A big data look at improving scientific research: A Q&A with Andrey Rzhetsky

Of all the possible experiments available in biomedical research, only a small subset are ever tackled by scientists. This is in part due to institutional and cultural pressures that lead researchers to avoid risk-taking and choose inefficient research strategies, according to a new study based on a computational analysis of millions of patents and research articles. Despite increased opportunities for groundbreaking experiments, most scientists choose conservative research strategies to reduce personal risk, which makes collective discovery slower and more expensive, conclude Andrey Rzhetsky, PhD, professor of medicine and human genetics and director of the Conte Center for Computational Neuropsychiatric Genomics, and his colleagues.

However, the team also uncovered more efficient approaches for maximizing discovery and identified the approaches used more often by scientists who have won Nobel Prizes and other prestigious awards. Not only do they quantify the advantages and disadvantages of modern science, which they published in the Proceedings of the National Academy of Sciences, they also propose steps for a more productive future. ScienceLife asked Rzhetsky a few questions about his big data look at the science of science. Read the journal article here. The Q&A can be read here.

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