Evidence map›Paper›PMID 37410917›Full record

ArticleDatabase : the journal of biological databases and curation2023

CropGF: a comprehensive visual platform for crop gene family mining and analysis.

Jingtian Xu, Can Zhu, Minzeng Su, Sida Li, Haoyu Chao, Ming Chen

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Jingtian XuDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Can ZhuDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Minzeng SuDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Sida LiDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Haoyu ChaoDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.
Ming ChenDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-9677-1699

Funding

Jiangsu Collaborative Innovation Center for Modern Crop Production and Collaborative Innovation Center for Modern Crop Production co-sponsored by province and ministryNational Natural Sciences Foundation of China 32070677 32261133526 32270709SRTP Program of Zhejiang University Y202204165the 151 Talent Project, and S&T Innovation Leader of Zhejiang Province
6 · The paper itself

Abstract

A gene family refers to a group of genes that share a common ancestry and encode proteins or RNA molecules with similar functions or structural features. Gene families play a crucial role in determining the traits of plants and can be utilized to develop new crop varieties. Therefore, a comprehensive database of gene family is significant for gaining deep insight into crops. To address this need, we have developed CropGF (https://bis.zju.edu.cn/cropgf), a comprehensive visual platform that encompasses six important crops (rice, wheat, maize, barley, sorghum and foxtail millet) and one model plant (Arabidopsis), as well as genomics, transcriptomics and proteomics data for gene family mining and analysis, covering a total of 314 611 genes and 4399 types of domains. CropGF provides a versatile search system that allows for the identification of gene families and their members in a single crop or multiple crops. Users can customize their search based on gene family domains and/or homology using keywords or BLAST. To enhance usability, we have collected the corresponding ID information from various public databases for both genes and domains. Furthermore, CropGF comprises numerous downstream analysis modules, such as ka/ks analysis, phylogenetic tree construction, subcellular localization analysis and more. These visually-displayed modules provide intuitive insights into gene expression patterns, gene family expansion and functional relationships across different molecular levels and different species. We believe that CropGF will be a valuable resource for deep mining and analysis in future studies of crop gene families. Database URL https://bis.zju.edu.cn/cropgf.

Indexed as

Gene Expression ProfilingSetaria PlantGene Expression Regulation, PlantGenomicsPhylogenyPlant ProteinsZea maysPlant Proteins

Identifiers

PMID37410917
PMCPMC10325484

What Socratic holds

Textmetadata
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 Socratic graph.