Evidence map›Paper›PMID 21102456›Full record

ArticleNature biotechnology2010

Large-scale in silico modeling of metabolic interactions between cell types in the human brain.

Nathan E Lewis, Gunnar Schramm, Aarash Bordbar, Jan Schellenberger, Michael P Andersen, Jeffrey K Cheng, Nilam Patel, Alex Yee, Randall A Lewis, Roland Eils and 2 more

Open access · greenAbstract read
In one paragraph

Article in Nature biotechnology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 134 papers.

0numbers the graph read from it
0cells of the map it votes in
134citing papers in PubMed
10.0field-weighted citation impact, top 1% 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

134 citing papers in PubMed, 271 citations in OpenAlex.

  1. Article
  2. Article
  3. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
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  16. What are housekeeping genes?PLoS computational biology · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. Article

74 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

12 authors at 4 institutions in 2 countries.

Nathan E LewisDepartment of Bioengineering, University of California, San Diego, La Jolla, California, USA.
Gunnar Schramm
Aarash Bordbar
Jan Schellenberger
Michael P Andersen
Jeffrey K Cheng
Nilam Patel
Alex Yee
Randall A Lewis
Roland Eils
Rainer König
Bernhard Ø Palsson
University of California, San Diego · USGerman Cancer Research Center · DEHeidelberg University · DEMassachusetts Institute of Technology · US

Funding

CARDIOVASCULAR SURGERY/BIOENGINEERING TRAININGT32HL007089 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHIEN, SHU · 1985 to 2009
$9.3M
Network-based Analysis of Kinetics and RegulationR01GM068837 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 2003 to 2012
$2.4M
A Genome-Scale Regulated Metabolic Model of YeastR01GM071808 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 2004 to 2007
$2.3M
NHLBI NIH HHS T32 HL007089NIGMS NIH HHS 2R01GM068837_05A1NIGMS NIH HHS R01 GM068837NIGMS NIH HHS R01 GM071808
6 · The paper itself

Abstract

Metabolic interactions between multiple cell types are difficult to model using existing approaches. Here we present a workflow that integrates gene expression data, proteomics data and literature-based manual curation to model human metabolism within and between different types of cells. Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid. We apply the method to create models of brain energy metabolism that recapitulate metabolic interactions between astrocytes and various neuron types relevant to Alzheimer's disease. Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain. Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis.

Indexed as

Models, BiologicalAcetylcholineBrainComputer SimulationDatabases, FactualGene Expression ProfilingGenomicsGenotypeHumansMetabolic Networks and PathwaysPhenotypeAcetylcholine

Identifiers

PMID21102456
PMCPMC3140076
OpenAlexW2128776645

What OpenQuestion holds

Textmetadata
LicenceTDM
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.