Evidence map›Paper›PMID 22267905›Full record

ArticleEvolutionary bioinformatics online2012

EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.

Benjamin Linard, Ngoc Hoan Nguyen, Francisco Prosdocimi, Olivier Poch, Julie D Thompson

Abstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Visualizing time-related data in biology, a review.Briefings in bioinformatics · 2014
    Review
  2. MSV3d: database of human MisSense Variants mapped to 3D protein structure.Database : the journal of biological databases and curation · 2012
    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.

Benjamin LinardLaboratoire De Bioinformatique Et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire CNRS/INSERM/UDS, Illkirch, France.
Ngoc Hoan Nguyen
Francisco Prosdocimi
Olivier Poch
Julie D Thompson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.

Indexed as

data miningdata representationdata visualizationevolutionary historymultilevel data analysissystems biology

Identifiers

PMID22267905
PMCPMC3256995

What Socratic 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 Socratic graph.