Evidence map›Paper›PMID 26557642›Full record

ReviewFrontiers in bioengineering and biotechnology2015

Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants.

Camilla Beate Hill, Tobias Czauderna, Matthias Klapperstück, Ute Roessner, Falk Schreiber

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Camilla Beate HillSchool of BioSciences, University of Melbourne , Parkville, VIC , Australia.
Tobias CzaudernaFaculty of Information Technology, Monash University , Clayton, VIC , Australia.
Matthias KlapperstückFaculty of Information Technology, Monash University , Clayton, VIC , Australia.
Ute RoessnerSchool of BioSciences, University of Melbourne , Parkville, VIC , Australia.
Falk SchreiberFaculty of Information Technology, Monash University , Clayton, VIC , Australia ; Institute of Computer Science, Martin Luther University Halle-Wittenberg , Halle , Germany.
Monash University · AUAgriBio · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions.

Indexed as

metabolic engineeringmetabolic modelingmetabolomicssynthetic biologysystems biology

Identifiers

PMID26557642
PMCPMC4617106
OpenAlexW1932604562

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.