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Example Projects

Thomas Luechtefeld edited this page May 15, 2019 · 1 revision

The below projects help describe use cases for sysrev.com.

Hallmark and key characteristics mapping (sysrev.com/p/3588)

This project is intended to support work being done by the Cancer and Environmental Mixtures Committee: Assay and Biomarker Subgroup, as well as provide input into the National Toxicology Program “Converging on Cancer” workshop being held in April 2019 and support the NTP’s Strategic Health Effects Innovation on Carcinogenicity Testing for the 21st Century. The aim of this literature review is to identify novel assays and biomarkers that map to the hallmarks of cancer and the key characteristics of carcinogens. The overarching goals of developing such a literature database include informing new testing strategies and frameworks to incorporate mechanistic data into cancer risk assessment and developing effective screening tools to detect the carcinogenic potential of environmental chemicals (including mixtures). Other downstream applications could ultimately include engineering safer products and designing more effective multi-target therapeutics.

EBTC - Effects on the liver as observed in experimental animals after dosing of 10 specified compounds (sysrev.com/p/100)

The evidence based toxicology consortium at Johns Hopkins used sysrev to screen 5818 pubmed articles for a systematic review of liver toxicity. Related labels such as species and compounds used in the included articles were extracted as well. All of the data generated for this review is openly available at sysrev.com/p/100.

Vitamin C Cancer Trials (sysrev.com/p/6737)

A Review of clinicaltrials.gov Vitamin C Clinical Trials. This analysis was performed to analyze how vitamin C prevalence, combinations, success and other factors relating to the use of ascorbate in cancer clinical trials change over time.

Gene Hunter (sysrev.com/p/3144)

Gene Hunter was created to provide a public dataset for models that automatically identifying genes in text. Identifying genes in text takes us a step closer to finding their relevance in different diseases and therapies. In three weeks 10 reviewers annotated genes in 10,000 sentences.