Evidence map›Paper›PMID 42062737›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2026

Metabolic Engineering of Microalgae for Biofuel Production.

Mohammad Pooya Naghshbandi, Meisam Tabatabaei, Mortaza Aghbashlo, Muhammad Nauman Aftab, Irfana Iqbal

Abstract readReview
PubMed Publisher
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mohammad Pooya NaghshbandiDepartment of Microbial Biotechnology, School of Biology, College of Science, University of Tehran, Tehran, Iran.
Meisam TabatabaeiHigher Institution Centre of Excellence (HICoE), Institute ofTropical Aquaculture and Fisheries (AKUATROP), Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia. meisam_tab@yahoo.com.
Mortaza AghbashloDepartment of Agricultural Machinery, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. maghbashlo@ut.ac.ir.
Muhammad Nauman AftabInstitute of Industrial Biotechnology, Government College University, Lahore, Pakistan.
Irfana IqbalDepartment of Biotechnology, Lahore College for Women University, Lahore, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microalgae are considered promising cell factories to produce various types of biofuels, including bioethanol, biodiesel, and biohydrogen, by using carbon dioxide and sunlight. Despite the unique advantages of these microorganisms, the commercialization of microalgal biofuels has been hindered by unfavorable economic factors. Metabolic engineering is among the most promising strategies put forth to overcome this challenge. In this chapter, metabolic pathways involved in lipid and hydrogen production by microalgae are reviewed and discussed. Moreover, metabolic and genetic engineering approaches investigated for improving the rate of lipid production (as a feedstock for biodiesel production) and biohydrogen synthesis are presented. Finally, genetic engineering tools and approaches employed for engineering microalgal metabolic pathways are described in detail. A thorough step-by-step protocol for reconstructing the metabolic pathways of various microorganisms, including microalgae, is also presented.

Indexed as

BiofuelsBiomassMetabolic EngineeringMicroalgaeGenetic EngineeringMetabolic Networks and PathwaysBiofuelsBiodieselBiohydrogenGenetic engineeringMetabolic engineeringMicroalgae

Identifiers

PMID42062737

What OpenQuestion holds

Textmetadata
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Registered trials

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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.