Evidence map›Paper›PMID 22196224›Full record

ReviewCritical reviews in biomedical engineering2011

Advanced stoichiometric analysis of metabolic networks of mammalian systems.

Mehmet A Orman, Francois Berthiaume, Ioannis P Androulakis, Marianthi G Ierapetritou

Open access · greenAbstract readReview
In one paragraph

Review in Critical reviews in biomedical engineering, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

14 citing papers in PubMed, 33 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Mehmet A OrmanDepartment of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Francois Berthiaume
Ioannis P Androulakis
Marianthi G Ierapetritou
Rutgers, The State University of New Jersey · US

Funding

Bioinformatics Analysis of Control Mechanisms of HypermetabolismR01GM082974 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI ANDROULAKIS, IOANNIS P · 2008 to 2011
$1.6M
NIGMS NIH HHS GM082974NIGMS NIH HHS R01 GM082974
6 · The paper itself

Abstract

Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted.

Indexed as

Metabolic Networks and PathwaysAlgorithmsAnimalsCell LineComputational BiologyComputer SimulationCricetinaeEukaryotic CellsHumansMetabolic EngineeringMiceModels, BiologicalRatsSystems Biology

Identifiers

PMID22196224
PMCPMC3634616
OpenAlexW2025083491

What OpenQuestion holds

Textmetadata
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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.