Evolution of Modern Molecular Biology Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: closed (20 November 2021) | Viewed by 11032
Special Issue Editors
Interests: microbiome-host interactions and their role in human disease; algorithmical applications to modern scientific problems
Interests: genetic; molecular; biochemical; cytological and proteomic approaches to study meiotic chromosome dynamics in fission yeast
Special Issue Information
Dear Colleagues,
Forty years ago, when relatively powerful microprocessors first became available, many young entrepreneurs were inspired to create companies, platforms, and programming tools that helped make computing available to everyone. This in turn helped spark the information revolution. Today, thanks to the increasing sophistication, speed, and power of computer modeling and other new tools, we are on the brink of another revolution — this time in bioscience.
In laboratories around the world, some of the brightest scientists — well-established and those early in their careers — are conceiving novel theories at the very forefront of knowledge. The complexity of biology is a fascinating challenge, and I am keen to see the field deconstruct its mysteries, establish reliable and predictive models, and put that knowledge to work.
The aim of this Special Issue, therefore, is to offer a platform for scientists working on the different aspects of Molecular Biology; fusion of classical methods with novel approaches drives human progress, and it is this belief that fuels our optimism in that direction.
We invite you to submit manuscripts addressing novel uses of classical techniques in molecular biology and possible applications of these methods in future medical and life science research for a compilation of our current knowledge into a comprehensive issue.
Dr. Oleg Karaduta
Dr. Mari K. Davidson
Guest Editors
Manuscript Submission Information
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Keywords
- CRISPR
- Multiomics
- Systems Biology
- Molecular Databases
- Chemical Modulation
- Computational Biology
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