Evidence map›Paper›PMID 26085824›Full record

ArticleBiological theory2015

Engineering and Biology: Counsel for a Continued Relationship.

Brett Calcott, Arnon Levy, Mark L Siegal, Orkun S Soyer, Andreas Wagner

Abstract read
In one paragraph

Article in Biological theory, 2015. 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. Article
  2. Article
  3. Review
  4. Article
  5. 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.

Brett CalcottSchool of Life Sciences, Arizona State University, Tempe, AZ, USA.
Arnon LevyHebrew University of Jerusalem, Jerusalem, Israel.
Mark L SiegalDepartment of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA.
Orkun S SoyerSchool of Life Sciences, University of Warwick, Coventry, UK.
Andreas WagnerInstitute of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland. Swiss Institute of Bioinformatics, Lausanne, Switzerland. Santa Fe Institute, Santa Fe, NM, USA.

Funding

Sequencing yeast lines to measure rates of neutral and deleterious mutationsR01GM097415 · NIGMS · NEW YORK UNIVERSITY · PI PETROV, DMITRI, SIEGAL, MARK L · 2011 to 2014
$2.3M
Sources and consequences of phenotypic variation in complex regulatory networksR01GM086673 · NIGMS · NEW YORK UNIVERSITY · PI SIEGAL, MARK L · 2010 to 2013
$929k
NIGMS NIH HHS R01 GM086673NIGMS NIH HHS R01 GM097415
6 · The paper itself

Abstract

Biologists frequently draw on ideas and terminology from engineering. Evolutionary systems biology-with its circuits, switches, and signal processing-is no exception. In parallel with the frequent links drawn between biology and engineering, there is ongoing criticism against this cross-fertilization, using the argument that over-simplistic metaphors from engineering are likely to mislead us as engineering is fundamentally different from biology. In this article, we clarify and reconfigure the link between biology and engineering, presenting it in a more favorable light. We do so by, first, arguing that critics operate with a narrow and incorrect notion of how engineering actually works, and of what the reliance on ideas from engineering entails. Second, we diagnose and diffuse one significant source of concern about appeals to engineering, namely that they are inherently and problematically metaphorical. We suggest that there is plenty of fertile ground left for a continued, healthy relationship between engineering and biology.

Indexed as

AdaptationismDesignEngineeringEvolutionary systems biologyEvolvabilityGene regulationMetaphor

Identifiers

PMID26085824
PMCPMC4465806

What OpenQuestion holds

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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.