Evidence map›Paper›PMID 24371190›Full record

ArticleJournal of genetics2013

Time for the zebrafish ENCODE.

Sridhar Sivasubbu, Chetana Sachidanandan, Vinod Scaria

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-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

7 citing papers in PubMed, 14 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

3 authors at 1 institution in 1 country.

Sridhar SivasubbuGenomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110 007, India. s.sivasubbu@igib.res.in.
Chetana Sachidanandan
Vinod Scaria
Institute of Genomics and Integrative Biology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomics research in recent years, especially the human ENCODE project, have made great strides in understanding the genomic and epigenomic structure and organization of humans. These advances promise a new era of precision medicine, through a better understanding of the genomic correlates of human physiology and promise to offer precise and personalized preventive and therapeutic options. The translation of genome-scale maps of genomic and epigenomic markers to clinically relevant information and further to medical practice await functional validation of the genomic features identified through these large-scale efforts. Such studies must essentially be done in model systems where it is possible to model physiological and pathological processes and enquire how they could be modulated by genomic elements and epigenomic signatures. The availability of large number of personal genomes and maps of genomic variations at population scale has created an acute necessity for model systems to model phenotypic and molecular effects of variations, especially in regulatory regions. Efforts to create orthologous maps have been underway in other model systems including Caenorhabditis elegans and Drosophila through the modENCODE programe and in Mus musculus through the mouse ENCODE. We propose that the enormous wealth of disease models and excellent tools to engineer genomes in zebrafish could be effectively capitalized towards making it an effective and widely used model system for precision medicine. This would be possible only through a concerted and systematic effort to create orthologous genomic and epigenomic maps for zebrafish.We discuss how the present understanding and genome-scale methodologies available in this model organism could be effectively used towards realizing this goal.

Indexed as

Databases, GeneticAnimalsGenomicsHumansInformation DisseminationZebrafish

Identifiers

PMID24371190
OpenAlexW2116152477

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.