How the human genome project changed how to do Science

Years after the end of the Human Genome Project (HGP), the ramifications to science and its culture are still unfolding. Ioannis Pavlidis, Eckhard Pfeiffer Professor of Computational Physiology at the University of Houston, Alexander Petersen, Professor of Management at UC, Merced, and their colleagues have reported in Science Advances that HGP scientists not only laid the groundwork for scientific breakthroughs for decades to come, but also brought to the mainstream a collaboration model that changed science’s cultural norms.

For centuries the image of the loner scientist was not updated. Pavlidis and Petersen report that after the sequencing of the human genome was completed in 2003, the consortium model did not go away, and scientists never returned to their silos. In a clear departure from norms, new and old researchers from biology, computing, and other disciplines kept building consortia, unlocking the genetic secrets of fauna and flora, and in the process transforming our ability to understand, predict, and edit life.

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“One of the key factors of the success was the way it incorporated cross collaboration between biologists, computer scientists and other disciplines,” said Pavlidis. 

“Their cross-disciplinary publications had superior impact and the same patterns were found to be true at the international literature level,” said Petersen. Specifically, genomic articles with mixed authorship from biology and computing, or genomic articles with mixed biology and computing content, had significantly stronger impact compared to alternatives

For this study, the authors assembled a dataset that included biographic and funding information for over 4,000 faculty in 155 biology and computing departments in the United States, including information for their 400,000+ publications co-authored with a network of nearly 500,000 collaborators.

Source: Computational Physiology Lab, Health and Biomedical Sciences Center,
Houston, USA
Image credit: Prof. Ergun Akleman, Texas A&M Visualization Department (crafted specifically for the paper Petersen et al., Sci. Adv. 2018;4: eaat4211)