Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 664

The DOI matches its Crossref record; 139 of the 139 references it cites were found in a registry or an index.

Flavonoid biosynthetic pathways in plants: Versatile targets for metabolic engineering

Open access
Nabavi, Seyed Mohammad, Šamec, Dunja, Tomczyk, Michał, Milella, Luigi, Russo, Daniela, Habtemariam, Solomon, Suntar, Ipek, Rastrelli, Luca, Daglia, Maria, Xiao, Jianbo, Giampieri, Francesca, Battino, Maurizio, Sobarzo-Sanchez, Eduardo, Nabavi, Seyed Fazel, Yousefi, Bahman, Jeandet, Philippe, Xu, Suowen, Shirooie, Samira·2020·Biotechnology Advances
DOI 10.1016/j.biotechadv.2018.11.005
Open this paper in CoChat — free account

Abstract

Plants, fungi, and microorganisms are equipped with biosynthesis machinery for producing thousands of secondary metabolites. These compounds have important functions in nature as a defence against predators or competitors as well as other ecological significances. The full utilization of these compounds for food, medicine, and other purposes requires a thorough understanding of their structures and the distinct biochemical pathways of their production in cellular systems. In this review, flavonoids as classical examples of secondary metabolites are employed to highlight recent advances in understanding how valuable compounds can be regulated at various levels. With extensive diversity in their chemistry and pharmacology, understanding the metabolic engineering of flavonoids now allows us to fine-tune the eliciting of their production, accumulation, and extraction from living systems. More specifically, recent advances in the shikimic acid and acetate biosynthetic pathways of flavonoids production from metabolic engineering point of view, from genes expression to multiple principles of regulation, are addressed. Specific examples of plants and microorganisms as the sources of flavonoids-based compounds with particular emphasis on therapeutic applications are also discussed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.biotechadv.2018.11.005

Cites

139 of 139 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 139 references

Cited by

See all 664

Metadata

Authors
Nabavi, S. M., Šamec, D., Tomczyk, M., Milella, L., Russo, D., Habtemariam, S., Suntar, I., Rastrelli, L., Daglia, M., Xiao, J., Giampieri, F., Battino, M., Sobarzo-Sanchez, E., Nabavi, S. F., Yousefi, B., Jeandet, P., Xu, S., & Shirooie, S.
Venue
Biotechnology Advances
Publisher
Elsevier BV
Published
2020-01
Volume
38
Pages
107316
ISSN
0734-9750 (ISSN-L)
DOI
10.1016/j.biotechadv.2018.11.005
OpenAlex
W2901653977
Cited by
664
References
139
FWCI
9.10
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Flavonoid biosynthetic pathways in plants: Versatile targets for metabolic engineering. https://app.cochat.ai/papers/10.1016/j.biotechadv.2018.11.005
The paper
Nabavi, S. M., Šamec, D., Tomczyk, M., Milella, L., Russo, D., Habtemariam, S., Suntar, I., Rastrelli, L., Daglia, M., Xiao, J., Giampieri, F., Battino, M., Sobarzo-Sanchez, E., Nabavi, S. F., Yousefi, B., Jeandet, P., Xu, S., & Shirooie, S. (2020). Flavonoid biosynthetic pathways in plants: Versatile targets for metabolic engineering. Biotechnology Advances. https://doi.org/10.1016/j.biotechadv.2018.11.005

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.