101 questions with a bioinformatician #4: Michael Hoffman

This post is part of a series that interviews some notable bioinformaticians to get their views on various aspects of bioinformatics research. Hopefully these answers will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.

Michael Hoffman is a principal investigator at the Princess Margaret Cancer Center in Toronto. His research group is based in the glamorous sounding Toronto Medical Discovery Tower, and the focus of his current work is on developing machine learning techniques to better understand chromatin biology. The highest complement that I can pay to Michael is that he understands the need to properly document his code; the description for his segway software states:

Our software has extensive documentation and was designed from the outset with external users in mind.

I wish more bioinformaticians had this attitude! You can find out more about Michael by following him on Twitter (@michaelhoffman).


001. What's something that you enjoy about current bioinformatics research?

I love how easy it is to experiment with new ideas. The activation energy for writing and managing a useful piece of code or looking at results keeps reducing. Improvements in lower levels of abstraction keep making it easier to think about more complex problems rather than low-level of implementations.


010. What's something that you *don't* enjoy about current  bioinformatics research?

The amount of time wasted by moving data around, converting it from one format to another. Was it Nick Loman who referred to bioinformatics as "advanced file copying"? I hate that stuff. I can't believe no one has solved this problem yet.


011. If you could go back in time and visit yourself as an 18 year old, what single piece of advice would you give yourself to help your future bioinformatics career?

I was a biochemistry undergraduate in a chemistry and biochemistry department. I would have been served better by more statistics classes and fewer advanced chemistry classes. I still learned some cool stuff in those classes though, and I got to quantify the hotness of commercial salsas via HPLC. Best lab teaching experiment ever.


100. What's your all-time favorite piece of bioinformatics software, and why?

Can I bend the rules and name and name my all-time favorite bioinformatics data resource? That would be Margaret Dayhoff's Atlas of Protein Sequence and Structure (here is a good review on how this resource was developed). Dayhoff and colleagues were the first people to realize that we needed to gather all the available protein sequence information in a database so that we could do cool stuff with it. The whole field traces its origin to Dayhoff's work starting in the 1950s. Of course, back then you could print out all the sequence information available in a book. Try doing that today (well there is this, KB).

Bioinformatics has been around longer than people realize.



101. IUPAC describes a set of 18 single-character nucleotide codes that can represent a DNA base: which one best reflects your personality?

I'm going to go with R because of my interest in pure science.


2014-04-22 11.04 - Article updated to correct typo and correct the web link for Michael's research group.