Bridging the gap between the micro- and the macro-world of tumors
Source abstract
Abstract
At present it is still quite difficult to match the vast knowledge on the behavior of individual tumor cells with macroscopic measurements on clinical tumors. On the modeling side, we already know how to deal with many molecular pathways and cellular events, using systems of differential equations and other modeling tools, and ideally, we should be able to extend such a mathematical description up to the level of large tumor masses. An extended model should thus help us forecast the behavior of large tumors from our basic knowledge of microscopic processes. Unfortunately, the complexity of these processes makes it very difficult – probably impossible – to develop comprehensive analytical models. We try to bridge the gap with a simulation program which is based on basic biochemical and biophysical processes – thereby building an effective computational model – and in this paper we describe its structure, endeavoring to make the description sufficiently detailed and yet understandable.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Mathematical Biology Tumor Growth · Gene Regulatory Network Analysis · Microtubule and mitosis dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Università di Verona and I.N.F.N. – Sezione di Trieste 1 Dipartimento di Biotecnologie, , Strada Le Grazie 15 - CV1, I-37134 Verona, Italy
Dipartimento di Fisica dell’Università di Trieste and I.N.F.N. – Sezione di Trieste 2 , Via Valerio, 2 – I-34127 Trieste, Italy
References (40)
Show source-provided references
1. Nuclear Physics B (Proc. Suppl.) · 1989 · 6 · 710.1016/0920-5632(89)90401-5 ↗
2. 1944
3. Cell · 2000 · 100 · 5710.1016/S0092-8674(00)81683-9 ↗
4. Journal Theor Med · 2000 · 2 · 30710.1080/10273660008833057 ↗
5. Reports on Progress in Physics · 2009 · 72 · 05670110.1088/0034-4885/72/5/056701 ↗
6. Pharm Res · 2009 · 26 · 236910.1007/s11095-009-9958-3 ↗
7. Annu. Rev. Biomed. Eng. · 1999 · 1 · 46310.1146/annurev.bioeng.1.1.463 ↗
8. Molecular Therapy · 2010
9. Physica A: Statistical Mechanics and its Applications · 2004 · 338 · 26110.1016/j.physa.2004.02.049 ↗
10. Journal of Bioinformatics and Computational Biology · 2011 · 9 · 55910.1142/S0219720011005379 ↗
11. Science · 1988 · 240 · 17710.1126/science.2451290 ↗
12. PLoS One · 2010 · 5 · e1394210.1371/journal.pone.0013942 ↗
13. Computational Science & Engineering, IEEE · 1998 · 5 · 4610.1109/99.660313 ↗
14. Phys Biol · 2005 · 2 · 810.1088/1478-3967/2/1/002 ↗
15. Physical Biology · 2007 · 4 · 11410.1088/1478-3975/4/2/005 ↗
16. Current opinion in cell biology · 2000 · 12 · 50910.1016/S0955-0674(00)00124-1 ↗
17. Current Biology · 2001 · 11 · 64410.1016/S0960-9822(01)00177-4 ↗
18. CGAL, Computational Geometry Algorithms Library
19. 2008
20. 1992 · 7510.1145/147130.147153 ↗
21. 1999
22. Computer Physics Communications · 2009 · 180 · 216610.1016/j.cpc.2009.06.021 ↗
23. Future Generation Computer Systems · 2001 · 17 · 83510.1016/S0167-739X(00)00062-5 ↗
24. Biomed Microdevices · 2008 · 10 · 54710.1007/s10544-008-9164-9 ↗
25. Plant Physiol · 2001 · 126 · 112910.1104/pp.126.3.1129 ↗
26. Biophys J · 2005 · 88 · 6210.1529/biophysj.104.041459 ↗
27. J Biomech · 2000 · 33 · 2310.1016/S0021-9290(99)00163-3 ↗
28. Biophys J · 1984 · 45 · 105110.1016/S0006-3495(84)84252-6 ↗
29. American scientist · 1997 · 85 · 456
30. Reviews of Physiology, Biochemistry and Pharmacology · 2003 · 110.1007/978-3-540-44834-1 ↗
31. Cell death and differentiation · 2002 · 9 · 130710.1038/sj.cdd.4401126 ↗
32. Physical Review E · 2000 · 62 · 214010.1103/PhysRevE.62.2140 ↗
33. Journal of molecular modeling · 2002 · 8 · 3310.1007/s00894-001-0068-3 ↗
34. 2010
35. ParaView
36. Applied physics letters · 2003 · 83 · 57510.1063/1.1594830 ↗
37. Applied optics · 2004 · 43 · 486210.1364/AO.43.004862 ↗
38. Journal of Laboratory Automation · 2011
39. Nature biotechnology · 2007 · 25 · 123910.1038/nbt1356 ↗
40. Nature biotechnology · 2008 · 26 · 73710.1038/nbt0708-737 ↗