Improving prediction fidelity of cellular metabolism with kinetic descriptions

Anupam Chowdhury, Ali Khodayari, Costas D. Maranas

Research output: Contribution to journalReview articlepeer-review

18 Scopus citations

Abstract

Several modeling frameworks for describing and redirecting cellular metabolism have been developed keeping pace with the rapid development in high-throughput data generation and advances in metabolic engineering techniques. The incorporation of kinetic information within stoichiometry-only modeling techniques offers potential advantages for improved phenotype prediction and consequently more precise computational strain design. In addition to substrate-level kinetic regulatory information, the integration of a number of additional layers of regulation at the transcription, translation, and post-translation levels is sought after by many research groups. However, the practical integration of these complex biological processes into a unified framework amenable to design remains an ongoing challenge.

Original languageEnglish (US)
Pages (from-to)57-64
Number of pages8
JournalCurrent Opinion in Biotechnology
Volume36
DOIs
StatePublished - Dec 1 2015

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Bioengineering
  • Biomedical Engineering

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