Understanding Life: A Bioinformatics Perspective
Natalia Szostak,
Szymon Wasik and
Jacek Blazewicz
European Review, 2017, vol. 25, issue 2, 231-245
Abstract:
According to some hypotheses, from a statistical perspective the origin of life seems to be a highly improbable event. Although there is no rigid definition of life itself, life as it is, is a fact. One of the most recognized hypotheses for the origins of life is the RNA world hypothesis. Laboratory experiments have been conducted to prove some assumptions of the RNA world hypothesis. However, despite some success in the ‘wet-lab’, we are still far from a complete explanation. Bioinformatics, supported by biomathematics, appears to provide the perfect tools to model and test various scenarios of the origins of life where wet-lab experiments cannot reflect the true complexity of the problem. Bioinformatics simulations of early pre-living systems may give us clues to the mechanisms of evolution. Whether or not this approach succeeds is still an open question. However, it seems likely that linking efforts and knowledge from the various fields of science into a holistic bioinformatics perspective offers the opportunity to come one step closer to a solution to the question of the origin of life, which is one of the greatest mysteries of humankind. This paper illustrates some recent advancements in this area and points out possible directions for further research.
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cup:eurrev:v:25:y:2017:i:02:p:231-245_00
Access Statistics for this article
More articles in European Review from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().