Publications

Publications

APBN News Article

published 5 October 2016

Link to Asia Pacific Biotech News website:
Tobacco Harm Reduction and Reduced-Risk Products

Drug Discovery News Article

published 15 September 2016

Link to Drug Discovery News website:
Crowdsourcing lung biology

R&D Magazine Article

published 9 September 2016

Link to R&D Magazine website:
21st Century Toxicology & In Vitro-Based Testing Methodologies

Front Line Genomics Article

published 8 September 2016

Link to Front Line Genomics website:
Could transcriptomics predict exposure to toxicants?

American Laboratory Article

published 3 August 2016

Link to American Laboratory website:
Community-Verified Biological Network Models Show Promise for Toxicology, Drug Discovery

Drug Discovery Today Article

published 3 August 2016

Link to Drug Discovery Today website:
Community verified biological network models show promise for toxicology and drug discovery

Libertas Academica

published 3 August 2016

Link to Libertas Academica website:
Public Science Insights: Community verified biological network models

Clinical OMICS Article

published August 2016

Link to Clinical OMICS issue:
Clinical OMICS August 2016

News Medical Article

published 26 July 2016

Link to News Medical website:
Novel community-produced biological network models hold potential in drug discovery and toxicology

News Medical Article

published 22 July 2016

Link to News Medical website:
Predictive power of computational toxicology demonstrated with crowd-sources scientific challenge

Pages

Testimonials

Assessing toxicant exposure from blood data alone is a complex and fascinating undertaking. The tasks set in the Systems Toxicology Computational Challenge allowed us to address this issue, while objectively testing our computational methodologies. As computational biologists we are always looking for new data to work with, and it is of huge value to have access to the high quality datasets provided by sbv IMPROVER.

İsmail Bilgen

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sbv IMPROVER is shaping up to be the new gold-standard in assessing scientific validity.

Ashutosh Malhotra, M.Sc.

On the Network Verification Challenge

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The first sbv IMPROVER challenge offered an excellent opportunity to test and develop different approaches to classifying clinical samples based on gene expression.

Dr. Adi Laurentiu Tarca

On the Diagnostic Signature Challenge

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