Lunin Vladimir Yur'evich

Publications in Math-Net.Ru

1. Determination of the structure of biological macromolecular particles using X-ray lasers. Achievements and prospects
   
   Mat. Biolog. Bioinform., 15:Suppl. (2020),  52–87
2. Mask-based approach in phasing and restoring of single-particle diffraction data
   
   Mat. Biolog. Bioinform., 15:Suppl. (2020),  1–20
3. Determination of the structure of biological macromolecular particles using X-ray lasers. Achievements and prospects
   
   Mat. Biolog. Bioinform., 15:2 (2020),  195–234
4. Mask-based approach in phasing and restoring of single-particle diffraction data
   
   Mat. Biolog. Bioinform., 15:1 (2020),  57–72
5. Single particle study by X-ray diffraction: crystallographic approach
   
   Mat. Biolog. Bioinform., 14:Suppl. (2019),  44–61
6. Single particle study by X-ray diffraction: crystallographic approach
   
   Mat. Biolog. Bioinform., 14:2 (2019),  500–516
7. The use of connected masks for reconstructing the single particle image from X-ray diffraction data. III. Maximum-likelihood based strategies to select solution of the phase problem
   
   Mat. Biolog. Bioinform., 13:Suppl. (2018),  70–83
8. The use of connected masks for reconstructing the single particle image from X-ray diffraction data. III. Maximum-likelihood based strategies to select solution of the phase problem
   
   Mat. Biolog. Bioinform., 12:2 (2017),  521–535
9. The biological crystallography without crystals
   
   Mat. Biolog. Bioinform., 12:1 (2017),  55–72
10. The use of connected masks for reconstructing the single particle image from X-ray diffraction data. II. The dependence of the accuracy of the solution on the sampling step of experimental data
    
    Mat. Biolog. Bioinform., 10:Suppl. (2015),  56–72
11. The use of connected masks for reconstructing the single particle image from X-ray diffraction data
    
    Mat. Biolog. Bioinform., 10:Suppl. (2015),  1–19
12. The use of connected masks for reconstructing the single particle image from X-ray diffraction data. II. The dependence of the accuracy of the solution on the sampling step of experimental data
    
    Mat. Biolog. Bioinform., 10:2 (2015),  508–525
13. The Use of Connected Masks for Reconstructing the Single Particle Image from X-Ray Diffraction Data
    
    Mat. Biolog. Bioinform., 9:2 (2014),  543–562
14. Computer Simulation of Diffraction of X-ray Pulses by Nanocrystals of Biological Macromolecules Using Unitary Approximation of Nonstationary Atomic Scattering Factors
    
    Mat. Biolog. Bioinform., 8:1 (2013),  93–118
15. The Use of Refmac Crystallographic Refinement Program for Detection of Alternative Conformations in Biological Macromolecules
    
    Mat. Biolog. Bioinform., 7:2 (2012),  692–702
16. The use of cluster analysis methods for the study of a set of feasible solutions of the phase problem in biological crystallography
    
    Computer Research and Modeling, 2:1 (2010),  91–101
17. Unrestrained reciprocal space refinement of macromolecular structures as a tool to indicate alternative conformations
    
    Mat. Biolog. Bioinform., 3:2 (2008),  50–59
18. Statistical modelling and likelihood-based choice in macromolecular crystallography
    
    Mat. Biolog. Bioinform., 1:1 (2006),  17–26
19. Regeneration of missing structural factors in the X-ray analysis of macromolecules
    
    Dokl. Akad. Nauk SSSR, 299:2 (1988),  363–366
20. The finiteness of the boundary layer in the solutions of certain classes of boundary value problems that contain a small parameter
    
    Uspekhi Mat. Nauk, 32:1(193) (1977),  171–172
21. Estimates of the solutions of abstract parabolic equations
    
    Uspekhi Mat. Nauk, 29:3(177) (1974),  213–214


22. To the memory of Èmmanuil Èl'evich Shnol'
    
    Uspekhi Mat. Nauk, 72:1(433) (2017),  197–208
23. Emmanuil El'evich Shnol' (on his 70th birthday)
    
    Uspekhi Mat. Nauk, 54:3(327) (1999),  199–204