Synthetic Biology Handbook
by Darren N. Nesbeth · Darren N. Nesbeth
An edited CRC Press volume in which specialists survey the field's major goals and the technical state of the art, from parts and chassis design to industrial biomanufacturing. Useful for readers who already know the basics and want depth.
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More resources on Synthetic Biology
synbiobeta.com
SynBioBeta is a media and events platform for the synthetic biology community, offering news and analysis, startup profiles, and information on conferences, funding, and industry resources.
syntheticbiology.org
Syntheticbiology.org is a central resource hub for learning about synthetic biology, offering introductory explanations, educational materials, and news and policy updates about the field.
igem.org
iGEM.org is the official site for the International Genetically Engineered Machine (iGEM) competition in synthetic biology. It provides project showcases, the Registry of Standard Biological Parts, tutorials and educational resources, team information, and event details like the annual Jamboree.
OpenWetWare
Community wiki where academic biology labs publish protocols, open notebooks, course materials and group pages. Useful for finding a working bench protocol and seeing how synthetic biology groups document their day-to-day methods.
Introduction to Biological Engineering Design (MIT 20.020)
Project-based introduction to engineering synthetic biological systems: prokaryotic and eukaryotic control, DNA synthesis, standard parts and abstraction, plus biosafety, security, intellectual property and ethics. Provides lecture slides, short tutorial videos and example student projects for designing biology-based solutions to real problems.
Foundations of Computational and Systems Biology (MIT 7.91J)
Computational biology fundamentals: nucleic acid and protein sequence alignment, motif finding, structural modeling and prediction, and network models of biological systems. Includes 22 lecture videos, slides, programming assignments and projects, preparing learners to apply algorithms to genomic and protein data.