Evidence map›Paper›PMID 25576845›Full record

ReviewCurrent opinion in biotechnology2015

Computing the functional proteome: recent progress and future prospects for genome-scale models.

Edward J O'Brien, Bernhard O Palsson

Abstract readReview
In one paragraph

Review in Current opinion in biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Searching for principles of microbial physiology.FEMS microbiology reviews · 2020
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Constraint-based modeling in microbial food biotechnology.Biochemical Society transactions · 2018
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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.

Edward J O'BrienBioinformatics and Systems Biology Program, University of California, San Diego, United States; Department of Bioengineering, University of California, San Diego, United States.
Bernhard O PalssonBioinformatics and Systems Biology Program, University of California, San Diego, United States; Department of Bioengineering, University of California, San Diego, United States; Department of Pediatrics, University of California, San Diego, United States; Novo Nordisk Center for Biosustainability, The Danish Technical University, Denmark. Electronic address: palsson@ucsd.edu.

Funding

GENOMICALLY BASED MODELS FOR ANTIBIOTIC DEVELOPMENTR01GM057089 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 1998 to 2021
$6.9M
Multiscale Molecular Systems Biology: Reconstruction and Model OptimizationU01GM102098 · NIGMS · STANFORD UNIVERSITY · PI SAUNDERS, MICHAEL ALAN · 2012 to 2016
$1.8M
NIGMS NIH HHS R01 GM057089NIGMS NIH HHS U01 GM102098
6 · The paper itself

Abstract

Constraint-based models enable the computation of feasible, optimal, and realized biological phenotypes from reaction network reconstructions and constraints on their operation. To date, stoichiometric reconstructions have largely focused on metabolism, resulting in genome-scale metabolic models (M-Models). Recent expansions in network content to encompass proteome synthesis have resulted in models of metabolism and protein expression (ME-Models). ME-Models advance the predictions possible with constraint-based models from network flux states to the spatially resolved molecular composition of a cell. Specifically, ME-Models enable the prediction of transcriptome and proteome allocation and limitations, and basal expression states and regulatory needs. Continued expansion in reconstruction content and constraints will result in an increasingly refined representation of cellular composition and behavior.

Indexed as

AnimalsGene ExpressionGenomeHumansModels, BiologicalPhenotypeProteomeProteome

Identifiers

PMID25576845
PMCPMC4495013

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.