What is a C.E.O.

This is a topic I’ve had to think an awful lot about over the past year, so it’s fitting that it becomes my first real post on the blog. Whether you want it or not, starting a company forces you to do some self reflection. Becoming a Chief Executive Officer forces you to constantly ask yourself if you could be doing things better.

If you had asked me what a C.E.O. does at the start of my career, I would have told you that they are in charge of making the decisions, obviously, and that the responsibility for those decisions rests on their shoulders. Clearly that’s why the word “executive” is in their title.

A decade of management experience has completely changed my way of thinking about management, however. In every role I’ve undertaken, I’ve treated management as an exercise in communication and support. It was my job to communicate upper management’s priorities to my team and to ensure they have the resources to do their job the best they could, while simultaneously communicating my team’s challenges and concerns to upper management.

While the responsibility for the company rests on the C.E.O.’s shoulders, it turns out the job isn’t just about making decisions. It’s about communication. Communicating internally within the company, as well as communicating outward from the company. I’ve spent most of the past year simply developing the company’s vision (which is the decision making process) but critically, those decisions then had to be communicated it to everyone.

To the company, that communication comes in great detail about what order we need to tackle which task, about how to organize our documents, or just to ensure that we’re all still enthusiastic about the project. Some days, you have to become very granular and ensure that you’re communicating the mechanics of the software design through pull requests and code reviews, but the actual work I’m doing is nearly always communication. Teaching, pointing the path, or just listening, but always communication.

To investors, I have to communicate on a different level, speaking about our plans and timelines, about the value of the project and the outcomes we expect. It means communicating the enthusiasm of the whole company to the people who might consider funding our work – and remembering to learning from their experience.

It’s as important to communicate who we are and what we’re doing externally, as it is to communicate how and when we’re doing things internally – and to hear the responses of those to whom it’s being communicated.

While I’m not a huge fan of internet personalities, I think Simon Sinek captured it perfectly in one of his internet rants about why Chief Executive Officer is the wrong title. Calling it a Chief Vision Officer sums up the job much more efficiently. At the end of the day, what I’m communicating is the company vision, no matter how granular or high-level it may be.

While I don’t think the world is yet ready to embrace that particular change of title, I will say that it has become an integral part of how I view my job, which has helped me a lot in this journey. When you realize it’s your job to knock on doors to tell people the company’s story, rather than to just make the decisions about what you want that story to be, there’s a moment of clarity about how you need to move forward.

In a round about way, that brings me to one last point. This blog is also about communication – giving people a chance to come along on our journey, and in order to make it worthwhile, I’d like to invite people to communicate with me as well. If you have questions you want me to answer about startups, or our journey, let me know. I’ll do my best to answer. As I said from the start, communication is the key to making all of this work.

First Post!

You may have noticed a bit of a change here. A bit of spring cleaning, you might say. I’ve hidden my old posts, to make it a little less cluttered, and to make room for new content.

I have a goal in mind. I want to blog the start of a biotech company.

Let me be a bit clearer. Not just the start of any biotech company, but rather, the company I’ve started with my friend Alex: htuobio.com.

I’m not going to tell you any of our secrets, and I’m not going to discuss office politics. There are definitely topics that are off limit, and won’t show up here. But, I do want to inspire others to take this journey, and the best way to do that is to let people come along for the ride.

A lot of people have questions about what it’s like to start a company, what it takes, and what the experience is like, and I’d be happy to answer those questions.

So, if you want to join us on this adventure, you can do it by following along here, or by commenting and asking questions. Starting a company isn’t a one-person job, it’s a community – and I’d love to invite you to be a part of it.

How do you become a bioinformatician?

I’ve been following the bioinformatics sub-reddit for the past couple of months, ever since I stumbled upon it when a colleague asked me about bioinformatics resources on the web.  It’s a fascinating place to visit, but it’s incredibly repetitive in that people keep asking “How do I become a bioinformatician?”

Unfortunately there is not a single answer, because bioinformatics isn’t a single job – it’s a collection of people who have found a way to live with one foot in each of two worlds: computer programming and biology.  Getting a firm footing in each can be a serious challenge, as people spend years studying just one of those to become proficient at it.

However, I think there are some common threads that tie the field together.  You need to invest the time in at least a handful of basic fields: some basic programming, some elementary cell biology and at least a simple understanding of math or statistics.  What you can accomplish with just that little can be incredibly productive.  Mostly in terms of automation of data processing or modelling of your results.

On the other hand, bioinformatics also includes a lot of sub-disciplines.  Great programmers can build incredible pipelines.  Great mathematicians can invent or apply algorithms to create new ways of interpreting data, and great biologists can develop heuristics and re-interpret data in new ways to generate insights that others have overlooked.  There’s even room for “neat freaks” in organizing and imposing order on unruly data.

The challenge of becoming a bioinformatician is learning where your strengths and weaknesses lay, and using them to your advantage.  Finding a research group that shores up your weaknesses – or helps you fill them in – can be a great boost to your career.  After my masters degree, I felt I had two big gaping holes in my resume: big data and databases, which I made the focus of my PhD research. Coming out of my defence, I felt I was able to bring a more balanced approach to the table – and had simultaneously purged any instinct I might have ever had to reach for a spreadsheet to interpret information. (Spreadsheets and big data don’t mix.)

So, where does that lead an aspiring bioinformatician?  Unless you take the time to do both a computer science degree and a biology degree, you probably won’t be able to shoehorn everything in to become an expert in both, and not everyone wants to get their PhD to fill in the gaps left in an undergrad education.

With that said, let me lay down a few useful points:

  1. Pick and chose to study subjects that interest you because you’ll at least end up with strengths in things you enjoy, which leads to jobs doing things you enjoy.
  2. You can always learn something new later… but take opportunities to try new things when they come.
  3. Remember that you’re not going to be the expert in every field you put your foot into – so look for opportunities to collaborate with the people who are.  (If you’re going into bioinformatics and expect to do everything yourself, you’re probably doing it wrong.)
  4. Don’t be afraid of the fact that you don’t know stuff.  Your job isn’t to be the best biologist and best computer scientist at the same time – it’s to be the bridge between.  The stronger your foundations, the better a bridge you can be, but unlike a concrete bridge, you can always invest in learning more.
  5. Yes, higher education does help in this field.  Bioinformatics is still dominated by research based organizations, and the academic hierarchy saturates the mindset of bioinformaticians everywhere.  (Or, almost everywhere.)
  6. Bioinformatics is also about the “soft” skills.  Don’t forget that bioinformaticians are also in a good place to be good leaders – since you’ll be one of the few people who can speak both languages, and tie together groups that would otherwise lack a common language.
  7. Don’t believe the hype about what you should learn:  R isn’t really the only language for doing bioinformatics.  Perl isn’t always evil (just most of the time, though it did save the human genome…), Java isn’t the slowest language out there, and c isn’t only for hardcore programmers. (Python, though, is a pretty good all-around language.)  Everyone has an opinion on where bioinformatics is going – but it’s just an opinion, so make your own choices.

At the end of the day, I always give students the same piece of advice:  As you go through life, you will learn new skills that you can apply as you see fit.  At the end of the day, each of these skills will be a tool in your toolbox that you can turn to when you hit a problem.  If you only have a hammer in your toolbox, your repertoire is pretty limited.  On the other hand, if you collect a fantastic assembly of tools, you’ll be equipped to handle just about anything that comes your way.  Your job is to invest your time into building the best toolkit you can, so that when you get out of school, you’ll be ready to solve as many problems as you can.

Bioinformatics is just a special case of toolbox building, in that you need the tools of at least two disciplines in your toolbox.  What you chose to put into your toolbox is entirely up to you, but (to stretch the toolbox analogy just a little too far), take a few minutes to ask if you’d like to be a plumber or a carpenter before you start collecting your tools. Or, without the metaphoric toolkit, ask yourself what kind of bioinformatician you want to be.

Once you know the answer to that question, you’ll figure out pretty quickly which tools you want to start collecting.  And the path towards becoming a bioinformatician will start to become clear.  It may not take you where you expect, but I can guarantee that you’ll be walking down an interesting road.

What is a bioinformatician

I’ve been participating in an interesting conversation on linkedin, which has re-opened the age old question of what is a bioinformatician, which was inspired by a conversation on twitter, that was later blogged.  Hopefully I’ve gotten that chain down correctly.

In any case, it appears that there are two competing schools of thought.  One is that bioinformatician is a distinct entity, and the other is that it’s a vague term that embraces anyone and anything that has to do with either biology or computer science.  Frankly, I feel the second definition is a waste of a perfectly good word, despite being a commonly accepted method.

That leads me to the following two illustrations.

How bioinformatics is often used, and I would argue that it’s being used incorrectly.:


And how it should be used, according to me:


I think the second clearly describes something that just isn’t captured otherwise. It covers a specific skill set that’s otherwise not captured by anything else.

In fact, I have often argued that bioinformatician is really a position along a gradient from computer science to biology, where your skills in computer science would determine whether you’re a computational biologist (someone who applies computer programs to solve biology problems) or a bioinformatician (someone who designs computer programs to solve biology problems). Those, to me, are entirely different skill sets – and although bioinformaticians are often those who end up implementing the computer programs, that’s yet another skill, but can be done by a programmer who doesn’t understand the biology.


That, effectively, makes bioinformatician an accurate description of a useful skill set – and further divides the murky field of “people who understand biology and use computers” – which is vague enough to include people who use an excel spreadsheets to curate bacterial strain collections.

I suppose the next step is to get those who do taxonomy into the computational side of things and have them sort us all out.