Literature DB >> 24048354

Toxygates: interactive toxicity analysis on a hybrid microarray and linked data platform.

Johan Nyström-Persson1, Yoshinobu Igarashi, Maori Ito, Mizuki Morita, Noriyuki Nakatsu, Hiroshi Yamada, Kenji Mizuguchi.   

Abstract

MOTIVATION: In early stage drug development, it is desirable to assess the toxicity of compounds as quickly as possible. Biomarker genes can help predict whether a candidate drug will adversely affect a given individual, but they are often difficult to discover. In addition, the mechanism of toxicity of many drugs and common compounds is not yet well understood. The Japanese Toxicogenomics Project provides a large database of systematically collected microarray samples from rats (liver, kidney and primary hepatocytes) and human cells (primary hepatocytes) after exposure to 170 different compounds in different dosages and at different time intervals. However, until now, no intuitive user interface has been publically available, making it time consuming and difficult for individual researchers to explore the data.
RESULTS: We present Toxygates, a user-friendly integrated analysis platform for this database. Toxygates combines a large microarray dataset with the ability to fetch semantic linked data, such as pathways, compound-protein interactions and orthologs, on demand. It can also perform pattern-based compound ranking with respect to the expression values of a set of relevant candidate genes. By using Toxygates, users can freely interrogate the transcriptome's response to particular compounds and conditions, which enables deep exploration of toxicity mechanisms.

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Year:  2013        PMID: 24048354     DOI: 10.1093/bioinformatics/btt531

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  10 in total

1.  Open TG-GATEs: a large-scale toxicogenomics database.

Authors:  Yoshinobu Igarashi; Noriyuki Nakatsu; Tomoya Yamashita; Atsushi Ono; Yasuo Ohno; Tetsuro Urushidani; Hiroshi Yamada
Journal:  Nucleic Acids Res       Date:  2014-10-13       Impact factor: 16.971

2.  Workshop report: Identifying opportunities for global integration of toxicogenomics databases, 26-27 June 2013, Research Triangle Park, NC, USA.

Authors:  Diana M Hendrickx; Rebecca R Boyles; Jos C S Kleinjans; Allen Dearry
Journal:  Arch Toxicol       Date:  2014-10-19       Impact factor: 5.153

3.  Predicting target proteins for drug candidate compounds based on drug-induced gene expression data in a chemical structure-independent manner.

Authors:  Yoshiyuki Hizukuri; Ryusuke Sawada; Yoshihiro Yamanishi
Journal:  BMC Med Genomics       Date:  2015-12-18       Impact factor: 3.063

4.  Interactive Toxicogenomics: Gene set discovery, clustering and analysis in Toxygates.

Authors:  Johan Nyström-Persson; Yayoi Natsume-Kitatani; Yoshinobu Igarashi; Daisuke Satoh; Kenji Mizuguchi
Journal:  Sci Rep       Date:  2017-05-03       Impact factor: 4.379

5.  Toxic Dose prediction of Chemical Compounds to Biomarkers using an ANOVA based Gene Expression Analysis.

Authors:  Mohammad Nazmol Hasan; Zobaer Akond; Md Jahangir Alam; Anjuman Ara Begum; Moizur Rahman; Md Nurul Haque Mollah
Journal:  Bioinformation       Date:  2018-07-31

6.  Decision Variants for the Automatic Determination of Optimal Feature Subset in RF-RFE.

Authors:  Qi Chen; Zhaopeng Meng; Xinyi Liu; Qianguo Jin; Ran Su
Journal:  Genes (Basel)       Date:  2018-06-15       Impact factor: 4.096

7.  Assessment of Drugs Toxicity and Associated Biomarker Genes Using Hierarchical Clustering.

Authors:  Mohammad Nazmol Hasan; Masuma Binte Malek; Anjuman Ara Begum; Moizur Rahman; Md Nurul Haque Mollah
Journal:  Medicina (Kaunas)       Date:  2019-08-08       Impact factor: 2.430

8.  A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data.

Authors:  Ran Su; Haitang Yang; Leyi Wei; Siqi Chen; Quan Zou
Journal:  PLoS Comput Biol       Date:  2022-09-07       Impact factor: 4.779

9.  ZBIT Bioinformatics Toolbox: A Web-Platform for Systems Biology and Expression Data Analysis.

Authors:  Michael Römer; Johannes Eichner; Andreas Dräger; Clemens Wrzodek; Finja Wrzodek; Andreas Zell
Journal:  PLoS One       Date:  2016-02-16       Impact factor: 3.240

10.  Robust Co-clustering to Discover Toxicogenomic Biomarkers and Their Regulatory Doses of Chemical Compounds Using Logistic Probabilistic Hidden Variable Model.

Authors:  Mohammad Nazmol Hasan; Md Masud Rana; Anjuman Ara Begum; Moizur Rahman; Md Nurul Haque Mollah
Journal:  Front Genet       Date:  2018-11-01       Impact factor: 4.599

  10 in total

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