Evidence map›Paper›PMID 33186464›Full record

ArticleDatabase : the journal of biological databases and curation2020

YQFC: a web tool to compare quantitative biological features between two yeast gene lists.

Wei-Sheng Wu, Lai-Ji Wang, Han-Chen Yen, Yan-Yuan Tseng

Open access · goldAbstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2020. 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
0.2field-weighted citation impact, top 49% 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, 3 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

4 authors at 2 institutions in 2 countries.

Wei-Sheng WuDepartment of Electrical Engineering, National Cheng Kung University, No.1, University Road, Tainan city, 70101 Taiwan.
Lai-Ji WangDepartment of Electrical Engineering, National Cheng Kung University, No.1, University Road, Tainan city, 70101 Taiwan.
Han-Chen YenDepartment of Electrical Engineering, National Cheng Kung University, No.1, University Road, Tainan city, 70101 Taiwan.
Yan-Yuan TsengCenter for Molecular Medicine and Genetics, Wayne State University, School of Medicine, 3127 Scott Hall, 540 East Canfield, Detroit, MI 48201, USA.
National Cheng Kung University · TWWayne State University · US

Funding

Database and Tools for Functional Inference and Mechanistic Insight into Somatic Cancer MutationsR01CA204962 · NCI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI LIANG, JIE, TSENG, YAN-YUAN · 2017 to 2019
$988k
NCI NIH HHS R01 CA204962
6 · The paper itself

Abstract

Nowadays high-throughput omics technologies are routinely used in biological research. From the omics data, researchers can easily get two gene lists (e.g. stress-induced genes vs. stress-repressed genes) related to their biological question. The next step would be to apply enrichment analysis tools to identify distinct functional/regulatory features between these two gene lists for further investigation. Although various enrichment analysis tools are already available, two challenges remain to be addressed. First, most existing tools are designed to analyze only one gene list, so they cannot directly compare two gene lists. Second, almost all existing tools focus on identifying the enriched qualitative features (e.g. gene ontology [GO] terms, pathways, domains, etc.). Many quantitative features (e.g. number of mRNA isoforms of a gene, mRNA half-life, protein half-life, transcriptional plasticity, translational efficiency, etc.) are available in the yeast, but no existing tools provide analyses on these quantitative features. To address these two challenges, here we present Yeast Quantitative Features Comparator (YQFC) that can directly compare various quantitative features between two yeast gene lists. In YQFC, we comprehensively collected and processed 85 quantitative features from the yeast literature and yeast databases. For each quantitative feature, YQFC provides three statistical tests (t-test, U test and KS test) to test whether this quantitative feature is statistically different between the two input yeast gene lists. The distinct quantitative features identified by YQFC may help researchers to study the underlying molecular mechanisms that differentiate the two input yeast gene lists. We believe that YQFC is a useful tool to expedite the biological research that uses high-throughput omics technologies. DATABASE URL: http://cosbi2.ee.ncku.edu.tw/YQFC/.

Indexed as

Databases, GeneticSaccharomyces cerevisiaeComputational BiologyProteinsSoftwareProteins

Identifiers

PMID33186464
PMCPMC7805433
OpenAlexW3099670593

What OpenQuestion 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 OpenQuestion graph.