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The Impact of Bioinformatics on Science and Society

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quanda
12 diapositives · 266 Views · Sep 17, 2014

In this talk by Hugh Shanahan from Royal Holloway, University of London, the relevance of bioinformatics is explored, particularly in addressing global challenges such as population growth, aging demographics, and climate change. The discussion covers the significance of omics data (genomic, transcriptomic, metabolomic, and proteomic) and emphasizes the role of bioinformaticians in helping biologists interpret this data. Key lessons include the importance of data over algorithms, the need for collaboration with wet lab scientists, and the responsibility of professionals to ensure data quality and sharing.

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  1. Why do we do Bioinformatics ? • Hugh Shanahan, • Department of Computer Science, • Royal Holloway, • University of London FAFU, Fuzhou, Fujian 4 Sep 2012 This talk is available at http://gene.cs.rhul.ac.uk/CCC12/Lectures/bioinformatics.ppt

  2. Summary • Who am I ? • Impact of Bioinformatics • Lessons learnt • Being a professional Bioinformatician • Question time

  3. Summary • Background in High Energy (Particle) Physics • In 2000 moved into Bioinformatics at UCL/EBI • Worked on Protein Structures - identifying evolution of hydrophobic patches • Identifying DNA-binding proteins from structure alone • In 2005 started lectureship at Computer Science at Royal Holloway • Working on transcriptomics - Plant Science and Human Data

  4. Big Picture • Best estimate by the end of century human population will plateau at 10 Billion. • Some countries will face an increasingly older demographic (some will still be very young). • Climate change is a reality - Permanent Artic ice cap could be gone in FOUR years. • We live longer and have healthier lives than our parents/grandparents/.... • Large disparities between different populations • Human migration occurs on a huge scale

  5. Challenges from the big picture • Need to feed more people with a better diet - 3-fold improvement of yield for crops. • Need to ensure that everybody stays happy with an older demographic - healthier for longer • Need to ensure this happens across the world (otherwise the world comes to your doorstep) • Need to do this with a much more variable weather systems/reduce greenhouse gas emissions

  6. Bioinformatics in this big picture • Need major steps forward in • Plant Science • Crop yield • Crops in poor environments • Biofuels • Medicine

  7. Omic data - • Biologists/Biomedical Scientists generate this data and more • Genomic • Transcriptomic • Metabolomic • Proteomic • ...

  8. Omic data - Where you fit in • Biologists and Biomedical Scientists generate this data. • They are not capable of making the most of this data. • That is your job. • You will guide and help them to learn from that data. • This will ultimately feed back into the challenges discussed above.

  9. Lesson learnt • Data is always more important than algorithms. • Algorithms are always more important than conjecture. • The best computational biology algorithms use evolution. • Understand evolution. • Most of the time you have to deal with reading in data so think hard about the best way of storing data.

  10. Being a professional • Two modes of research • work with other Bioinformaticians and publicly available data • work with wet lab scientists and their pre-published data • The second mode means you need to think like a professional

  11. Responsibilities to wet lab Scientists • Point out if there are problems with the data. • Do everything that can be done with the data. • Do not promise miracles. • Encourage them to make the data available after publication(s).

  12. Thank you for your time !Please ask questions !