“I am interested in data visualisation.” – “Great! Try this cupcake.”

Imagine the following situation. You are at a party and chat with someone you’ve just met. You start talking about what you do and what you are interested in. You say something like “I like statistics, and especially how it applies to solving biological problems.” The person you are talking to smiles brightly and then says: “Fantastic! Have you tried braiding your hair?”

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Dear Sir …

“Excellent”, said an e-mail I received recently from a collaborator, “talk to you soon, Stephanie!” This happens to me a lot, in professional contexts. I have been called Stephanie by colleagues and teachers, bosses and students. I have been introduced to a full lecture theatre as Stephanie, I have been invited for job interviews as Stephanie.

I don’t like it.

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How my coffee shop solved my research problem

A while ago I told you I was stuck with my research beccause I could not afford to build a library on the moon. Yes, it’s a long story, but it comes down to the fact that the proteins that transmit and store information in our body do this by undergoing changes to their function, shape, chemistry, location etc.

Here, for instance, is my favourite protein, CaMKII, and some of the things that can happen to it:

CaMKII_monomer_states_anno

Actually, this picture does not show all of CaMKII, only about one twelfth of it (well, one twelfth of what matters). But even for this little part of a protein, there are a lot of options: Is a phosphate group attached to it or not? Is it active or inactive? Bound to another protein called calmodulin or not? That’s already 8 possible states that little protein subunit can be in. With each new possible modification, the number of possible states doubles, and soon you have a mindboggingly big number of possibilities (what we call “combinatorial explosion”). This makes those proteins difficult to model using a computer.

Unfortunately, modelling proteins using a computer is what I do for a living. Hence the dilemma. What did I decide to do? Go for a coffee, of course. But this turned out harder than I thought.

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Stuck with your research? – Kaffeehaus

Remember the time when I was stuck with my research on combinatorial complexity in multi-state proteins, because I could not get the money to build a massive library on the moon? (Don’t you hate it when that happens?)

So, what did I do to solve the problem? I will answer this question in a minute, but let’s look at some poetry first.

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Say it in a sentence

I recently came across this very awesome site called “lol my thesis”. The site challenges people to summarise the content of their dissertation in one sentence. The one-word thesis summaries range from the somewhat surprising (“Irish cultural history is defined, before and after, by one school teacher’s crazy lifelong dream of becoming a martyr, because druids.“) to the somewhat less surprising (“If you take an obscure mathematical object and encode it into another obscure mathematical object, the result is an obscure mathematical object.“) to the somewhat depressing (“We will never know what a long dead writer wanted us to know about his work.“) Reading the entries on lol my thesis reminded me of a rather traumatic experience I had as a young grad student. 

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It’s a large world

Recently, I received an e-mail. Andrea and Noah are very happy to welcome little Ethan. He was born on November 12, is 52 cm tall and weighs 3300 g.

I never understood why parents always announce the height and weight of their new-born baby. Maybe it is because, even though that new little person takes up each of the many (many!) waking moments of their lives, they actually don’t know all that much about them. So they stick to the basics: name, date of birth, height, weight, until they figure out who little Ethan really is.

Meanwhile, I have a different, yet related question: Who the hell are Andrea and Noah?

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Your self can take the train

What have I been up to this last month? Obviously, it wasn’t writing blog posts. No, dear reader, I have been moving. Moving house, moving jobs, moving everything. Specifically, I have moved from sunny California to also-sunny-at-the-moment Massachusetts to take a new job in Boston (more about this at some later point).

This is another thing about my life as a scientist: It has allowed (and partly required) me to move around quite a bit. I did my first degree in one place (interrupted by a study semester in a different place), then I went elsewhere for my Master’s thesis, then elsewhere again for my PhD, then elsewhere as a short-term visiting scholar, then elsewhere for my postdoc, and then elsewhere again and here I am. Overall, my studies and work have involved six countries, four languages and three continents, and that is only counting the places where I have spent six months or more. In general, I find this cool and exciting. Except when I’m actually in the process of moving between two places. Then I find it tedious and difficult.

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What is your Plan B?

Being a scientist in academia is not always easy. You go to school for years and years and years, you don’t make much money, you have to apply for grants to fund both your research and your salary, you move house quite frequently (at least at the beginning of your career), you work long hours. You spend months, even years working on a particular project. If you are lucky it works out, and you can publish the results. If you are unlucky, someone publishes them before you. Or your machine breaks down or your cell culture dies or animal rights activists kidnap your mice or it goes wrong in the many, many other ways it can go wrong. (You know, all happy scientists are alike, but every unhappy scientist is unhappy in their own way.)

So, many of us have a Plan B.

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A day in the life

Today is Monday, 20 May 2013 (yes, sorry for the delay in posting)

I am working at Caltech as a postdoctoral fellow in the Division of Biology and Biological Engineering

This is a day in my life.

  • 8 am – It is a sunny morning in California.

    palm_trees

    I get up, shower, have breakfast and walk to work, admiring the blooming jacaranda trees on my street.

    jacaranda

  • 10 am – Work is underway.

    desk

    I spend the morning trying to install a new software package which will eventually allow me to do some cool modelling and parameter analysis of biochemical reaction systems. This bit of software requires some other software, which in turn requires some other software. After spending nearly all morning googling exotic error message, I finally manage to install all the required packages.

  • 12:15 pm – I check my e-mails and reply to some of the more urgent ones.
  • 12:45 pm – I go for lunch, enjoying the beautiful May weather outside.

    Campus

  • 1:15 pm – Back in the office, I read a paper draft my work study student has sent me, and start adding my own sections and figures to the paper.
  • 3 pm – As part of the “Women Mentoring Women” programme at Caltech, I have this year been mentoring a grad student. This afternoon, we meet for coffee to discuss her plans for medical school, books, and cats.

    coffee

  • 4 pm – Back working on my paper draft.
  • 4:30 pm – My boss just came in to schedule a meeting for tomorrow. I take some time to prepare for the meeting and e-mail relevant documents to both my boss and my co-worker.
  • 5 pm – Back to working on the paper draft, and finally get it into a state that I am happy with. Will it be Ice Cream Day soon?
  • 5:45 pm – Do some reading.
  • 6:45 pm – It’s evening on campus. Get a sandwich for dinner.

    evening

  • 7 pm – Back at work, wrap up, update my lab notebook, make plans for tomorrow.
  • 7:30 pm – Choir rehearsal on campus. At the moment, we are learning bits of Beethoven’s 9th for commencement. Good fun.
  • 9:45 pm – Home from choir, I spend half an hour doing some housework, while listening to an audiobook (Bring up the Bodies, part 2 of Hilary Mantel’s trilogy about Thomas Cromwell). Listening to audiobooks is literally the only way I can trick myself in doing any household chores at all. (The rest of it is handled by my robot vacuum cleaner. Yay robots!)
  • 10:15 pm – I make myself some tea and tackle my final exam for my EdX Statistics Course. Longer than I expected, but fortunately not hard.

    stats

  • 11:30 pm – I skype with by boyfriend in London. It is the last thing I do before I go to sleep and the first thing he does after waking up. I am insanely grateful to be living in an age where technology allows us to do that. Where it is possible for two people, across an ocean and a continent, across an entire night on earth, to connect.