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.

Tuuli Lappalainen is a Group leader at the New York Genome Center, an institution that's so new, that their Illumina HiSeq X Ten is counted as one of their older sequencing machines. In addition to having possibly the coolest logo for a genomics/bioinformatics institute, they also have an impressive set of green credentials. And did I mention that it's in New York, New York? Start spreading the newwwss…

Sorry, I got distracted.

Tuuli is also an assistant professor at the Department of Systems Biology at Columbia University. Her work focuses on using high-throughput sequencing data to study functional genetic variation in human populations. Her website — paraphrasing Dobzhansky — puts it like this:

Nothing in the genome makes sense except in the light of the transcriptome

You can find out more about Tuuli by following her on twitter (@tuuliel) or by checking out her lab's website. Oh, and Tuuli is looking for a talented post-doc to join her lab (she didn't ask me to say that, it's all part of the service). And now, on to the 101 questions...

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

I have very little interest in methods for the sake of methods; for me it's all about understanding biology, and bioinformatics provides fantastic opportunities for that.

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

The working environment that is local when data and analyses are increasingly global is driving me insane. I've done (and still do) a lot of consortium work, where all of us still end up copying large data files to our local servers, and having locally optimized pipelines and scripts that are impossible to transfer to colleagues. I know that many people are trying to solve the problem, and I hope we'll be able to make it happen soon. And then there are the complications of applying and getting access to various datasets. Privacy concerns are important, but does dbGap really need to be so difficult to use? Our open access data set from GEUVADIS (Genetic European Variation in Health and Disease) is a great exception to this.

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?

Learn more stats, math, proper programming. It's great to see how the younger generations have formal training in so many of the skills that I've had to just pick up the along the way — I'm a biologist by training and proud of it, but in the early 2000's computational biology was still very marginal.

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

My two current favorites are pysam for handling BAM/SAM files — fast, great syntax, and much more versatile than alternatives — and Matrix eQTL for very fast eQTL analysis.

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

T for Tuuli!