Register      Login
Reproduction, Fertility and Development Reproduction, Fertility and Development Society
Vertebrate reproductive science and technology
RESEARCH FRONT

Computational modelling of maternal interactions with spermatozoa: potentials and prospects

Mark Burkitt A B , Dawn Walker A , Daniela M. Romano A and Alireza Fazeli B C
+ Author Affiliations
- Author Affiliations

A The Department of Computer Science, University of Sheffield, Sheffield, Regent Court, 211 Portobello, Sheffield S1 4DP, UK.

B Academic Unit of Reproductive and Developmental Medicine, Department of Human Metabolism, The Medical School, University of Sheffield, Level 4, The Jessop Wing, Tree Root Walk, Sheffield S10 2SF, UK.

C Corresponding author. Email: a.fazeli@sheffield.ac.uk

Reproduction, Fertility and Development 23(8) 976-989 https://doi.org/10.1071/RD11032
Submitted: 4 February 2011  Accepted: 12 July 2011   Published: 12 October 2011

Abstract

Understanding the complex interactions between gametes, embryos and the maternal tract is required knowledge for combating infertility and developing new methods of contraception. Here we present some main aspects of spermatozoa interactions with the mammalian oviduct before fertilisation and discuss how computational modelling can be used as an invaluable aid to experimental investigation in this field. A complete predictive computational model of gamete and embryo interactions with the female reproductive tract is a long way off. However, the enormity of this task should not discourage us from working towards it. Computational modelling allows us to investigate aspects of maternal communication with gametes and embryos, which are financially, ethically or practically difficult to look at experimentally. In silico models of maternal communication with gametes and embryos can be used as tools to complement in vivo experiments, in the same way as in vitro and in situ models.

Additional keywords: 3D, agent, oviduct, simulation.


References

Aggarwal, K., and Lee, K. H. (2003). Functional genomics and proteomics as a foundation for systems biology. Brief. Funct. Genomics Proteomics 2, 175–184.
Functional genomics and proteomics as a foundation for systems biology.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXivFWntQ%3D%3D&md5=48295a82f56674dd4560a00789f7ea84CAS |

Attur, M. G., Dave, M. N., Tsunoyama, K., Akamatsu, M., Kobori, M., Miki, J., Abramson, S. B., Katoh, M., and Amin, A. R. (2002). “A system biology” approach to bioinformatics and functional genomics in complex human diseases: arthritis. Curr. Issues Mol. Biol. 4, 129–146.
| 1:CAS:528:DC%2BD38XovFKgsLs%3D&md5=c4bdede6f16c3ed79a534c7c9c3a9eaaCAS | 12432964PubMed |

Bahat, A., Tur-Kaspa, I., Gakamsky, A., Giojalas, L. C., Breitbart, H., and Eisenbach, M. (2003). Thermotaxis of mammalian sperm cells: a potential navigation mechanism in the female genital tract. Nat. Med. 9, 149–150.
Thermotaxis of mammalian sperm cells: a potential navigation mechanism in the female genital tract.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXotlSjsA%3D%3D&md5=20107837b6c38a4325a035516098b897CAS | 12563318PubMed |

Bathe, K.-J. (2007). Finite element method. In ‘Wiley Encyclopedia of Computer Science and Engineering’. (Ed. B. Wah.) pp. 1–12. (John Wiley & Sons, Inc.: Hoboken, NJ.)

Battalia, D. E., and Yanagimachi, R. (1979). Enhanced and co-ordinated movement of the hamster oviduct during the periovulatory period. J. Reprod. Fertil. 56, 515–520.
Enhanced and co-ordinated movement of the hamster oviduct during the periovulatory period.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaL3c%2FgvV2qsA%3D%3D&md5=1eae51b20625fdb682e39b6eb7555fbeCAS | 573324PubMed |

Bonabeau, E. (2002). Agent-based modeling: methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. USA 99, 7280–7287.
Agent-based modeling: methods and techniques for simulating human systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XjvVynsrc%3D&md5=54665d61f13563b87557f595d7286072CAS | 12011407PubMed |

Bottino, D., Mogilner, A., Roberts, T., Stewart, M., and Oster, G. (2002). How nematode sperm crawl. J. Cell Sci. 115, 367–384.
| 1:CAS:528:DC%2BD38Xht1CmsL4%3D&md5=fb8e3a3666e97f45c10fc7c65e19bc71CAS | 11839788PubMed |

Box, G., and Draper, N. (1986). ‘Empirical Model-building and Response Surface.’ (John Wiley & Sons, Inc.: New York, NY.)

Brokaw, C. (2001). Simulating the effects of fluid viscosity on the behaviour of sperm flagella. Math. Methods Appl. Sci. 24, 1351–1365.
Simulating the effects of fluid viscosity on the behaviour of sperm flagella.Crossref | GoogleScholarGoogle Scholar |

Brokaw, C. J., and Luck, D. J. L. (1983). Bending patterns of chlamydomonas flagella I. Wild-type bending patterns. Cell Motil. Cytoskeleton 3, 131–150.
Bending patterns of chlamydomonas flagella I. Wild-type bending patterns.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaL3s3osFWrsw%3D%3D&md5=c48f26d11b3c502326e2b9fe5bb38305CAS |

Burkitt, M., Romano, D. M., Walker, D., and Fazeli, A. (2010a). 3D modelling of complex biological structures: the oviduct. In ‘EG UK Theory and Practice of Computer Graphics’. pp. 255–262. (University of Sheffield: UK.)

Burkitt, M., Walker, D., Romano, D. M., and Fazeli, A. (2010b). Using computational systems biology to investigate sperm navigation and transport in the female reproductive tract. In ‘Systems Biology in Maternal Communication with Gametes and Embryos’. (Eds A. Fazeli and J. Grizelj.) (Gemini: Opatija, Croatia.)

Burkitt, M., Walker, D., Romano, D., and Fazeli, A. (2011a). Constructing complex 3D biological environments from medical imaging using high performance computing. IEEE ACM T. Comput. Bi. 99, .

Burkitt, M., Walker, D., Romano, D. M., and Fazeli, A. (2011b). Using computational modelling to investigate sperm navigation and behaviour in the female reproductive tract. Theriogenology , .

Butcher, E., Berg, E., and Kunkel, E. (2004). Systems biology in drug discovery. Nat. Biotechnol. 22, 1253–1259.
Systems biology in drug discovery.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXotFGqur0%3D&md5=3d486538a2ea1a932ecf105e16f913baCAS | 15470465PubMed |

Chaichana, T., Sun, Z., and Jewkes, J. (2011). Computation of hemodynamics in the left coronary artery with variable angulations. J. Biomech. , .
Computation of hemodynamics in the left coronary artery with variable angulations.Crossref | GoogleScholarGoogle Scholar | 21550611PubMed |

Chilvers, M., and O’Callaghan, C. (2000). Analysis of ciliary beat pattern and beat frequency using digital high speed imaging: comparison with the photomultiplier and photodiode methods. Thorax 55, 314–317.
Analysis of ciliary beat pattern and beat frequency using digital high speed imaging: comparison with the photomultiplier and photodiode methods.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3c7oslyktA%3D%3D&md5=dc07525453c133a9f99c6568709c51d6CAS | 10722772PubMed |

Clayton, R. H., and Panfilov, A. V. (2008). A guide to modelling cardiac electrical activity in anatomically detailed ventricles. Prog. Biophys. Mol. Biol. 96, 19–43.
A guide to modelling cardiac electrical activity in anatomically detailed ventricles.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD1c7jtlKqsw%3D%3D&md5=1538c4e8f4dee7edbb858fb69b06a64cCAS | 17825362PubMed |

Dauptain, A., Favier, J., and Bottaro, A. (2008). Hydrodynamics of ciliary propulsion. J. Fluids Structures 24, 1156–1165.
Hydrodynamics of ciliary propulsion.Crossref | GoogleScholarGoogle Scholar |

de Jong, H. (2002). Modeling and simulation of genetic regulatory systems: a literature review. J. Comput. Biol. 9, 67–103.
Modeling and simulation of genetic regulatory systems: a literature review.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38Xit1Kntr4%3D&md5=5d1502bd17d9e671b476511e8cc1e66dCAS | 11911796PubMed |

Debbaut, C., Monbaliu, D., Casteleyn, C., Cornillie, P., Van Loo, D., Masschaele, B., Pirenne, J., Simoens, P., Van Hoorebeke, L., and Segers, P. (2011). From vascular corrosion cast to electrical analog model for the study of human liver hemodynamics and perfusion. IEEE Trans. Biomed. Eng. 58, 25–35.
From vascular corrosion cast to electrical analog model for the study of human liver hemodynamics and perfusion.Crossref | GoogleScholarGoogle Scholar | 20709637PubMed |

Demott, R. P., and Suarez, S. S. (1992). Hyperactivated sperm progress in the mouse oviduct. Biol. Reprod. 46, 779–785.
Hyperactivated sperm progress in the mouse oviduct.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK383ntlOisA%3D%3D&md5=4793fb3fcc45fe523f7c2e55d57f5daeCAS | 1591334PubMed |

Dillon, R., and Fauci, L. (2000). An integrative model of internal axoneme mechanics and external fluid dynamics in ciliary beating. J. Theor. Biol. 207, 415–430.
An integrative model of internal axoneme mechanics and external fluid dynamics in ciliary beating.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3M7hsFynug%3D%3D&md5=ac4db658513629f329eb0bd7a38624e1CAS | 11082310PubMed |

Dillon, R., Fauci, L., Omoto, C., and Yang, X. (2007). Fluid dynamic models of flagellar and ciliary beating. Ann. N. Y. Acad. Sci. 1101, 494–505.
Fluid dynamic models of flagellar and ciliary beating.Crossref | GoogleScholarGoogle Scholar | 17344534PubMed |

Eisenbach, M., and Giojalas, L. (2006). Sperm guidance in mammals – an unpaved road to the egg. Nat. Rev. Mol. Cell Biol. 7, 276–285.
Sperm guidance in mammals – an unpaved road to the egg.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28Xjt12qsLY%3D&md5=ba4551e974a87446ae5f4552d87a9e01CAS | 16607290PubMed |

Evans, D. J. W., Lawford, P. V., Gunn, J., Walker, D., Hose, D. R., Smallwood, R. H., Chopard, B., Krafczyk, M., Bernsdorf, J., and Hoekstra, A. (2008). The application of multiscale modelling to the process of development and prevention of stenosis in a stented coronary artery. Philos. Transact. A Math. Phys. Eng. Sci. 366, 3343–3360.
The application of multiscale modelling to the process of development and prevention of stenosis in a stented coronary artery.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD1crgsleruw%3D%3D&md5=67676e466167f5acc167cf4353a9c3d4CAS |

Fauci, L., and Dillon, R. (2006). Biofluidmechanics of reproduction. Annu. Rev. Fluid Mech. 38, 371–394.
Biofluidmechanics of reproduction.Crossref | GoogleScholarGoogle Scholar |

Fazeli, A., and Pewsey, E. (2008). Maternal communication with gametes and embryos: a complex interactome. Brief. Funct. Genomics Proteomics 7, 111–118.
Maternal communication with gametes and embryos: a complex interactome.Crossref | GoogleScholarGoogle Scholar |

Finkelstein, A., Hetherington, J., Li, L., Margoninski, O., Saffrey, P., Seymour, R., and Warner, A. (2004). Computational challenges of systems biology. Computer 37, 26–33.
Computational challenges of systems biology.Crossref | GoogleScholarGoogle Scholar |

Foo, J., and Lim, C. (2008). Biofluid mechanics of the human reproductive process: modelling of the complex interaction and pathway to the oocytes. Zygote 16, 343–354.
Biofluid mechanics of the human reproductive process: modelling of the complex interaction and pathway to the oocytes.Crossref | GoogleScholarGoogle Scholar | 18652708PubMed |

Foote, R. (2007). Mathematics and complex systems. Science 318, 410–412.
Mathematics and complex systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtFOjtbzE&md5=12232d457b5cd5abfef3279bc00a7dfeCAS | 17947574PubMed |

Friedrich, B., and Jülicher, F. (2007). Chemotaxis of sperm cells. Proc. Natl. Acad. Sci. USA 104, 13 256–13 261.
Chemotaxis of sperm cells.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXps1Kgtrs%3D&md5=81b738edbcfc76d4a521cf76fb40345fCAS |

Friedrich, B. M., Riedel-Kruse, I. H., Howard, J., and Julicher, F. (2010). High-precision tracking of sperm swimming fine structure provides strong test of resistive force theory. J. Exp. Biol. 213, 1226–1234.
High-precision tracking of sperm swimming fine structure provides strong test of resistive force theory.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3c3hsleqsw%3D%3D&md5=e072bea0ed1d568ea18847fc6f32c0a5CAS | 20348333PubMed |

Georgiou, S., Snijders, A., Sostaric, E., Aflatoonian, R., Vazquez, J., Vazquez, J., Roca, J., Martinez, E., Wright, P., and Fazeli, A. (2007). Modulation of the oviductal environment by gametes. J. Proteome Res. 6, 4656–4666.
Modulation of the oviductal environment by gametes.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtlWmu73O&md5=7b8bd74a29a748e414759b74fa3c4eaeCAS |

Ginalski, K. (2006). Comparative modeling for protein structure prediction. Curr. Opin. Struct. Biol. 16, 172–177.
Comparative modeling for protein structure prediction.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28Xjs1Grs7o%3D&md5=80fbb27253a43229eb76d0fd7a07b6e3CAS | 16510277PubMed |

Giojalas, L., Rovasio, R., Fabro, G., Gakamsky, A., and Eisenbach, M. (2004). Timing of sperm capacitation appears to be programmed according to egg availability in the female genital tract. Fertil. Steril. 82, 247–249.
Timing of sperm capacitation appears to be programmed according to egg availability in the female genital tract.Crossref | GoogleScholarGoogle Scholar | 15237027PubMed |

Gray, J. (1929). The mechanism of ciliary movement. Am. Nat. 63, 68–81.
The mechanism of ciliary movement.Crossref | GoogleScholarGoogle Scholar |

Gray, J., and Hancock, G. J. (1955). The propulsion of sea-urchin spermatozoa. J. Exp. Biol. 32, 802–814.

Grimm, V. (1994). Mathematical models and understanding in ecology. Ecol. Modell. 75–76, 641–651.
Mathematical models and understanding in ecology.Crossref | GoogleScholarGoogle Scholar |

Grimm, V. (1999). Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future? Ecol. Modell. 115, 129–148.
Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future?Crossref | GoogleScholarGoogle Scholar |

Grimm, V., Frank, K., Jeltsch, F., Brandl, R., Uchmaski, J., and Wissel, C. (1996). Pattern-oriented modelling in population ecology. Sci. Total Environ. 183, 151–166.
Pattern-oriented modelling in population ecology.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK28XitlGnu70%3D&md5=d6e61eeca6bf0c684b968b99cdddfc00CAS |

Gueron, S., and Levit-Gurevich, K. (2001). A three-dimensional model for ciliary motion based on the internal 9 + 2 structure. Proc. Biol. Sci. 268, 599–607.
A three-dimensional model for ciliary motion based on the internal 9 + 2 structure.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3MvjsFSntg%3D%3D&md5=0ceca0eb02c861952be27a775b55e40dCAS | 11297177PubMed |

Gueron, S., and Liron, N. (1993). Simulations of three-dimensional ciliary beats and cilia interactions. Biophys. J. 65, 499–507.
Simulations of three-dimensional ciliary beats and cilia interactions.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK3sznvFWrsg%3D%3D&md5=bed1263f54f3e384d0542017dfdcb18fCAS | 8369453PubMed |

Harper, M. (1982). Sperm and egg transport. In ‘Germ Cells and Fertilization’. (Eds C. R. Austin and R. V. Short.) pp. 102–127. (Cambridge University Press: Cambridge, England.)

Ho, H. C., and Suarez, S. S. (2001). Hyperactivation of mammalian spermatozoa: function and regulation. Reproduction 122, 519–526.
Hyperactivation of mammalian spermatozoa: function and regulation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3MXotFGltb8%3D&md5=d70dc885be671cd64bb8bbc91986f1e8CAS | 11570958PubMed |

Hoekstra, A., Chopard, B., Lawford, P., Hose, R., Krafczyk, M., and Bernsdorf, J. (2006). Introducing complex automata for modelling multi-scale complex systems. In ‘Proceedings of European Conference on Complex Systems ECCS ’06’. (European Complex Systems Society: Oxford, England.)

Holdsworth, D., and Thornton, M. (2002). Micro-CT in small animal and specimen imaging. Trends Biotechnol. 20, S34–S39.
Micro-CT in small animal and specimen imaging.Crossref | GoogleScholarGoogle Scholar |

Hood, L., Heath, J. R., Phelps, M. E., and Lin, B. (2004). Systems biology and new technologies enable predictive and preventative medicine. Science 306, 640–643.
Systems biology and new technologies enable predictive and preventative medicine.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXos1KqtLY%3D&md5=b06799eaa973fe4bee2ba36788076b43CAS | 15499008PubMed |

Hornberg, J., Bruggeman, F., Westerhoff, H., and Lankelma, J. (2006). Cancer: a systems biology disease. Biosystems 83, 81–90.
Cancer: a systems biology disease.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XhtlGiurs%3D&md5=2d93ae5a937f357db9e401b981ac6621CAS | 16426740PubMed |

Hughey, J., Lee, T., and Covert, M. (2010). Computational modeling of mammalian signaling networks. WIREs Syst. Biol. Med. 2, 194–209.
| 1:CAS:528:DC%2BC3cXmtVSqs78%3D&md5=c0f612a57d255f22ef6d42c039664e99CAS |

Hunter, R. H. F. (2008). Sperm release from oviduct epithelial binding is controlled hormonally by peri-ovulatory graafian follicles. Mol. Reprod. Dev. 75, 167–174.
Sperm release from oviduct epithelial binding is controlled hormonally by peri-ovulatory graafian follicles.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2snkslOlsg%3D%3D&md5=2a20cafd0cb5e4918633e3dae7c30e4eCAS |

Hyakutake, T., Hashimoto, Y., Yanase, S., Matsuura, K., and Naruse, K. (2009). Application of a numerical simulation to improve the separation efficiency of a sperm sorter. Biomed. Microdevices 11, 25–33.
Application of a numerical simulation to improve the separation efficiency of a sperm sorter.Crossref | GoogleScholarGoogle Scholar | 18815887PubMed |

Ideker, T., Galitski, T., and Hood, L. (2001). A NEW APPROACH TO DECODING LIFE: systems biology. Annu. Rev. Genomics Hum. Genet. 2, 343–372.
A NEW APPROACH TO DECODING LIFE: systems biology.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3MXos1anurw%3D&md5=6d6384cea7883dad809cbaefa4c00347CAS | 11701654PubMed |

Ishikawa, M., Tsutsui, H., Cosson, J., Oka, Y., and Morisawa, M. (2004). Strategies for sperm chemotaxis in the siphonophores and ascidians: a numerical simulation study. Biol. Bull. 206, 95–102.
Strategies for sperm chemotaxis in the siphonophores and ascidians: a numerical simulation study.Crossref | GoogleScholarGoogle Scholar | 15111364PubMed |

Jackson, D., Holcombe, M., and Ratnieks, F. (2004). Trail geometry gives polarity to ant foraging networks. Nature 432, 907–909.
Trail geometry gives polarity to ant foraging networks.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXhtVOht7rF&md5=a8de9d5b41b3ca0df7c9ca6b4e50051eCAS | 15602563PubMed |

Kapetanovic, I. (2008). Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach. Chem.-Biol. Interact. 171, 165–176.
| 1:CAS:528:DC%2BD1cXhsVSitr4%3D&md5=4f36fc3e2962512b5098f70e2dcc8b61CAS | 17229415PubMed |

Katagiri, F. (2003). Attacking complex problems with the power of systems biology. Plant Physiol. 132, 417–419.
Attacking complex problems with the power of systems biology.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXkslers7k%3D&md5=810fdb48c21df34b34af7bfec77476e3CAS | 12805572PubMed |

Kirschner, D., and Linderman, J. (2009). Mathematical and computational approaches can complement experimental studies of host–pathogen interactions. Cell. Microbiol. 11, 531–539.
Mathematical and computational approaches can complement experimental studies of host–pathogen interactions.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXktVajsrg%3D&md5=6b5b7654d5e17e8f82e8db61e9613157CAS | 19134115PubMed |

Kitano, H. (2002a). Looking beyond the details: a rise in system-oriented approaches in genetics and molecular biology. Curr. Genet. 41, 1–10.
Looking beyond the details: a rise in system-oriented approaches in genetics and molecular biology.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XktVKlsr8%3D&md5=ed29821e282981eff7aa2dceb009ffbeCAS | 12073094PubMed |

Kitano, H. (2002b). Systems biology: a brief overview. Science 295, 1662–1664.
Systems biology: a brief overview.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38Xhsleitb0%3D&md5=22038f6c940e7fbed30021f682857c49CAS | 11872829PubMed |

Klauschen, F., Angermann, B. R., and Meier-Schellersheim, M. (2007). Understanding diseases by mouse click: the promise and potential of computational approaches in systems biology. Clin. Exp. Immunol. 149, 424–429.
Understanding diseases by mouse click: the promise and potential of computational approaches in systems biology.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2svnvFKrug%3D%3D&md5=809f8b7468bb98294c28739e30ef6687CAS | 17666096PubMed |

Li, G., Citrin, D., Miller, R., Camphausen, K., Mueller, B., Mychalczak, B., and Song, Y. (2008). 3D and 4D medical image registration combined with image segmentation and visualization. In ‘Encyclopaedia of Healthcare Information Systems’. (Eds N. Wickramasinghe and E. Geisler.) pp. 1–9. (IGI Global.: Hershey, PA.)

Lindemann, C. (2007). The geometric clutch as a working hypothesis for future research on cilia and flagella. Ann. N. Y. Acad. Sci. 1101, 477–493.
The geometric clutch as a working hypothesis for future research on cilia and flagella.Crossref | GoogleScholarGoogle Scholar | 17303832PubMed |

Lyons, R. A., Saridogan, E., and Djahanbakhch, O. (2006). The reproductive significance of human fallopian tube cilia. Hum. Reprod. Update 12, 363–372.
The reproductive significance of human fallopian tube cilia.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD28vmt1OqsA%3D%3D&md5=1c096fb1031b727e389f7a1fefc216c5CAS | 16565155PubMed |

Marzo, A., Singh, P., Larrabide, I., Radaelli, A., Coley, S., Gwilliam, M., Wilkinson, I. D., Lawford, P., Reymond, P., Patel, U., Frangi, A., and Hose, D. R. (2011). Computational hemodynamics in cerebral aneurysms: the effects of modeled versus measured boundary conditions. Ann. Biomed. Eng. 39, 884–896.
Computational hemodynamics in cerebral aneurysms: the effects of modeled versus measured boundary conditions.Crossref | GoogleScholarGoogle Scholar | 20972626PubMed |

Mastroianni, L. (1999). The fallopian tube and reproductive health. J. Pediatr. Adolesc. Gynecol. 12, 121–126.
The fallopian tube and reproductive health.Crossref | GoogleScholarGoogle Scholar | 10546902PubMed |

Materi, W., and Wishart, D. S. (2007). Computational systems biology in drug discovery and development: methods and applications. Drug Discov. Today 12, 295–303.
Computational systems biology in drug discovery and development: methods and applications.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXjs1OntLY%3D&md5=ab351ef24e0109bbfa57607876b9561fCAS | 17395089PubMed |

Noble, D. (2002a). Modeling the heart – from genes to cells to the whole organ. Science 295, 1678–1682.
Modeling the heart – from genes to cells to the whole organ.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38Xhsleiuro%3D&md5=8cd5989a9abe88dd57940564d0c4a842CAS | 11872832PubMed |

Noble, D. (2002b). The rise of computational biology. Nat. Rev. Mol. Cell Biol. 3, 459–463.
The rise of computational biology.Crossref | GoogleScholarGoogle Scholar | 12042768PubMed |

Noble, D. (2003). The future: putting Humpty-Dumpty together again. Biochem. Soc. Trans. 31, 156–158.
| 1:CAS:528:DC%2BD3sXptF2lug%3D%3D&md5=27a3b8d1981e09b52d9cebc60e09665fCAS | 12546675PubMed |

Oren-Benaroya, R., Kipnis, J., and Eisenbach, M. (2007). Phagocytosis of human post-capacitated spermatozoa by macrophages. Hum. Reprod. 22, 2947–2955.
Phagocytosis of human post-capacitated spermatozoa by macrophages.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1Shu7bI&md5=23b7947508afeb93e07dc1af476e7e41CAS | 17766922PubMed |

Poddar, A. H., Krol, A., Beaumont, J., Price, R. L., Slamani, M. A., Fawcett, J., Subramanian, A., Coman, I. L., Lipson, E. D., and Feiglin, D. H. (2005). Ultrahigh resolution 3D model of murine heart from micro-CT and serial confocal laser scanning microscopy images. In ‘Nuclear Science Symposium and Medical Imaging Conference’. pp. 2615–2617. (IEEE: Fajardo, Puerto Rico.)

Pop, M., and Salzberg, S. (2008). Bioinformatics challenges of new sequencing technology. Trends Genet. 24, 142–149.
Bioinformatics challenges of new sequencing technology.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXislKht78%3D&md5=f3eeaddf6b59185b35af5697ac84d5c4CAS | 18262676PubMed |

Richmond, P., Walker, D., Coakley, S., and Romano, D. M. (2010). High performance cellular level agent-based simulation with FLAME for the GPU. Brief. Bioinform. 11, 334–347.
High performance cellular level agent-based simulation with FLAME for the GPU.Crossref | GoogleScholarGoogle Scholar | 20123941PubMed |

Riffell, J., and Zimmer, R. (2007). Sex and flow: the consequences of fluid shear for sperm egg interactions. J. Exp. Biol. 210, 3644–3660.
Sex and flow: the consequences of fluid shear for sperm egg interactions.Crossref | GoogleScholarGoogle Scholar | 17921166PubMed |

Salekdeh, G., and Komatsu, S. (2007). Crop proteomics: aim at sustainable agriculture of tomorrow. Proteomics 7, 2976–2996.
Crop proteomics: aim at sustainable agriculture of tomorrow.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtVelsL7K&md5=44821efd225d1521ff62659acc4cce7dCAS | 17639607PubMed |

Samsonova, A., Niranjan, M., Russell, S., and Brazma, A. (2007). Prediction of gene expression in embryonic structures of Drosophila melanogaster. PLOS Comput. Biol. 3, e144.
Prediction of gene expression in embryonic structures of Drosophila melanogaster.Crossref | GoogleScholarGoogle Scholar | 17658945PubMed |

Sargent, R. (2005). Verification and validation of simulation models. In ‘WSC ‘05: Proceedings of the 37th Conference on Winter Simulation’. pp. 130–143. (Winter Simulation Conference: Orlando, FL.)

Sauer, U., Heinemann, M., and Zamboni, N. (2007). Getting closer to the whole picture. Science 316, 550–551.
Getting closer to the whole picture.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXltVegt7g%3D&md5=d2400d5ad393a1b2185374a22a6c1b73CAS | 17463274PubMed |

Scott, A. (2004). Reductionism revisited. J. Conscious. Stud. 11, 51–68.

Segal, E., Raveh-Sadka, T., Schroeder, M., Unnerstall, U., and Gaul, U. (2008). Predicting expression patterns from regulatory sequence in Drosophila segmentation. Nature 451, 535–540.
Predicting expression patterns from regulatory sequence in Drosophila segmentation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhs1ent7w%3D&md5=8455c5de96fbcc07da71053e65c33ca6CAS | 18172436PubMed |

Seo, D.-b., Agca, Y., Feng, Z., and Critser, J. (2007). Development of sorting, aligning, and orienting motile sperm using microfluidic device operated by hydrostatic pressure. Microfluid. Nanofluid. 3, 561–570.
Development of sorting, aligning, and orienting motile sperm using microfluidic device operated by hydrostatic pressure.Crossref | GoogleScholarGoogle Scholar |

Seytanoglu, A., Georgiou, S., Sostaric, E., Watson, P., Holt, W., and Fazeli, A. (2008). Oviductal cell proteome alterations during the reproductive cycle in pigs. J. Proteome Res. 7, 2825–2833.
Oviductal cell proteome alterations during the reproductive cycle in pigs.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXmvFCit7s%3D&md5=9fde7c37623a8df5aaa614ab11b4f3b7CAS | 18540664PubMed |

Smith, T. T., and Yanagimachi, R. (1990). The viability of hamster spermatozoa stored in the isthmus of the oviduct: the importance of sperm-epithelium contact for sperm survival. Biol. Reprod. 42, 450–457.
The viability of hamster spermatozoa stored in the isthmus of the oviduct: the importance of sperm-epithelium contact for sperm survival.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK3c3lsVansQ%3D%3D&md5=0e6fc78a88fc813f117f45649be6bb98CAS | 2340331PubMed |

Smith, D. J., Gaffney, E. A., Blake, J. R., and Kirkman-Brown, J. C. (2009). Human sperm accumulation near surfaces: a simulation study. J. Fluid Mech. 621, 289–320.
Human sperm accumulation near surfaces: a simulation study.Crossref | GoogleScholarGoogle Scholar |

Suarez, S. S. (1987). Sperm transport and motility in the mouse oviduct: observations in situ. Biol. Reprod. 36, 203–210.
Sperm transport and motility in the mouse oviduct: observations in situ.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaL2s7osFKkug%3D%3D&md5=6cae67335891a88f92bbb435c7aaf4d9CAS | 3567275PubMed |

Suarez, S. (2008a). Control of hyperactivation in sperm. Hum. Reprod. Update 14, 647–657.
Control of hyperactivation in sperm.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXht1Ois7%2FK&md5=8df914dc7d3c20eb23ef34beda4d7dc6CAS | 18653675PubMed |

Suarez, S. S. (2008b). Regulation of sperm storage and movement in the mammalian oviduct. Int. J. Dev. Biol. 52, 455–462.
Regulation of sperm storage and movement in the mammalian oviduct.Crossref | GoogleScholarGoogle Scholar | 18649258PubMed |

Suarez, S. S., and Pacey, A. A. (2006). Sperm transport in the female reproductive tract. Hum. Reprod. Update 12, 23–37.
Sperm transport in the female reproductive tract.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2MnmslSgtA%3D%3D&md5=e82e4f77b1828d6441801b4e384e67e0CAS | 16272225PubMed |

Sun, F., Bahat, A., Gakamsky, A., Girsh, E., Katz, N., Giojalas, L., Tur-Kaspa, I., and Eisenbach, M. (2005). Human sperm chemotaxis: both the oocyte and its surrounding cumulus cells secrete sperm chemoattractants. Hum. Reprod. 20, 761–767.
Human sperm chemotaxis: both the oocyte and its surrounding cumulus cells secrete sperm chemoattractants.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXhsFSgsbg%3D&md5=6868408349d392216022f1ae0f5b4f15CAS | 15591080PubMed |

Taylor, G. (1951). Analysis of the swimming of microscopic organisms. Proc. Roy. Soc. Lond. Ser. A Math. Phys. Sci. 209, 447–461.
Analysis of the swimming of microscopic organisms.Crossref | GoogleScholarGoogle Scholar |

Tienthai, P., Johannisson, A., and Rodriguez-Martinez, H. (2004). Sperm capacitation in the porcine oviduct. Anim. Reprod. Sci. 80, 131–146.
Sperm capacitation in the porcine oviduct.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2c7kt1Oquw%3D%3D&md5=a6a9b635a21bb7ce86e481e969284354CAS | 15036522PubMed |

Walker, D., and Southgate, J. (2009). The virtual cell – a candidate co-ordinator for ‘middle-out’ modelling of biological systems. Brief. Bioinform. 10, 450–461.
The virtual cell – a candidate co-ordinator for ‘middle-out’ modelling of biological systems.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXnsFWqu7k%3D&md5=d7fc5f8a80e22c15aefe4d777b0bc157CAS | 19293250PubMed |

Wilke, A. (2003). Bioinformatics support for high-throughput proteomics. J. Biotechnol. 106, 147–156.
Bioinformatics support for high-throughput proteomics.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXpsVSrtrs%3D&md5=ef3149b0022bf8a89b6f325030fdafe7CAS | 14651857PubMed |

Wissel, C. (1992). Aims and limits of ecological modelling exemplified by island theory. Ecol. Modell. 63, 1–12.
Aims and limits of ecological modelling exemplified by island theory.Crossref | GoogleScholarGoogle Scholar |

Wolfram, S. (1984). Cellular automata as models of complexity. Nature 311, 419–424.
Cellular automata as models of complexity.Crossref | GoogleScholarGoogle Scholar |

Yang, X., Dillon, R., and Fauci, L. (2008). An integrative computational model of multiciliary beating. Bull. Math. Biol. 70, 1192–1215.
An integrative computational model of multiciliary beating.Crossref | GoogleScholarGoogle Scholar | 18236120PubMed |

Zervomanolakis, I., Ott, H. W., Hadziomerovic, D., Mattle, V., Seeber, B. E., Virgolini, I., Heute, D., Kissler, S., Leyendecker, G., and Wildt, L. (2007). Physiology of upward transport in the human female genital tract. Ann. N. Y. Acad. Sci. 1101, 1–20.
Physiology of upward transport in the human female genital tract.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXlvFCgs70%3D&md5=42d159adfbe82b988694d36ea51747b9CAS | 17416925PubMed |

Zinzen, R., Senger, K., Levine, M., and Papatsenko, D. (2006). Computational models for neurogenic gene expression in the Drosophila embryo. Curr. Biol. 16, 1358–1365.
Computational models for neurogenic gene expression in the Drosophila embryo.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28XmsFSltb8%3D&md5=ec139e96417d7b7683ad32e881ee88abCAS | 16750631PubMed |