ReviewMolecular biology of the cell2014
What's that gene (or protein)? Online resources for exploring functions of genes, transcripts, and proteins.
Review in Molecular biology of the cell, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Studying Translesion DNA Synthesis Using Xenopus In Vitro Systems.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Differential gene expression profile of multinodular goiter.PloS one · 2022Article
- Genomic association with pathogen carriage in bighorn sheep (Ecology and evolution · 2021Article
- Effect of Tension on Human Periodontal Ligament Cells: Systematic Review and Network Analysis.Frontiers in bioengineering and biotechnology · 2021Article
- Proteomic data on the nuclear interactome of human MCM9.Data in brief · 2016Article
- Protein Sequence Annotation Tool (PSAT): a centralized web-based meta-server for high-throughput sequence annotations.BMC bioinformatics · 2016Article
- Only one health, and so many omics.Cancer cell international · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The genomic era has enabled research projects that use approaches including genome-scale screens, microarray analysis, next-generation sequencing, and mass spectrometry-based proteomics to discover genes and proteins involved in biological processes. Such methods generate data sets of gene, transcript, or protein hits that researchers wish to explore to understand their properties and functions and thus their possible roles in biological systems of interest. Recent years have seen a profusion of Internet-based resources to aid this process. This review takes the viewpoint of the curious biologist wishing to explore the properties of protein-coding genes and their products, identified using genome-based technologies. Ten key questions are asked about each hit, addressing functions, phenotypes, expression, evolutionary conservation, disease association, protein structure, interactors, posttranslational modifications, and inhibitors. Answers are provided by presenting the latest publicly available resources, together with methods for hit-specific and data set-wide information retrieval, suited to any genome-based analytical technique and experimental species. The utility of these resources is demonstrated for 20 factors regulating cell proliferation. Results obtained using some of these are discussed in more depth using the p53 tumor suppressor as an example. This flexible and universally applicable approach for characterizing experimental hits helps researchers to maximize the potential of their projects for biological discovery.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.