Eight {So Far} Things I Wish I had Thought About 40 Years Ago
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This document provides eight pieces of advice for computational biologists starting their careers: 1) Science is a team sport and long-term success depends on building and maintaining a team. 2) Collaboration, communication, and administrative skills impact productivity and career advancement as much as individual accomplishments. 3) Work on problems that will be most important in the future. 4) Computational biomedicine is becoming more integrated and data-driven. 5) Emerging areas like imaging, EHRs, and global health show opportunities. 6) Follow funding to see what areas are priorities. 7) Treat others as you want to be treated to avoid future problems. 8) Find a
Eight {So Far} Things I Wish I had Thought About 40 Years Ago
- 1. Eight {So Far} Things I Wish I Had Thought About 40 Years Ago Philip E. Bourne PhD, FACMI Stephenson Chair of Data Science Director, Data Science Institute Professor of Biomedical Engineering [email protected] https://www.slideshare.net/pebourne 1 @pebourne ISMB Student Council July 6, 2018
- 2. This is not a lecture it is a discussion …. Acknowledgement: The context for this discussion draws from the nearly 100 x Ten Simple Rules.. Which takes us to Take Home One & Two 2
- 3. Take home one … Science is a team sport … Your long term success will depend as much on the ability to build and maintain a team as it will on your individual accomplishments 3
- 4. Take home two … • Its more … • Collaboration • Management skills • Communication • Verbal • Written • Administrative ability • All impact productivity • Grants • Papers • Teaching awards • Editorial and committee work • Etc. 4 Ten Simple Rules for Getting Ahead as a Computational Biologist in Academia. PLoS Comput Biol 7(1): e1002001.
- 5. Take home three … (from Hamming) Work on the most important problems in your field {as you believe they will be in years to come} 5 Erren TC, Cullen P, Erren M, Bourne PE (2007) Ten Simple Rules for Doing Your Best Research, According to Hamming. PLOS Comput Biol 3(10): e213 https://en.wikipedia.org/wiki/Richard_Hamming
- 6. What is to come can be extrapolated from past history 6
- 7. The Past History of Computational Biomedicine According to Bourne 1980s 1990s 2000s 2010s 2020 Discipline: Unknown Expt. Driven Emergent Over-sold A Service A Partner A Driver The Raw Material: Non-existent Limited /Poor More/Ontologies Big Data/Siloed Open/Integrated Unstructured The People: No name Technicians Industry recognition Academics Data Scientists Searls (ed) The Roots in Bioinformatics Series PLOS Comp Biol 7 As described to the Advisory Committee to the NIH Director
- 8. You are entering the field at a time when society at large is catching up … The good news ... Many opportunities The bad news ... Many opportunities outside of biomedicice 8
- 10. 10
- 11. What of the future? One view is the 6D’s 11
- 12. Digitization Deception Disruption Demonetization Dematerialization Democratization Time Volume,Velocity,Variety Digital camera invented by Kodak but shelved Megapixels & quality improve slowly; Kodak slow to react Film market collapses; Kodak goes bankrupt Phones replace cameras Instagram, Flickr become the value proposition Digital media becomes bona fide form of communication From a presentation to the Advisory Board to the NIH Director Example - photography 12
- 13. Maybe follow the emergent data & analytics… • A few examples: • Imaging – biggest success in machine learning • EHR’s – still the wild west, but becoming civilized • Integration with environmental data • Cancer • Autism • Prevention – social media • Mental health • Global health • Pandemics • Biocomplexity 13
- 14. Think about the technologies and how they will change … Will biomedical research become more like Airbnb? 14 Should biomedical research be like Airbnb? PLOS Biol 15(4): e2001818
- 15. Open platforms will digitally integrate the scholarly workflow for human and machine analysis Should biomedical research be Like Airbnb? doi: 10.1371/journal.pbio.2001818 15
- 16. Take home four … The most compelling science still needs money 16
- 17. Look to what is being funded (apologies for the US centricity) • Moonshot – cancer genomics • MODs old dog; new tricks • Human Microbiome Project – a gut feel • TOPMed - genotype to phenotype • All-of-Us – precision medicine • ECHO – child health and the environment • BRAIN - neuroscience 17
- 18. Take home five … Treat others as you treat yourself Trust me, If you don’t it will come back to haunt you 18
- 19. Take home six … Follow your heart not your brain 19http://brainwarriorswaypodcast.com/the-brain-in-love-lust-can-you-choose-your-love/
- 20. Take home seven … Diversity of research is a relative term … Figure out where you are comfortable on the spectrum … More diversity means less depth however smart you are 20
- 21. Take home eight … its about balance 21 ISMB 2006 ISMB 2009
- 22. Discussion •Does this resonate with you? •What is missing from your perspective? •What could ISCB do to help that it is not? 22
- 23. References • Russ Altman – Translational Bioinformatics Year in Review https://www.dropbox.com/s/dtlfdfxc8rcudb1/amia-tb-review-18.pdf?dl=0 • Bourne PE (2011) Ten Simple Rules for Getting Ahead as a Computational Biologist in Academia. PLOS Comput Biol 7(1): e1002001 23