NanoMiner - integrative human transcriptomics data resource for nanoparticle research

PLoS One. 2013 Jul 12;8(7):e68414. doi: 10.1371/journal.pone.0068414. Print 2013.

Abstract

The potential impact of nanoparticles on the environment and on human health has attracted considerable interest worldwide. The amount of transcriptomics data, in which tissues and cell lines are exposed to nanoparticles, increases year by year. In addition to the importance of the original findings, this data can have value in broader context when combined with other previously acquired and published results. In order to facilitate the efficient usage of the data, we have developed the NanoMiner web resource (http://nanominer.cs.tut.fi/), which contains 404 human transcriptome samples exposed to various types of nanoparticles. All the samples in NanoMiner have been annotated, preprocessed and normalized using standard methods that ensure the quality of the data analyses and enable the users to utilize the database systematically across the different experimental setups and platforms. With NanoMiner it is possible to 1) search and plot the expression profiles of one or several genes of interest, 2) cluster the samples within the datasets, 3) find differentially expressed genes in various nanoparticle studies, 4) detect the nanoparticles causing differential expression of selected genes, 5) analyze enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) terms for the detected genes and 6) search the expression values and differential expressions of the genes belonging to a specific KEGG pathway or Gene Ontology. In sum, NanoMiner database is a valuable collection of microarray data which can be also used as a data repository for future analyses.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cluster Analysis
  • Gene Expression Profiling*
  • Gene Expression Regulation
  • Humans
  • Molecular Sequence Annotation
  • Nanoparticles / chemistry*
  • Nanotechnology*
  • Particulate Matter
  • Software*
  • Statistics as Topic*
  • Transcriptome / genetics*

Substances

  • Particulate Matter

Grants and funding

The project is supported by the Seventh Framework Programme of the European Commission FP7-NANOMMUNE, no 214281 (coordinator: BF) and Academy of Finland Finnish Programme for Centres of Excellence in Signal Processing no 129657, no 134117 (to RA), no 129529 (to RL), no 140019 (to RL) and the Centre of Excellence in Molecular systems Immunology and Physiology Research, no 250114 (to RL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.