nuclear Physics B151, 389-398 (1979)

    A semiclassical model for quark jet fragmentation
    B. Andersson. G. Gustafson and C. Peterson
    Zeitschrift f. Physik C1, 105-116 (1979)

    Implications of a large vector meson production on quark jet fragmentation and large pt reactions
    B. Andersson. G. Gustafson and C. Peterson
    Physica Scripta 18, 193-195 (1978)

    A statistical model for quark fragmentation distributions
    B. Andersson. G. Gustafson and C. Peterson
    Nuclear Physics B135, 273-284 (1978)

    A comparison of the quark parton model with data on electro-production of pions
    G. Gustafson and C. Peterson
    Lettere al Nuovo Cimento 21, 265-269 (1978)

    A quark parton model for hadron fragmentation distributions
    B. Andersson. G. Gustafson and C. Peterson
    Physics Letters 71B, 337-341 (1977)

    The relationship between the meson, baryon, photon and quark fragmentation distributions
    B. Andersson. G. Gustafson and C. Peterson
    Physics Letters 69B, 221-224 (1977)

    On the diffractive production of charmed baryons
    G. Gustafson and C. Peterson
    Physics Letters 67B, 81-83 (1977)

    Rescattering effects in the decay of A1
    G. Gustafson and C. Peterson
    Nuclear Physics B116, 301-316 (1976)
    [abs] [pdf]

    Evidence for a fixed J=0 pole in pion compton scattering
    C. Peterson
    Lettere al Nuovo Cimento 13, 460-462 (1976)

    High energy pN backward-scattering models and continous moment sum rules
    C. Peterson and L. Sollin
    Il Nuovo Cimento 26A, 1-15 (1975)