METABOLIC ENGINEERING

Scope & Guideline

Unlocking the Potential of Metabolic Engineering

Introduction

Delve into the academic richness of METABOLIC ENGINEERING with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN1096-7176
PublisherACADEMIC PRESS INC ELSEVIER SCIENCE
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 1999 to 2024
AbbreviationMETAB ENG / Metab. Eng.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address525 B ST, STE 1900, SAN DIEGO, CA 92101-4495

Aims and Scopes

The journal 'Metabolic Engineering' focuses on the innovative application of metabolic engineering techniques to enhance the production of valuable compounds through microbial and plant systems. It encompasses a wide range of methodologies aimed at optimizing metabolic pathways and improving bioproduction efficiency.
  1. Metabolic Pathway Engineering:
    Research aimed at designing and reconstructing metabolic pathways to enhance the production of desired metabolites, including biofuels, pharmaceuticals, and specialty chemicals.
  2. Synthetic Biology Applications:
    Utilization of synthetic biology tools to construct novel biosynthetic pathways, enabling the production of compounds that are not naturally synthesized by the host organism.
  3. Systems Biology and Omics Technologies:
    Integration of systems biology approaches and omics technologies (genomics, transcriptomics, proteomics, and metabolomics) to understand and manipulate cellular metabolism at a systems level.
  4. Microbial and Plant Cell Factories:
    Development of microbial and plant systems as efficient production platforms for biochemicals, focusing on improving yield, productivity, and sustainability.
  5. Machine Learning and Computational Modeling:
    Application of machine learning algorithms and computational models to predict metabolic fluxes and optimize metabolic pathways for enhanced bioproduction.
  6. Environmental Sustainability:
    Research focused on utilizing renewable resources and waste materials in metabolic engineering to promote sustainable bioproduction practices.
Recent publications in 'Metabolic Engineering' reveal a dynamic shift towards innovative methodologies and themes that address contemporary challenges in metabolic engineering.
  1. CRISPR and Genome Editing Technologies:
    The adoption of CRISPR and other advanced genome-editing technologies has surged, enabling precise modifications and the construction of complex metabolic pathways.
  2. Machine Learning in Metabolic Engineering:
    The incorporation of machine learning techniques to predict metabolic outcomes and optimize bioprocesses is rapidly gaining traction, reflecting a trend towards data-driven approaches.
  3. Multi-Omics Integration:
    A growing emphasis on multi-omics strategies to holistically analyze and engineer metabolic pathways, allowing for a better understanding of cellular responses and interactions.
  4. Sustainable Bioproduction from Waste Resources:
    Research focused on converting waste materials and biomass into valuable products is increasingly prominent, aligning with global sustainability goals.
  5. Dynamic and Adaptive Metabolic Control:
    Emerging strategies involve dynamic regulation and adaptive control of metabolism, allowing for real-time adjustments in production processes based on environmental conditions.
  6. Novel Chassis Development:
    There is an increasing trend towards the development of new microbial and plant chassis that offer enhanced capabilities for bioproduction, expanding the toolbox available for metabolic engineers.

Declining or Waning

As the field of metabolic engineering evolves, certain themes have seen a decline in publication frequency. This may indicate a shift in focus towards more innovative methodologies or emerging technologies.
  1. Traditional Fermentation Processes:
    Research centered on conventional fermentation processes for metabolite production has diminished as the field shifts towards more advanced synthetic and systems biology approaches.
  2. Single-Target Enzyme Engineering:
    The focus on engineering individual enzymes for enhanced activity is decreasing in favor of holistic approaches that consider entire pathways and networks.
  3. Basic Genetic Manipulation Techniques:
    Basic techniques for genetic modifications, such as simple gene knockouts or overexpression, are being overshadowed by more sophisticated methods like CRISPR/Cas9 and multiplex genome editing.
  4. Conventional Strain Improvement:
    Traditional methods for strain improvement through random mutagenesis are less prevalent, as directed evolution and machine learning-based approaches gain prominence.
  5. Focus on Model Organisms:
    There is a waning interest in using traditional model organisms, like E. coli and S. cerevisiae, as researchers explore a broader range of non-conventional hosts for metabolic engineering.

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