Evidence map›Paper›PMID 26942765›Full record

ArticlePLoS computational biology2016

Reconstruction of Tissue-Specific Metabolic Networks Using CORDA.

André Schultz, Amina A Qutub

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 1 pooled it
8.0field-weighted citation impact, top 2% 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

78 citing papers in PubMed, 1 synthesis or guideline pooled it, 155 citations in OpenAlex.

  1. Preclinical techniques to investigate exercise training in vascular pathophysiology.American journal of physiology. Heart and circulatory physiology · 2021
    Pooled it
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  12. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
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  14. Bioinformatics advances · 2025
    Article
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18 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

2 authors at 1 institution in 1 country.

André SchultzDepartment of Bioengineering, Rice University, Houston, Texas, United States of America.
Amina A QutubDepartment of Bioengineering, Rice University, Houston, Texas, United States of America.
Rice University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human metabolism involves thousands of reactions and metabolites. To interpret this complexity, computational modeling becomes an essential experimental tool. One of the most popular techniques to study human metabolism as a whole is genome scale modeling. A key challenge to applying genome scale modeling is identifying critical metabolic reactions across diverse human tissues. Here we introduce a novel algorithm called Cost Optimization Reaction Dependency Assessment (CORDA) to build genome scale models in a tissue-specific manner. CORDA performs more efficiently computationally, shows better agreement to experimental data, and displays better model functionality and capacity when compared to previous algorithms. CORDA also returns reaction associations that can greatly assist in any manual curation to be performed following the automated reconstruction process. Using CORDA, we developed a library of 76 healthy and 20 cancer tissue-specific reconstructions. These reconstructions identified which metabolic pathways are shared across diverse human tissues. Moreover, we identified changes in reactions and pathways that are differentially included and present different capacity profiles in cancer compared to healthy tissues, including up-regulation of folate metabolism, the down-regulation of thiamine metabolism, and tight regulation of oxidative phosphorylation.

Indexed as

AlgorithmsMetabolomeModels, BiologicalComputer SimulationHumansMetabolomicsNeoplasm ProteinsNeoplasmsOrgan SpecificityProteomeSignal TransductionNeoplasm ProteinsProteome

Identifiers

PMID26942765
PMCPMC4778931
OpenAlexW2291465340

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.