"For an idea that does not at first seem insane, there is no hope." - Albert Einstein
In the last 20 years there has been a dramatic increase in the complexity of experiments and publications in Biology. This problem is specially severe in neuroscience, since in this field experiments often attempt to integrate across different sub-disciplines and levels of complexity, including, molecular, cellular, systems, behavioral, cognitive and clinical neuroscience.
This multidisciplinary integration process involves a plurality of technologies, concepts and expertise that result in research papers with complex results and implications. This problem is further compounded by the unprecedented proliferation of the scientific literature. Neuroscience, for example, includes nearly two million research articles reporting approximately 20 million experiments.
Therefore, there is a great need to develop maps (simplified abstractions) of published information that could be used to decode complex research information and to guide research planning. As a first step to tackle this problem, our laboratory developed a taxonomy for biology experiments and a set of algorithms to generate research maps of causal information.
This taxonomy allows us to classify experiments in our field into a small set of distinct categories, a critical first step in the development of simplified abstractions of research findings. The algorithms are essential for representing these experiments in causal networks (i.e., our maps). Additionally, we have developed a free web application that helps biologists keep track and interact with causal information in research papers ( www.researchmaps.org). ( www.researchmaps.org)
For a recent Ray Kurzweil's newsletter article on our researchmaps work click here...
- Silva, AJ, Landreth, A, Bickle, J. Engineering the next revolution in neuroscience: the new science of experiment planning. Book from Oxford Press 2013
- Landreth, A, Silva, AJ, The Need for Research Maps to Navigate Published Work and Inform Experiment Planning Neuron (PDF)