@article{1469951,
      recid = {1469951},
      author = {Ning, Kang. and Zhan, Yi.},
      title = {Synthetic biology and IGEM : an omics big-data mining  perspective /},
      publisher = {Springer,},
      address = {Singapore :},
      pages = {1 online resource (119 p.)},
      year = {2023},
      abstract = {This book focuses on biological engineering techniques,  multi-omics big-data integration, and data-mining  techniques, as well as cutting-edge researches in  principles and applications of several synthetic biology  applications. Synthetic biology is a new research area,  while it has been rooted from the long-established area  including biological engineering, metabolite engineering,  and systems biology. This book will discuss the following  aspects: (1) introduction to synthetic biology and iGEM,  especially focusing on the systematic design, rational  engineering, and sustainability of design in the omics  ages; (2) synthetic biologyrelated multi-omics data  integration and data mining techniques; (3) the technical  issues, development issues, and safety issues of synthetic  biology; (4) data resources, web services, and  visualizations for synthetic biology; and (5) advancement  in concrete research on synthetic biology, with several  case studies shown. Devised as a book on synthetic biology  research and education in the omics age, this book has put  focuses on systematic design, rational engineering, and  sustainability of design for synthetic biology, which will  explain in detail and with supportive examples the What,  Why, and How of the topic. It is an attempt to bridge the  gap between synthetic biologys research and education side,  for best practice of synthetic biology and in-depth  insights for the related questions.},
      url = {http://library.usi.edu/record/1469951},
      doi = {https://doi.org/10.1007/978-981-99-2460-8},
}