Evidence map›Paper›PMID 21641560›Full record

ArticleGenomics, proteomics & bioinformatics2011

EST-based identification of genes expressed in skeletal muscle of the mandarin fish (Siniperca chuatsi).

Feng Ding, Wuying Chu, Peng Cui, Meng Tao, Ruixue Zhou, Falan Zhao, Songnian Hu, Jianshe Zhang

Open access · goldAbstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

8 authors at 3 institutions in 1 country.

Feng DingCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
Wuying Chu
Peng Cui
Meng Tao
Ruixue Zhou
Falan Zhao
Songnian Hu
Jianshe Zhang
Changsha University · CNBeijing Institute of Genomics · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To enrich the genomic information of the commercially important fish species, we obtained 5,063 high-quality expressed sequence tags (ESTs) from the muscle cDNA database of the mandarin fish (Siniperca chuatsi). Clustering analysis yielded 1,625 unique sequences including 443 contigs (from 3,881 EST sequences) and 1,182 singletons. BLASTX searches showed that 959 unique sequences shared homology to proteins in the NCBI non-redundant database. A total of 740 unique sequences were functionally annotated using Gene Ontology. The 1,625 unique sequences were assigned to Kyoto Encyclopedia of Genes and Genomes reference pathways, and the results indicated that transcripts participating in nucleotide metabolism and amino acid metabolism are relatively abundant in S. chuatsi. Meanwhile, we identified 15 genes to be abundantly expressed in muscle of the mandarin fish. These genes are involved in muscle structural formation and regulation of muscle differentiation and development. The most remarkable gene in S. chuatsi is nuclease diphosphate kinase B, which is represented by 449 EST sequences accounting for 8.86% of the total EST sequences. Our work provides a transcript profile expressed in the white muscle of the mandarin fish, laying down a foundation in better understanding of fish genomics.

Indexed as

Expressed Sequence TagsGene Expression ProfilingAnimalsMetabolomeMolecular Sequence AnnotationMuscle, SkeletalNucleoside-Diphosphate KinasePerciformesNucleoside-Diphosphate Kinase

Identifiers

PMID21641560
PMCPMC5054145
OpenAlexW2043145319

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.