  Biomedical research results are being published at a high rate, and with
existing search engines, the vast amount of published work is usually easily
accessible. However, reproducing published results, either experimental data or
observations is often not viable. In this work, we propose a framework to
overcome some of the issues of reproducing previous research, and to ensure
re-usability of published information. We present here a framework that
utilizes the results from state-of-the-art biomedical literature mining,
biological system modeling and analysis techniques, and provides means to
scientists to assemble and reason about information from voluminous, fragmented
and sometimes inconsistent literature. The overall process of automated
reading, assembly and reasoning can speed up discoveries from the order of
decades to the order of hours or days. Our framework described here allows for
rapidly conducting thousands of in silico experiments that are designed as part
of this process.
