Evidence map›Paper›PMID 21749716›Full record

ArticleBMC systems biology2011

iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states.

Aarash Bordbar, Neema Jamshidi, Bernhard O Palsson

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

64 citing papers in PubMed, 115 citations in OpenAlex.

  1. Trial
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  5. Reconstruction of human metabolic models with large language models.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  14. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
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  16. NAR genomics and bioinformatics · 2024
    Article
  17. Article
  18. Article
  19. Review
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4 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Aarash BordbarDepartment of Bioengineering, University of California San Diego, La Jolla, 92093-0412, USA.
Neema Jamshidi
Bernhard O Palsson
La Jolla Bioengineering Institute · US

Funding

Network-based Analysis of Kinetics and RegulationR01GM068837 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 2003 to 2012
$2.4M
NIGMS NIH HHS GM068837
6 · The paper itself

Abstract

backgroundThe development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored.

resultsErythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte.

conclusionThe advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

Indexed as

Knowledge BasesMetabolic Networks and PathwaysModels, BiologicalBiomarkersErythrocytesHumansProteomicsSystems BiologyBiomarkers

Identifiers

PMID21749716
PMCPMC3158119
OpenAlexW2154717205

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.