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


Functional Genomics and Systems Biology

    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]

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    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] [postscript]

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

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

    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] [postscript]

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

    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] [postscript]

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

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

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

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

    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] [postscript]

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

    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), 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, eds. E.H.L. Aarts and J.K. Lenstra, New York 1997: John Wiley & Sons

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

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

    Combinatorial optimization with neural networks
    C. Peterson and B. Söderberg
    Modern Heuristic Techniques for Combinatorial Problems, 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] [postscript]


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]


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][ ps]

    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)
    [postscript, html]

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

    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)

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

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

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

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

    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


Bag Models


Quantum Chromodynamics

Quark Fragmentation and Multiparticle Dynamics