Semantic analysis of thyroid cancer cell proteins obtained from rare research opportunities

Research in natural sciences is mainly done by means of experiments. Some of those experiments such as spaceflight-dependent experiments are extremely laborious, complex and expensive. Hence, they often remain rare events with little chances of statistical tests and possibilities of repetition. In order to make each single event as valuable as possible, a sophisticated comparison of experimental data received with the hundreds of millions of computer-stored documents appears necessary. We used results of an earlier study on proteome analysis of microgravity-exposed human thyroid cancer cells, selected twenty proteins which appeared gravity sensitive and investigated whether their change observed in cells under the loss of gravity could cause health problems in astronauts. Using network analysis via Knowledge Explorer (KE) we searched the literature for diseases related to one or more of the selected proteins. After using Linked Open Data (LOD) and other public resources to establish a comprehensive semantic knowledgebase around functional properties of the selected proteins, the collection's network was used to query a set of databases for the proteins' involvement in biosystems and human diseases. Finally, possible countermeasures could be proposed.