Evidence map›Paper›PMID 22934043›Full record

ArticleFrontiers in physiology2012

Understanding complexity in neurodegenerative diseases: in silico reconstruction of emergence.

Alexey Kolodkin, Evangelos Simeonidis, Rudi Balling, Hans V Westerhoff

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

6 citing papers in PubMed, 21 citations in OpenAlex.

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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

4 authors at 3 institutions in 4 countries.

Alexey KolodkinLuxembourg Centre for Systems Biomedicine, University of Luxembourg Esch-sur-Alzette, Luxembourg.
Evangelos Simeonidis
Rudi Balling
Hans V Westerhoff
University of Luxembourg · LUInstitute for Systems Biology · USUniversity of Manchester · GB

Funding

Biotechnology and Biological Sciences Research Council BB/C008219/1Biotechnology and Biological Sciences Research Council BB/I004688/1Biotechnology and Biological Sciences Research Council BB/I004696/1Biotechnology and Biological Sciences Research Council BB/I00470X/1
6 · The paper itself

Abstract

Healthy functioning is an emergent property of the network of interacting biomolecules that comprise an organism. It follows that disease (a network shift that causes malfunction) is also an emergent property, emerging from a perturbation of the network. On the one hand, the biomolecular network of every individual is unique and this is evident when similar disease-producing agents cause different individual pathologies. Consequently, a personalized model and approach for every patient may be required for therapies to become effective across mankind. On the other hand, diverse combinations of internal and external perturbation factors may cause a similar shift in network functioning. We offer this as an explanation for the multi-factorial nature of most diseases: they are "systems biology diseases," or "network diseases." Here we use neurodegenerative diseases, like Parkinson's disease (PD), as an example to show that due to the inherent complexity of these networks, it is difficult to understand multi-factorial diseases with simply our "naked brain." When describing interactions between biomolecules through mathematical equations and integrating those equations into a mathematical model, we try to reconstruct the emergent properties of the system in silico. The reconstruction of emergence from interactions between huge numbers of macromolecules is one of the aims of systems biology. Systems biology approaches enable us to break through the limitation of the human brain to perceive the extraordinarily large number of interactions, but this also means that we delegate the understanding of reality to the computer. We no longer recognize all those essences in the system's design crucial for important physiological behavior (the so-called "design principles" of the system). In this paper we review evidence that by using more abstract approaches and by experimenting in silico, one may still be able to discover and understand the design principles that govern behavioral emergence.

Indexed as

computer modelingnetwork diseasesneurodegenerative diseaseParkinson's disease (PD)strong emergencesystems biologysystems biology diseasesweak emergence

Identifiers

PMID22934043
PMCPMC3429063
OpenAlexW2145012579

What OpenQuestion holds

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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.