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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 |
 |
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]
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]
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]
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]
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]
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)
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]
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)
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)
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)