Publications

(Computational) Algorithms for Biological Problems

• Clustering techniques

  C.-P. Chen, H. Fushing, R. Atwill, and P. Koehl biDCG: A new method for discovering global features of DNA microarray data via an iterative re-clustering procedure PLoS One, 9:e102445, 2014. [ bib ]

  H. Fushing, C. Chen, S.H. Liu, and P. Koehl Bootstrapping on undirected binary networks via statistical mechanics J. Stat. Phys. 156:853-862, 2014. [ bib ]

  H. Fushing, H. Wang, K. VanderWaal, B. McCowan, and P. Koehl. Multi-scale clustering by building a robust and self correcting ultrametric topology on data points. PLoS One, 8:e56259, 2013. [ bib ]

• Partial differential equations

  P. Koehl and M. Delarue. AQUASOL: an efficient solver for the dipolar Poisson-Boltzmann-Langevin equation. J. Chem. Phys., 132:064101, 2010. [ bib ]

  X. Shi and P. Koehl. Adaptive skin meshes coarsening for biomolecular simulation. Comput. Aided Graph. Design, 28:307-320, 2011. [ bib ]

  X. Shi and P. Koehl. Adaptive surface meshes coarsening with guaranteed quality and topology. In Proc. Comput. Graphics Inter. Conf., pages 53-61, 2009. [ bib ]

  X. Shi and P. Koehl. The geometry behind numerical solvers of the Poisson-Boltzmann equation. Commun. Comput. Phys., 3:1032-1050, 2008. [ bib ]

• Bioinformatics: protein structures

  M. Carlsen, P. Koehl, and P. Røgen. On the importance of the distance measures used to train and test knowledge-based potentials for proteins PLoS One, (2014: in press). [ bib ]

  P. Koehl and P. Røgen. Extracting knowledge from protein structure geometry. Proteins: Struct. Func. Bioinfo., 81:841-851, 2013. [ bib ]

  E. Kang and P. Koehl. Identifying alpha-helices in proteins using the contact map and morphological operations. J. Korean Inst. Next Gen. Comput., 8:75-86, 2012. [ bib ]

  P. Francis-Lyon, S. Gu, J. Hass, N. Amenta, and P. Koehl. Sampling the conformation of protein surface residues for flexible protein docking. BMC Bioinformatics, 11:575, 2010. [ bib ]

  C. Hu and P. Koehl. Helix-sheet packing in proteins. Proteins: Struct. Func. Bioinfo., 78:1736-1747, 2010. [ bib ]

  Q. Le, G. Pollastri, and P. Koehl. Structural alphabets for protein structure classification: a comparison study. JMB, 387:431-450, 2008. [ bib ]

  P. Koehl. Protein structure classification. Rev. Comput. Chem., 22:1-56, 2006. [ bib ]

  R. Kolodny, P. Koehl, and M. Levitt. Comprehensive evaluation of protein structure alignment methods: Scoring by geometric measures. J. Mol. Biol., 346:1173-1188, 2005. [ bib ]

  J. M. Chandonia, N. S. Walker, L. L. Conte, P. Koehl, M. Levitt, and S. E. Brenner. Astral compendium enhancements. Nucl. Acids. Res., 32:D189-D192, 2004. [ bib ]

  R. Kolodny, P. Koehl, L. Guibas, and M. Levitt. Small libraries of protein fragments model native protein structures accurately. J. Mol. Biol., 323:297-307, 2002. [ bib ]

  J. M. Chandonia, N. S. Walker, L. L. Conte, P. Koehl, M. Levitt, and S. E. Brenner. Astral compendium enhancements. Nucl. Acids. Res., 30:260-263, 2002. [ bib ]

  P. Koehl. Protein structure similarities. Curr. Opin. Struct. Biol., 11:348-353, 2001. [ bib ]

  S. E. Brenner, P. Koehl, and M. Levitt. The Astral compendium for protein structure and sequence analysis. Nucl. Acids. Res., 28:254-256, 2000. [ bib ]

  E. Furuichi and P. Koehl. Influence of protein structure database on the predictive power of statistical pair potentials. Proteins: Struct. Func. Genet., 31:139-149, 1998. [ bib ]

• Bioinformatics: Protein sequences

  J. Li and P. Koehl 3D representations of amino acids - applications to protein sequence comparison and classification Comp. Struct. Biotech. J., (2014: in press). [ bib ]

  S. Gu, O. Poch, B. Hamann, and P. Koehl. A geometric representation of protein sequences. In IEEE International Conf. Biol. Medicine, pages 135-142, 2007. [ bib ]

  J. D. Thompson, P. Koehl, R. Ripp, and O. Poch. BAliBASE 3.0: latest developments of the multiple sequence alignment benchmark. Proteins: Struct. Func. Genet., 61:127-136, 2005. [ bib ]

  J. D. Thompson, S. R. Holbrook, K. Katoh, P. Koehl, D. Moras, E. Westhof, and O. Poch. MAO: a multiple alignment ontology for nucleic acid and protein sequences. Nucl. Acids. Res., 33:4164-4171, 2005. [ bib ]

• NMR method development

  P. Koehl. Linear prediction spectral analysis of NMR data. Progress in NMR spectroscopy, 34:257-299, 1999. [ bib ]

  P. Koehl, C. Ling, and J. F. Lefèvre. Automatic phase correction of NMR spectra: statistics and limits. J. Chim. Phys., 92:1929-1938, 1995. [ bib ]

  P. Koehl and J. F. Lefèvre. Relaxation matrix refinement: Nucleic acids. In D. M. Grant and R. K. Harris, editors, Encyclopedia of Nuclear Magnetic Resonance. Wiley, Chichester, England, 1995. [ bib ]

  P. Koehl, C. Ling, and J. F. Lefèvre. Oversampling improves linear prediction quantification of magnetic resonance spectral parameters. J. Chim. Phys., 91:595-606, 1994. [ bib ]

  P. Koehl, C. Ling, and J. F. Lefèvre. Linear prediction quantification of magnetic resonance spectral parameters: statistics and limits. J. Magn. Reson., A109:32-40, 1994. [ bib ]

  P. Koehl, B. Kieffer, and J. F. Lefèvre. Computer-assisted assignment of biological macromolecule NMR spectra. J. Chim. Phys., 89:135-146, 1992. [ bib ]

  P. Koehl, J. F. Lefèvre, and O. Jardetzky. Computing the geometry of a molecule in dihedral angle space using NMR-derived constraints: a new algorithm based on optimal filtering. J. Mol. Biol., 223:299-315, 1992. [ bib ]

  P. Koehl and J. F. Lefèvre. The relaxation matrix reconstructed from an incomplete set of 2D-NOE data: Statistics and limits. Bull. Magn. Reson., 12:23-29, 1990. [ bib ]

  P. Koehl and J. F. Lefèvre. The reconstruction of the relaxation matrix from an incomplete set of nuclear Overhauser effects. J. Magn. Reson., 87:565-583, 1990. [ bib ]

(Computational) Geometry of Biological Systems

• The geometry of shapes

  P. Koehl and J. Hass. Automatic alignment of genus-zero surfaces. IEEE Trans. Pattern Anal. Mach. Intell., 36:466-478, 2014. [ bib ]

  P. Koehl. Mathematics's role in the grand challenge of deciphering the molecular basis of life. Frontiers in biomolecular sciences, (in press, 2014). [ bib ]

  A. Tsui, D. Fenton, P. Vuong, J. Hass, P. Koehl, N. Amenta, D. Coeurjolly, C. DeCarli, and O. T. Carmichael. Globally optimal cortical surface matching with exact landmark correspondence. In Proc. Information Processing in Medical Imaging, IPMI 2013, pages 487-498, 2013. [ bib ]

  P. Koehl. Fast recursive computation of 3D geometric moments from surface meshes. IEEE Trans. Pattern Anal. Mach. Intell., 34:2158-2163, 2012. [ bib ]

  S. Gu, P. Koehl, J. Hass, and N. Amenta. Surface-histogram: A new shape descriptor for protein-protein docking. Proteins: Struct. Func. Bioinfo., 80:221-238, 2012. [ bib ]

• Geometry and topology of biomolecules

  J. Li, P. Mach, and P. Koehl. Measuring the shapes of macromolecules and why it matters. Comp. Struct. Biotech. J., (in press, 2013). [ bib ]

  P. Mach and P. Koehl. An analytical method for computing atomic contact areas in biomolecules. J. Comp. Chem., 34:105-120, 2012. [ bib ]

  P. Mach and P. Koehl. Geometric measures of large biomolecules: Surface, volume, and pockets. J. Comp. Chem., 32:3023-3038, 2011. [ bib ]

  X. Shi and P. Koehl. Geometry and topology for modeling biomolecular surfaces. Far East J. Applied Math., 50:1-34, 2011. [ bib ]

  V. Natarajan, P. Koehl, Y. Wang, and B. Hamann. Visual analysis of biomolecular surfaces. In Visualization in Medicine and Life Sciences, pages 237-255, 2008. [ bib ]

  A. Zomorodian, L. Guibas, and P. Koehl. Geometric filtering of pairwise atomic interactions applied to the design of efficient statistical potentials. Comput. Aided Graph. Design, 23:531-544, 2006. [ bib ]

  H. Edelsbrunner and P. Koehl. The geometry of biomolecular solvation. MSRI Publications, 52:243-275, 2005. [ bib ]

  R. Bryant, H. Edelsbrunner, P. Koehl, and M. Levitt. The weighted area derivative of a space filling diagram. Discrete Comput. Geom., 32:293-308, 2004. [ bib ]

  H. Edelsbrunner and P. Koehl. The weighted volume derivative of a space filling diagram. Proc. Natl. Acad. Sci. (USA), 100:2203-2208, 2003. [ bib ]

(Computational) Physics of Biological Systems

• Solvation (Electrostatics)

  P. Koehl, F. Poitevin, H. Orland, and M. Delarue. Modified Poisson Boltzmann equations for characterizing biomolecular solvation. J. Theo. Comp. Chem., page 1440001, 2014. [ bib ]

  L. Sauguet, F. Poitevin, S. Murail, G. Moraga, C. van Renterghem, A. W. Thompson, P. Koehl, P. J. Corringer, M. Baaden, and M. Delarue. Structural basis for ion permeation mechanism in pentameric ligand-gated ion channels. EMBO J., 32:728-741, 2013. [ bib ]

  M. R. Smaoui, F. Poitevin, M. Delarue, P. Koehl, H. Orland, and J. Waldispühl. Computational assembly of polymorphic amyloid fibrils reveals stable aggregates. Biophys. J., 104:683-693, 2013. [ bib ]

  L. Miao, H. Qin, P. Koehl, and J. Song. Selective and specific ion binding on proteins at physiologically-relevant concentrations. FEBS Lett., 585:3126-3132, 2011. [ bib ]

  P. Koehl, H. Orland, and M. Delarue. Adapting Poisson-Boltzmann to the self-consistent mean field theory: Application to protein side-chain modeling. J. Chem. Phys., 135:055104, 2011. [ bib ]

  F. Poitevin, H. Orland, S. Doniach, P. Koehl, and M. Delarue. AquaSAXS: A web server for computation and fitting of SAXS profiles with a non-uniform hydration layer. Nucl. Acids. Res., 39:W184-W189, 2011. [ bib ]

  P. Koehl, H. Orland, and M. Delarue. Computing ion solvation free energies using the dipolar Poisson model. J. Phys. Chem. B., 113:5694-5697, 2009. [ bib ]

  P. Koehl, H. Orland, and M. Delarue. Beyond Poisson-Boltzmann: Modeling biomolecule-water and water-water interactions. Phys. Rev. Let., 102:087801, 2009. [ bib ]

  P. Koehl, H. Orland, and M. Delarue. Solvation of ion pairs: The Poisson-Langevin model. In Proc. International Conf. Applied Phys. Math., pages 917-923, 2009. [ bib ]

  A. Azuara, H. Orland, M. Bon, P. Koehl, and M. Delarue. Incorporating dipolar solvents with variable density in Poisson-Boltzmann electrostatics. Biophys. J., 95:5587-5605, 2008. [ bib ]

  C. Azuara, E. Lindahl, P. Koehl, H. Orland, and M. Delarue. PDB_Hydro. incorporating dipolar solvents with variable density in the Poisson-Boltzmann treatment of macromolecule electrostatics. Nucl. Acids. Res., 34:W38-W42, 2006. [ bib ]

  P. Koehl. Electrostatics calculations: latest methodological advances. Curr. Opin. Struct. Biol., 16:142-151, 2006. [ bib ]

  M. Delarue and P. Koehl. Atomic environment energies in proteins defined from statistics of accessible and contact surface areas. J. Mol. Biol., 249:675-690, 1995. [ bib ]

  P. Koehl and M. Delarue. Polar and non-polar atomic environments in the protein core: implications for folding and binding. Proteins: Struct. Func. Genet., 20:264-278, 1994. [ bib ]

• Dynamics

  V. Weinreb, L. Li, S.N. Chandrasekaran, P. Koehl, M. Delarue, and C.W. Carter. Domain motion sensed by the d1 switch, a remote dynamic packing motif. J. Biol. Chem., 289:4367-4376, 2014. [ bib ]

  D. R. Weiss and P. Koehl. Morphing methods to visualize coarse-grained protein dynamics. Methods Mol. Biol., 1084, 2014. [ bib ]

  F. Xei, D. Tong, W. Lifeng, H. Dayong, C.H. Steven, P. Koehl, and L. Lu. Identifying essential pairwise interactions in elastic network model using the alpha shape theory. J. Comp. Chem., (in press, 2014). [ bib ]

  P. Laowanapiban, M. Kapustina, C. Vonrhein, M. Delarue, P. Koehl, and C. W. Carter Jr. Independent saturation of three TrpRS subsites generates a partially assembled state similar to those observed in molecular simulations. Proc. Natl. Acad. Sci. (USA), 106:1790-1795, 2009. [ bib ]

  P. Koehl. Molecular force fields. In S. Park and J. Cochran, editors, Protein engineering and design, pages 255-277. CRC Press, Boca Raton, Fl, 2009. [ bib ]

  J. Franklin, P. Koehl, S. Doniach, and M. Delarue. Minactionpath: maximum likelihood trajectory for large-scale structural transitions in a coarse grained locally harmonic energy landscape. Nucl. Acids. Res., 35:V477-W482, 2007. [ bib ]

  E. Lindahl, C. Azuara, P. Koehl, and M. Delarue. NORMAnDRef: visualization, deformation, and refinement of macromolecular structures based on all-atom normal mode analysis. Nucl. Acids. Res., 34:W52-W56, 2006. [ bib ]

  P. Agarwal, L. Guibas, H. Edelsbrunner, J. Erickson, M. Isard, S. Har-Paled, J. Hershberger, C. Jensen, L. Kavraki, P. Koehl, M. Lin, D. Manocha, D. Metaxas, B. Mirtich, D. Mount, S. Muthukrishnan, D. Pai, E. Sacks, J. Snoeyink, S. Suri, and O. Wolfson. Algorithmic issues in modeling motion. ACM Computing surveys, 34:550-572, 2002. [ bib ]

  P. Rabier, B. Kieffer, P. Koehl, and J. F. Lefèvre. Fast measurements of heteronuclear relaxation: frequency domain analysis of NMR accordion spectroscopy. Mag. Res. Chem., 39:447-456, 2001. [ bib ]

  S. Sunada, N. Go, and P. Koehl. Calculation of NMR order parameters in proteins by normal mode analysis. J. Chem. Phys., 104:4768-4775, 1996. [ bib ]

  B. Kieffer, P. Koehl, and J. F. Lefèvre. Modeling the dynamic of an antigenic peptide using NMR data. Biochimie, 74:815-824, 1992. [ bib ]

• Protein structure prediction

  P. Francis-Lyon and P. Koehl. Protein side-chain modeling with a protein-dependent optimized rotamer library. Proteins: Struct. Func. Bioinfo., (in press, 2014). [ bib ]

  E. DiLuccio and P. Koehl. The H-factor as a novel quality metric for homology modeling. J. Clin. Bioinfo, 2:18-26, 2012. [ bib ]

  C. Hu, P. Koehl, and N. Max. PackHelix: A tool for helix-sheet packing during protein structure prediction. Proteins: Struct. Func. Bioinfo., 78:2828-2843, 2011. [ bib ]

  E. DiLuccio and P. Koehl. A quality metric for homology modeling: the H-factor. BMC Bioinformatics, 12:48, 2011. [ bib ]

  P. Koehl. Protein structure prediction. In T. Jue, editor, Biomolecular applications of Biophysics, pages 1-34. Humana press, New York, NY, 2010. [ bib ]

  R. Kolodny, L. Guibas, M. Levitt, and P. Koehl. Inverse kinematics in biology: the protein loop closure problem. Int. J. Robot. Res., 24:151-163, 2005. [ bib ]

  R. Samudrala, E. S. Huang, P. Koehl, and M. Levitt. Constructing side-chains on near native main chains for ab initio protein structure prediction. Prot. Eng., 13:453-457, 2000. [ bib ]

  P. Koehl and M. Levitt. A brighter future for protein structure prediction. Nature Struct. Biol., 6:108-111, 1999. [ bib ]

  P. Koehl and M. Levitt. Theory and simulation: Can theory challenge experiment? Curr. Opin. Struct. Biol., 9:155-156, 1999. [ bib ]

  E. S. Huang, P. Koehl, M. Levitt, R. V. Pappu, and J. W. Ponder. Accuracy of side-chain prediction upon near-native protein backbones generated by ab-initio folding methods. Proteins: Struct. Func. Genet., 33:204-217, 1998. [ bib ]

  P. Koehl and M. Delarue. Building protein lattice models using self consistent mean field theory. J. Chem. Phys., 108:9540-9549, 1998. [ bib ]

  P. Koehl and M. Delarue. Mean field minimization methods for biological macromolecules. Curr. Opin. Struct. Biol., 2:222-226, 1996. [ bib ]

  P. Koehl and M. Delarue. A self consistent mean field approach to simultaneous gap closure and side-chain positioning in homology modeling. Nature Struct. Biol., 2:163-170, 1995. [ bib ]

  P. Koehl and M. Delarue. Modeling side-chain conformation in proteins: a self consistent mean field approach. In M. Geisow and R. Epton, editors, Protein Engineering and Complementary Technologies, pages 31-34. Mayflower Worldwide Ltd, Birmingham, England, 1995. [ bib ]

  P. Koehl and M. Delarue. Application of a self-consistent mean field theory to predict protein side-chains conformation and estimate their conformational entropy. J. Mol. Biol., 239:249-275, 1994. [ bib ]

• Protein Sequence Design

  P. Mach and P. Koehl. Capturing protein sequence-structure specificity using computational sequence design. Proteins: Struct. Func. Bioinfo., 81, 1556-1570, 2013. [ bib ]

  P. Koehl and M. Levitt. Sequence variations within protein families are linearly related to structural variations. J. Mol. Biol., 323:551-562, 2002. [ bib ]

  P. Koehl and M. Levitt. Protein topology and stability define the space of allowed sequences. Proc. Natl. Acad. Sci. (USA), 99:1280-1285, 2002. [ bib ]

  P. Koehl and M. Levitt. Improved recognition of native-like protein structures using a family of designed sequences. Proc. Natl. Acad. Sci. (USA), 99:691-696, 2002. [ bib ]

  P. Koehl. Recent progress in computational protein design. In M. Gromiha and S. Selvaraj, editors, Protein folding, stability, and design, pages 307-324. Research Signpost, Trivvendrum, India, 2002. [ bib ]

  P. Koehl and M. Levitt. De novo protein design. In O. Jardetzky and M. D. Finucane, editors, NATO ASI Series vol. 315, pages 57-75. Plenum press, New York, NY, 2001. [ bib ]

  P. Koehl and M. Levitt. De novo protein design. I. in search of stability and specificity. J. Mol. Biol., 293:1161-1181, 1999. [ bib ]

  P. Koehl and M. Levitt. De novo protein design. II. plasticity of protein sequences. J. Mol. Biol., 293:1182-1193, 1999. [ bib ]

  P. Koehl and M. Levitt. Structure-based conformational preferences of amino acids. Proc. Natl. Acad. Sci. (USA), 96:12524-12529, 1999. [ bib ]

  P. Koehl and M. Delarue. The native sequence determines sidechain packing in a protein, but does optimal sidechain packing determine the native sequence? In Proc. Pacific Symp. Biocomputing, pages 198-209, 1997. [ bib ]

  M. Delarue and P. Koehl. The inverse protein folding problem: self consistent mean field optimization of a structure specific mutation matrix. In Proc. Pacific Symp. Biocomputing, pages 109-121, 1997. [ bib ]

High-resolution protein structures: X-ray crystallography and NMR spectroscopy

B. Babakasal, D. D. Gae, J. Li, J. C. Lagarias, P. Koeh l and A. J. Fisher. His74 conservation in the bilin reductase PcyA family reflects an important role in protein-substrate structure and dynamics. Biochim. Biophys. Acta, 537: 233-242, 2013. [ bib ]

F. Chalmel, T. Leveillard, C. Jaillard, A. Lardenois, N. Berdugo, E. Morel, P. Koehl, G. Lambrou, A. Holmgren, J. A. Sahel, and O. Poch. Rod-derived cone viability factor-2 is a novel bifunctional thioredoxin like protein with therapeutic potential. BMC Molec. Biol., 8:74-85, 2007. [ bib ]

L. McHale, X. Tan, P. Koehl, and R. Michelmore. Plant NBS-LRR proteins: adaptable guards. Genome Biology, 7:212, 2006. [ bib ]

P. Koehl. Relaxed specificity in aromatic prenyltransferases. Nature Chem. Biol., 1:71-72, 2005. [ bib ]

C. Birck, L. Damian, C. Marty-Detraves, A. Lougarre, C. Shulze Briese, P. Koehl, A. Fournie, L. Paquereau, and J. P. Samama. A new lectin family with structure similarity to actinoporins revealed by the crystal structure of Xerocomus chrysenteron lectin XCL. J. Mol. Biol., 344:1409-1420, 2004. [ bib ]

J. E. Wedeking, C. B. Trame, M. Dorywalska, P. Koehl, T. M. Rasche, M. McKee, D. Fitzgerald, R. J. Collier, and D. B. McKay. Refined crystallographic structure of pseudomonas aeruginosa exotoxin a and its implications for the molecular mechanism of toxicity. J. Mol. Biol., 314:823-837, 2001. [ bib ]

G. Mer, C. Kellenberger, P. Koehl, R. Stote, O. Sorokine, A. Van Dorsselaer, B. Luu, H. Hietter, and J. F. Lefèvre. Disulphide bridge pairing and solution structure by 1H NMR of PMPD2, a 35 residue peptide isolated from Locusta migratoria. Biochemistry, 33:15397-15409, 1994. [ bib ]

G. Mohn, P. Koehl, H. Budzikiewicz, and J. F. Lefèvre. Solution structure of pyoverdin GM-II. Biochemistry, 33:2843-2851, 1994. [ bib ]

B. Bersch, P. Koehl, Y. Nakatani, G. Ourisson, and A. Milon. 1H nuclear magnetic resonance determination of the membrane-bound conformation of senktide, a highly selective neurokinin B agonist. J. Biol. NMR, 3:91-112, 1993. [ bib ]

B. Kieffer, P. Koehl, S. Plaue, and J. F. Lefèvre. Structural and dynamic studies of two antigenic loops from haemagglutinin: a relaxation matrix approach. J. Biol. NMR, 3:91-112, 1993. [ bib ]

P. Koehl, B. Kieffer, and J. F. Lefèvre. The dynamics of oligonucleotides and peptides determined by proton NMR. In O. Jardetzky, editor, NATO ASI Series vol. 183, pages 139-154. Plenum press, New York, NY, 1990. [ bib ]

Others

• Mutagenesis studies

  P. Koehl, D. Burnouf, and R. P. P. Fuchs. Mutagenesis induced by a single acetylaminofluorene adduct within the nari site is position dependent. In P. C. Howard, S. S. Hecht, and F. A. Beland, editors, Nitroarenes: Occurrence, Metabolism and Biological Impact, pages 105-112. Plenum Press, New York, NY, 1991. [ bib ]

  D. Burnouf, P. Koehl, and R. P. P. Fuchs. Position of a single acetylaminofluorene adduct within a mutational hot spot is critical for the related mutagenic event. In Y. Kuroda, D. M. Shankel, and M. D. Waters, editors, Antimutagenesis and Anticarcinogenesis Mechanisms II, pages 277-288. Plenum Press, New York, NY, 1990. [ bib ]

  P. Koehl, P. Valladier, J. F. Lefèvre, and R. P. P. Fuchs. Strong structural effect of the position of a single acetylaminofluorene adduct within a mutation hot spot. Nucl. Acids. Res., 17:9531-9541, 1989. [ bib ]

  D. Burnouf, P. Koehl, and R. P. P. Fuchs. Single adduct mutagenesis : Strong effect of the position of a single acetylaminofluorene adduct within a mutation hot spot. Proc. Natl. Acad. Sci. (USA), 86:4147-4151, 1989. [ bib ]

  P. Koehl, D. Burnouf, and R. P. P. Fuchs. Construction of plasmids containing a unique acetylaminofluorene adduct located within a mutation hot spot: A new probe for frameshift mutagenesis. J. Mol. Biol., 207:355-364, 1989. [ bib ]

• Effects of radiation on DNA

  A. Chatterjee, P. Koehl, and J. L. Magee. Theoretical consideration of the chemical pathways for radiation-induced strand breaks. Adv. Space Res., 6:97-105, 1986. [ bib ]