{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T15:02:05Z","timestamp":1790002925421,"version":"4.0.1"},"reference-count":98,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2017,2,7]],"date-time":"2017-02-07T00:00:00Z","timestamp":1486425600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.cambridge.org"],"crossmark-restriction":true},"short-container-title":["Parasitology"],"published-print":{"date-parts":[[2018,2]]},"abstract":"<jats:title>SUMMARY<\/jats:title><jats:p>Cell cycle progression is a question of fundamental biological interest. The coordinated duplication and segregation of all cellular structures and organelles is however an extremely complex process, and one which remains only partially understood even in the most intensively researched model organisms. Trypanosomes are in an unusual position in this respect \u2013 they are both outstanding model systems for fundamental questions in eukaryotic cell biology, and pathogens that are the causative agents of three of the neglected tropical diseases. As a failure to successfully complete cell division will be deleterious or lethal, analysis of the cell division cycle is of relevance both to basic biology and drug design efforts. Cell division cycle analysis is however experimentally challenging, as the analysis of phenotypes associated with it remains hypothesis-driven and therefore biased. Current methods of analysis are extremely labour-intensive, and cell synchronization remains difficult and unreliable. Consequently, there exists a need \u2013 both in basic and applied trypanosome biology \u2013 for a global, unbiased, standardized and high-throughput analysis of cell division cycle progression. In this review, the requirements \u2013 both practical and computational \u2013 for such a system are considered and compared with existing techniques for cell cycle analysis.<\/jats:p>","DOI":"10.1017\/s0031182017000038","type":"journal-article","created":{"date-parts":[[2017,2,7]],"date-time":"2017-02-07T11:10:12Z","timestamp":1486465812000},"page":"196-209","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":5,"title":["Let's get fISSical: fast<i>in silico<\/i>synchronization as a new tool for cell division cycle 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