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How online networks (mostly) kept a lone
bioinformatician from going insane
Neil Saunders
DIGITAL PRODUCTIVITY
www.csiro.au
Social Networking: Slide 2 of 29
obligatory advertising slide
Transformational Bioinformatics Team
Australian eHealth Research Centre, CSIRO
http://aehrc.com/research/biomedical-imaging
Goal: develop advanced computational and statistical methodologies and apply them to large
datasets in the health/life sciences space
Bill Wilson Denis Bauer Firoz Anwar James Doecke Neil Saunders Sam Burnham Aidan O’Brien
Type Detail Value People
Software NGSANE: Lightweight Production Informatics Framework for High Throughput
Data Analysis
Collaborators: MQ, Garvan, ANU Denis
Contract Colo Vantage modeling CRC interventions
Janssen (J&J Pharma)
$100,000
$125,000/yr for 2 years
Rob
Sam
Publication A blood based predictor for neocortical Aβ burden in Alzheimer's disease: results
from the Australian Imaging, Biomarkers and lifestyle study of ageing
Burnham et al. Molecular Psychiatry.
IF=15
Sam, James, Bill
Grant MND Research Institute $100,000 Denis, Bill
Social Networking: Slide 3 of 29
a quick introduction to me
for the purpose of this talk
Social Networking: Slide 4 of 29
back in the year 2000
sequencing microbial genomes
one Windows machine, several thousand chromatograms
Social Networking: Slide 5 of 29
online support back then came in one form
the mailing list
Social Networking: Slide 6 of 29
what I learned from mailing lists
“community norms” :-)
Neil,
I’ve never written a “RTFM” post in my life...
Social Networking: Slide 7 of 29
the mailing list is not (quite) dead
Social Networking: Slide 8 of 29
experiments in more “personal” community
the Nodalpoint portal
Social Networking: Slide 9 of 29
what we learned from Nodalpoint
if you build it, they might come
Social Networking: Slide 10 of 29
the rise of the bioinformatics blog
2004 - 2008
Social Networking: Slide 11 of 29
blogs as community
bio::blogs
Social Networking: Slide 12 of 29
what we learned from blogs
want to express an opinion? be prepared to engage
https://xkcd.com/386/
Social Networking: Slide 13 of 29
structural bioinformatics Brisbane 2006 - 2009
predicting protein-protein interactions (Predikin)
something else happened in 2006 (more on that later)
Social Networking: Slide 14 of 29
an unlikely science community
the life scientists group at FriendFeed
Social Networking: Slide 15 of 29
rewards & recognition via online networks
Social Networking: Slide 16 of 29
why was FriendFeed important?
because it was not one of these - “facebook for scientists” a.k.a. fb4sci
social networks for scientists
N. Saunders (SMMS, UQ) Science networks November 26, 2008 8 / 29
Social Networking: Slide 17 of 29
health “omics” CSIRO 2009 - present
this is very much the age of Twitter
but what can you do with a real-time stream of 140-character
messages?
Social Networking: Slide 18 of 29
post links to interesting articles
possibly your own
Social Networking: Slide 19 of 29
provide status updates
services, software
Social Networking: Slide 20 of 29
advertise jobs
also meetings, events
Social Networking: Slide 21 of 29
advertise your other online content
Social Networking: Slide 22 of 29
ask/answer questions
Social Networking: Slide 23 of 29
discuss topical issues
Social Networking: Slide 24 of 29
and so back to forums...
forums have evolved and are still valuable
Social Networking: Slide 25 of 29
thoughts on online community 1/n
four ages of online interaction (at least since c. 2000)
the age of forums/mailing lists and portals
the age of blogs
the age of “facebook for scientists”
the age of Twitter
Social Networking: Slide 26 of 29
thoughts on online community 2/n
online communities
No matter who you are, most of the smartest people work
for someone else
- Bill Joy
It’s not information overload. It’s filter failure.
- Clay Shirky
clearly they are A Good Thing
they’ve provided me with advice, support and comfort for 15+ years
Social Networking: Slide 27 of 29
thoughts on online community 3/n
don’t be a lone bioinformatician
https://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/
Social Networking: Slide 28 of 29
thoughts on online community 4/n
local versus online
is online community “enough community”?
what about local communities?
what about bioinformatics in Sydney?
DIGITAL PRODUCTIVITY
www.csiro.au
CSIRO Digital Productivity
Neil Saunders
t
e
w website

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How online networks (mostly) kept a lone bioinformatician from going insane

  • 1. How online networks (mostly) kept a lone bioinformatician from going insane Neil Saunders DIGITAL PRODUCTIVITY www.csiro.au
  • 2. Social Networking: Slide 2 of 29 obligatory advertising slide Transformational Bioinformatics Team Australian eHealth Research Centre, CSIRO http://aehrc.com/research/biomedical-imaging Goal: develop advanced computational and statistical methodologies and apply them to large datasets in the health/life sciences space Bill Wilson Denis Bauer Firoz Anwar James Doecke Neil Saunders Sam Burnham Aidan O’Brien Type Detail Value People Software NGSANE: Lightweight Production Informatics Framework for High Throughput Data Analysis Collaborators: MQ, Garvan, ANU Denis Contract Colo Vantage modeling CRC interventions Janssen (J&J Pharma) $100,000 $125,000/yr for 2 years Rob Sam Publication A blood based predictor for neocortical Aβ burden in Alzheimer's disease: results from the Australian Imaging, Biomarkers and lifestyle study of ageing Burnham et al. Molecular Psychiatry. IF=15 Sam, James, Bill Grant MND Research Institute $100,000 Denis, Bill
  • 3. Social Networking: Slide 3 of 29 a quick introduction to me for the purpose of this talk
  • 4. Social Networking: Slide 4 of 29 back in the year 2000 sequencing microbial genomes one Windows machine, several thousand chromatograms
  • 5. Social Networking: Slide 5 of 29 online support back then came in one form the mailing list
  • 6. Social Networking: Slide 6 of 29 what I learned from mailing lists “community norms” :-) Neil, I’ve never written a “RTFM” post in my life...
  • 7. Social Networking: Slide 7 of 29 the mailing list is not (quite) dead
  • 8. Social Networking: Slide 8 of 29 experiments in more “personal” community the Nodalpoint portal
  • 9. Social Networking: Slide 9 of 29 what we learned from Nodalpoint if you build it, they might come
  • 10. Social Networking: Slide 10 of 29 the rise of the bioinformatics blog 2004 - 2008
  • 11. Social Networking: Slide 11 of 29 blogs as community bio::blogs
  • 12. Social Networking: Slide 12 of 29 what we learned from blogs want to express an opinion? be prepared to engage https://xkcd.com/386/
  • 13. Social Networking: Slide 13 of 29 structural bioinformatics Brisbane 2006 - 2009 predicting protein-protein interactions (Predikin) something else happened in 2006 (more on that later)
  • 14. Social Networking: Slide 14 of 29 an unlikely science community the life scientists group at FriendFeed
  • 15. Social Networking: Slide 15 of 29 rewards & recognition via online networks
  • 16. Social Networking: Slide 16 of 29 why was FriendFeed important? because it was not one of these - “facebook for scientists” a.k.a. fb4sci social networks for scientists N. Saunders (SMMS, UQ) Science networks November 26, 2008 8 / 29
  • 17. Social Networking: Slide 17 of 29 health “omics” CSIRO 2009 - present this is very much the age of Twitter but what can you do with a real-time stream of 140-character messages?
  • 18. Social Networking: Slide 18 of 29 post links to interesting articles possibly your own
  • 19. Social Networking: Slide 19 of 29 provide status updates services, software
  • 20. Social Networking: Slide 20 of 29 advertise jobs also meetings, events
  • 21. Social Networking: Slide 21 of 29 advertise your other online content
  • 22. Social Networking: Slide 22 of 29 ask/answer questions
  • 23. Social Networking: Slide 23 of 29 discuss topical issues
  • 24. Social Networking: Slide 24 of 29 and so back to forums... forums have evolved and are still valuable
  • 25. Social Networking: Slide 25 of 29 thoughts on online community 1/n four ages of online interaction (at least since c. 2000) the age of forums/mailing lists and portals the age of blogs the age of “facebook for scientists” the age of Twitter
  • 26. Social Networking: Slide 26 of 29 thoughts on online community 2/n online communities No matter who you are, most of the smartest people work for someone else - Bill Joy It’s not information overload. It’s filter failure. - Clay Shirky clearly they are A Good Thing they’ve provided me with advice, support and comfort for 15+ years
  • 27. Social Networking: Slide 27 of 29 thoughts on online community 3/n don’t be a lone bioinformatician https://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/
  • 28. Social Networking: Slide 28 of 29 thoughts on online community 4/n local versus online is online community “enough community”? what about local communities? what about bioinformatics in Sydney?
  • 29. DIGITAL PRODUCTIVITY www.csiro.au CSIRO Digital Productivity Neil Saunders t e w website