CEBS Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data

Waters, Michael D.; Stasiewicz, Stanley; Merrick, B. Alex; Tomer, Kenneth B.; Bushel, Pierre R.; Paules, Richard S.; Stegman, Nancy; Nehls, Gerald J.; Yost, K.J.; Johnson, Carl; Gustafson, Scott F.; Xirasagar, Sandhya; Xiao, Nianqing; Huang, Chengcheng; Boyer, Paul D.; Chan, Denny D.; Pan, Qinyan; Gong, Huan; Taylor, John‐Stephen; Choi, Danielle; Rashid, Asif; Ahmed, Ayazaddin; Howle, Reese; Selkirk, James K.; Tennant, Raymond; Fostel, Jennifer

doi:10.1093/nar/gkm755

Cited by 126 publications

(106 citation statements)

References 37 publications

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“…The data are then released to the public domain in a number of public databases including PubChem (http://pubchem.ncbi.nlm. nih.gov/), CEBS (http://tools.niehs.nih.gov/cebs3/ui/; Waters et al, 2008) and ACToR (http://actor.epa.gov/actor/faces/ACToRHome.jsp; Judson et al, 2008).…”

Section: Quantitative High-throughput Screeningmentioning

confidence: 99%

Advances in high-throughput screening technology for toxicology

Hsu

Huang

Attene‐Ramos

et al. 2017

IJRAM

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Abstract:The US Tox21 collaboration utilises a quantitative high-throughput screening (qHTS) platform to efficiently profile a large number of environmental chemicals. qHTS combined with informatics facilitates chemical prioritisation for further in-depth toxicity testing and development of computational models to predict chemical toxicity. The NIH Chemical Genomics Center (NCGC), now part of the National Center for Advancing Translational Sciences (NCATS), is a key contributor during all phases of the Tox21 collaboration, from assay development and compound screening to data analysis and model building. Since 2011, the Tox21/NCGC has been profiling the phase 2 Tox21 library of approximately 10,000 (10K) environmental chemicals and drugs. The advances in HTS assays and qHTS screens against the Tox21's and other chemical libraries are described in this review.

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Section: Quantitative High-throughput Screeningmentioning

confidence: 99%

Advances in high-throughput screening technology for toxicology

Hsu

Huang

Attene‐Ramos

et al. 2017

IJRAM

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“…A study titled "Drug Matrix In Vitro Toxicogenomic Study-Rat Hepatocytes [Affymetrix]" [12,13] was selected for further analysis. Although drug-treatment studies performed on normal human cell lines would be preferred for repurposed disease prediction, for this query, all human studies were only carried out for cancer cell lines or virus-infected cells.…”

Section: Study Selection From the Basespace Correlation Enginementioning

confidence: 99%

Demonstration Study: A Protocol to Combine Online Tools and Databases for Identifying Potentially Repurposable Drugs

Chattopadhyay¹,

Ganapathiraju

2017

Data

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Abstract:Traditional methods for discovery and development of new drugs can be very time-consuming and expensive processes because they include several stages, such as compound identification, pre-clinical and clinical trials before the drug is approved by the U.S. Food and Drug Administration (FDA). Therefore, drug repurposing, namely using currently FDA-approved drugs as therapeutics for other diseases than what they are originally prescribed for, is emerging to be a faster and more cost-effective alternative to current drug discovery methods. In this paper, we have described a three-step in silico protocol for analyzing transcriptomics data using online databases and bioinformatics tools for identifying potentially repurposable drugs. The efficacy of this protocol was evaluated by comparing its predictions with the findings of two case studies of recently reported repurposed drugs: HIV treating drug zidovudine for the treatment of dry age-related macular degeneration and the antidepressant imipramine for small-cell lung carcinoma. The proposed protocol successfully identified the published findings, thus demonstrating the efficacy of this method. In addition, it also yielded several novel predictions that have not yet been published, including the finding that imipramine could potentially treat Severe Acute Respiratory Syndrome (SARS), a disease that currently does not have any treatment or vaccine. Since this in silico protocol is simple to use and does not require advanced computer skills, we believe any motivated participant with access to these databases and tools would be able to apply it to large datasets to identify other potentially repurposable drugs in the future.

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“…sample characteristics, technologies used, type of measurements made) from experiments employing a combination of technologies [62]. Publicly available data from the ToxCast and the TG-GATEs projects are used as a benchmark [6,10,38,43,45,53]. The SEURAT-1 cluster has selected reference compounds, including doxorubicin and compiled extensive information on them in a semantic mediawiki (wiki.toxbank.net) [53].…”

Section: Surveying the Landscape Of Databases For Cancer Biology And mentioning

confidence: 99%

Cancer Biology, Toxicology and Alternative Methods Development Go Hand‐in‐Hand

Kohonen

Ceder

Smit

et al. 2014

Basic Clin Pharma Tox

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Toxicological research faces the challenge of integrating knowledge from diverse fields and novel technological developments generally in the biological and medical sciences. We discuss herein the fact that the multiple facets of cancer research, including discovery related to mechanisms, treatment and diagnosis, overlap many up and coming interest areas in toxicology, including the need for improved methods and analysis tools. Common to both disciplines, in vitro and in silico methods serve as alternative investigation routes to animal studies. Knowledge on cancer development helps in understanding the relevance of chemical toxicity studies in cell models, and many bioinformatics-based cancer biomarker discovery tools are also applicable to computational toxicology. Robotics-aided, cell-based, high-throughput screening, microscale immunostaining techniques and gene expression profiling analyses are common tools in cancer research, and when sequentially combined, form a tiered approach to structured safety evaluation of thousands of environmental agents, novel chemicals or engineered nanomaterials. Comprehensive tumour data collections in databases have been translated into clinically useful data, and this concept serves as template for computer-driven evaluation of toxicity data into meaningful results. Future 'cancer research-inspired knowledge management' of toxicological data will aid the translation of basic discovery results and chemicals-and materials-testing data to information relevant to human health and environmental safety.Assessing the intrinsic toxicological properties of environmental agents is central to defining hazard within the paradigm of human risk assessment used now for decades [1]. A constantly increasing number of chemicals and engineered nanomaterials (ENMs) emphasize the need of applying novel tools and screening technologies outside of the standard, both lengthy and expensive, rodent toxicological tests traditionally used in such work [1][2][3][4][5][6][7][8][9][10][11][12][13]. Especially considered for the future innovation of novel ENMs, safety evaluations should be integrated proactively and efficiently already in the material and product development phase [9,12]. Summarized under a concept termed 'Toxicity Testing in the 21st Century' or 'Tox21', biochemical and cell-based in vitro assays coupled with bioinformatics and modelling-driven in silico assays are now considered key to transforming toxicology from a previously animal-based testing practice into a computational science built on systems biology [2,4,6,[9][10][11]13]. The resulting novel research field is variably termed 'systems toxicology', 'toxicogenomics' or 'computational toxicology' [3,4,8,14,15]. Such effort typically relies on informatics-driven and modelling-based analyses of results from several experimental systems and data-rich technologies for measuring pools of biological molecules, such as mRNAs, the overall aim being to interdependently analyse toxicity data and profiling results for understanding...

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CEBS Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data

Cited by 126 publications

References 37 publications

Advances in high-throughput screening technology for toxicology

Advances in high-throughput screening technology for toxicology

Demonstration Study: A Protocol to Combine Online Tools and Databases for Identifying Potentially Repurposable Drugs

Cancer Biology, Toxicology and Alternative Methods Development Go Hand‐in‐Hand

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