Evidence map›Paper›PMID 27431524›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2016

Energy and time determine scaling in biological and computer designs.

Melanie Moses, George Bezerra, Benjamin Edwards, James Brown, Stephanie Forrest

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. How does mobility help distributed systems compute?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Article
  4. Article
  5. The major synthetic evolutionary transitions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2016
    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

5 authors.

Melanie MosesDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA Department of Biology, University of New Mexico, Albuquerque, NM, USA The Santa Fe Institute, Santa Fe, NM, USA melaniem@cs.unm.edu.ORCID 0000-0002-8848-9554
George BezerraDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA.
Benjamin EdwardsDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA.
James BrownDepartment of Biology, University of New Mexico, Albuquerque, NM, USA The Santa Fe Institute, Santa Fe, NM, USA.
Stephanie ForrestDepartment of Computer Science, University of New Mexico, Albuquerque, NM, USA Department of Biology, University of New Mexico, Albuquerque, NM, USA The Santa Fe Institute, Santa Fe, NM, USA.

Funding

Integrated, Interdisciplinary, Inter-university PHD Program Computational BiologyT32EB009414 · NIBIB · UNIVERSITY OF NEW MEXICO · PI SMITH, FELISA ANNAMARIE · 2009 to 2013
$989k
NIBIB NIH HHS T32 EB009414
6 · The paper itself

Abstract

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

Indexed as

Basal MetabolismElectric Power SuppliesMicrocomputersAnimalsBiological EvolutionMammalsModels, BiologicalModels, TheoreticalSelection, Geneticcomputer architectureevolutionary transitionsmetabolismnetworksscaling

Identifiers

PMID27431524
PMCPMC4958940

What OpenQuestion holds

Textmetadata
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.