I went to a seminar on thesis writing last year.  They warned us that this would happen…

There’s only so much time in a day.

I feel guilty if I’m not working on my thesis.

I feel guilty if I’m neglecting my blog.

I feel guilty if I’m not working on other projects.

I feel guilty if I work instead of spending time with my family.

Given the finite amount of time available in a day, it’s a fine balancing act.  I just hope I don’t drop something…

10 Tips for how to get the most from your PhD.

I’m clearly late to this conversation, but because I disagree with the first two contributors, I figured I might as well have my say.

First, there was @Katie_PhD‘s post on “How to make the most of your PhD: The road less traveled“., which (alas) doesn’t give you much of a sense of how to get more out of your PhD.  It’s a great piece, so don’t get me wrong – I’ve read it several times already – but there aren’t any tips for graduate students.

Following on, Nick at “For Love of Sciences” wrote a list of tips that could help incoming and early PhD students get more out of their PhD.  Unfortunately, I’m not sure I really believe Nick’s points cover the topic the way I’d like to see it covered.  Some of them are dead on: Yes, you should move out to a new city, to find a new environment and challenge yourself, but other’s I find myself disagreeing with Nick.  Alas, that’s the point of graduate school, really – to stand up for what you believe in, and boldly state when you think other people aren’t nailing the point as accurately as possible.

So, without further ado, let me introduce my top 10 tips for how to get the most out of your grad school experience.

1. Say yes, until you learn to say no.

When you start graduate school, you won’t know enough about which avenues are the right ones to follow up.  Learn to say yes at first, to tackle any project that comes your way.  You’ll find yourself tackling good projects and bad projects and, as time goes by, you’ll learn how to tell which projects are the bad ones in order to start saying no to them.  When you’re ready to graduate, you’ll even have to turn down a few of the good ones in order to keep your PhD from dragging on too long.  So start with yes, but learn how (and when) to say no.

2. Learn to communicate.

Half of the challenge of a PhD program is to become a good communicator.  Define what good communication means to you and then bust your ass to figure out how you can become as good as possible at it.  Whether that’s communicating science to non-scientists, communicating with your peers, blogging, twittering or even writing grants, make a commitment to learn to communicate in every possible form and then to get better at it.  At the end of your PhD you are going to be judged by how well you can defend your ideas, so why not practice it as often as you can?

2b.  Learn to teach.

Teaching is just another form of communication, but it’s an important one that just can’t be overstated.  If you become an academic, you’ll be evaluated on how well you teach your students.  If you become a blogger, you’ll be evaluated on how well you can teach your audience.  If you become an entrepreneur, you’ll be evaluated on how well you can teach your board about your technology.  The job of a scientist is always teaching and communicating, so get as much practice (and hence feedback) as you can while you can.

3. Take advantage of your university’s resources.

Every university that I’ve had the pleasure of visiting has had some form of courses for it’s graduate students to learn new skills – TAKE THEM!  I’ve gone to some really cheese-tastic courses, and I’ve gone to some life-altering good ones.  You never know which one is which till you try them out, but if you don’t try any of them, you’re tossing away a perfectly good opportunity.

4.  Meet your future life partner.

I cheated on this one – I met my wife while we were doing our masters degrees together, but it was still graduate school and I had been planning on doing a PhD at the time.  Regardless, when else will you be surrounded by people who are fascinated by the same things you are, smarter than you are, and are fantastically interesting people in their own right?

4b.  Make some great friends.

Yeah, even if you don’t meet the love of your life, you can definitely find a few friends.  I’ll admit, I haven’t made a lot of close friends during my PhD, but I’ve made up for that with a wide net of professional contacts and having had the opportunity to rub shoulders with a lot of fantastically interesting and successful scientists.  I wouldn’t have traded it for anything.

5. Decide what you stand for, and stand for it.

Along the long and winding road of your PhD, you’ll discover situations that test your morals, your sense of dignity and your ideals.  Everyone is sorely tempted to sweep a bit of dirt under the figurative carpet of their project in the name of having results to show off.  If you don’t believe me, spend some time reading the retraction watch blog. What separates the good scientists from the bad scientists is the moral code to which they hold themselves.

I’ve taken stands on open source code, on re-doing experiments and on re-coding units that were just “good enough.”  Grad school gives you a great opportunity to do the things that matter to you – and do them well.  This is one of the few times that you get to show people who you really are and not compromise on it.

6. Keep good notes

Pretty much everything you do, you’ll either have to show someone else how to do it, or do it over again later.  The better your notes are, the easier things will go for you – and that includes when it comes time for you to write up your thesis.  Trust me, good notes and documentation will make your life SO much better when you’re writing a chapter and want to figure out exactly how that algorithm worked, or need to make last minute changes to a poster  at 3am and can’t remember how you churned out that table…

7.  Be a sponge.

Grad school is also one of the few times that you can really delve into projects that you wouldn’t otherwise have a chance to pursue in a corporate environment.  I’ve learned such random/wonderful things as how to play ping pong, how to use professional publishing software and how to draw cartoons.  You never know when these things will come in handy.   (For the record, there are far better examples, but those were way more amusing to me.)

8. Face the challenges.

Not many graduate students get slapped down for trying to take on more responsibility or to tackle the tougher projects.  I’m constantly amazed by the people who just quietly slide through grad school without leaving a ripple behind:  Life doesn’t start once you’re finished – it’s already going on, so hiding behind your desk isn’t going to help you get anywhere.

Perhaps I’d sum it up this way: Have the courage to face problems head on, tackle projects that are bigger than you are and throw yourself into the fray.  The worst thing that’s likely to happen is a bruised ego, but even that’s sometimes a lesson worth learning – and it’s a lesson that’s much easier to learn as a student than in the corporate world.

9.  Don’t give up.

People will ridicule you, people will flame you in emails, projects will misfire, scholarship applications will be rejected.  These are facts of life.  You can’t make everyone happy all the time and even keeping yourself happy can be a challenge some days.  Remember that there is always a light at the end of the tunnel and if you persevere, you will get through.

An investor once told me a brilliant piece of advice in relationship to startup companies, which I’ll paraphrase and apply to grad school.

“Grad school is like a roller coaster: some days will be crazy high, some days will be desperately low.  Sure, you can enjoy the highs, and you’ll despair in the lows, but don’t let either of them change your course – keep a straight and level path and you’ll get through to the end of the ride. “

And that brings me to the last point…

10.  Enjoy the ride.

The longer you spend as a grad student, the more impatient you’ll be to leave, but that doesn’t mean you can’t enjoy the time you spend there.  You’ll rarely have such a wonderful combination of responsibility  (or lack thereof), freedom (or at least, lax deadlines) and community (how ever you want to define it.) –  Remember to appreciate what you have while you have it, because things will change once you hand in your thesis.

Here’s to that day coming as soon as possible!  Cheers!

How I would improve Google plus, or “Squares, not Circles”

First off, I absolutely think Google+ is fantastic and I’m thinking of giving up twitter in favour of it, which should say a lot.  I think it has the ability to be THAT good.  However, google missed something big.  As “Science of the Invisible” points out (and via tech crunch) – Google circles are great for organizing, but don’t really help you in the noise to signal ratio.

So, I’d like to propose a new Idea:  Google Squares.

Instead of the loosely grouped people that make up circles, a Square would be a rigidly defined group, with moderators.  The moderators have two roles: determining who can post to a Square, and who can follow a Square.

Imagine, if you will, a private Square. Lets imagine I want to start a Square for my family.  I can first decide to make it private – only people who are invited to the square are allowed to see the posts, and only those in my family are invited.  It becomes, instantly, the equivalent of an email mailing list (but much easier to set up and manage) for my family members.  I don’t have to worry about typing in the email address of my family every time I want to post something to the Square – and neither do my other family members.  Only one person needs to set it up (the moderator), and it instantly becomes a useful communication tool for everyone I add.

It would be useful for labs, social groups, clubs, etc.   And, it moves people away from email – a long time holy grail of security experts.

So, what about public Squares? They could be even more useful – providing the equivalent of a blogging consortium, or twittering group (which don’t even really exist.)  Imagine if there were a Square with all of your favorite twitter-ers. You can still follow them all, one by one, if you like, or add them to your circles, but the square would give you instant access to All those people who someone else has pre-screened as being good communicators and worth following.  Instant increase in signal-to-noise.

Finally, the last piece lacking is direct URLs.  Seriously, I’m a bit miffed that google didn’t set this up from the start, even based on the google ID.  Really, I’ve had the google id apfejes for a LONG time – why can’t I have  Even twitter has this one figured out.

In any case, these are minor grievances…. but I’m waiting for Google to up their game once more.  In the meantime:

Do not disturb my circles! – Archimedes

Extinguish the HST? A summary of silliness.

For those of you who don’t have the pleasure of living in British Columbia, Canada’s most western province, I thought I’d share with you our current (and slightly stale) obsession: the Harmonized Sales Tax.

To briefly recap, BC elected the BC liberal party (as opposed to it’s only viable alternative, the BC New Democratic Party) back into power in 2009.  Both the liberals and the NDP have terrible histories of scandals, abuse of power and other skulduggery, most of which just makes BC citizens somewhat cynical about the whole political system. However, during the election, absolutely nothing was said about changing the (at the time) current tax system – a 7% provincial sales tax on top of a 5% federal goods and services tax, which many people think should have been a major debate for the election campaign.  (Opinions differ as to whether it had even been considered at the time.)

Lo and behold, one of the first things the re-elected liberal government did was sign an agreement with the Federal government (which was busy trying to re-brand itself as the Harper government, despite the fact that our political system doesn’t work that way, and that it’s illegal to boot) in order to merge the provincial and federal taxes (the PST and the GST) into the harmonized sales tax (HST).

In reality, it’s not a bad thing, since both levels of government were collecting nearly identical taxes in parallel.   If that’s all that had been in the agreement, it might have been a reasonable argument, but to muddy the water and spark off conspiracy theories, the Federal government bundled in a big payment to the province to bail it out from some other debts, incurred by recession induced budget shortfalls.

Unfortunately, at this point, a former premier (the equivalent to a state governor) decided he’d been out of the limelight for too long and decided to make a name for himself crusading against the tax.  (He’s a former NDP, of course, and the liberals were the ones who modified the tax system so it was only natural that this would be a great crusade for him to try to bring down the liberals.)  Indeed, he created enough of a protest that the elected premier resigned and the Liberals had to elect a new premier. (We don’t directly elect the head of our governments at any level in canada.)  The NDP, crushed by their loss, despite the unpopularity of the premier in some circles, also elected a new leader, just to wipe the slate clean for both parties.

The incoming premier, and our now current premier, was in power when a report came out saying that the tax exemptions don’t quite match up between the previous PST + GST and the HST.  That is to say, the government actually was taxing people more by harmonizing the two taxes and using the federal list of what is taxable and what isn’t.  This was more fuel for the fire, as people started getting quite upset over a number of items that were previously exempt at the provincial level.  Thus, previously, people were paying 5% tax on things before and suddenly found themselves paying 12% tax on the same items under the HST.

Despite the propaganda, the list of items for which the tax actually increased isn’t that onerous – and does have measures to protect the poor, although some people continue to claim that the poor are the ones paying the most tax.

So, between the ex-premier running around making statements that the HST is undemocratic and doing some serious rabble-rousing, and people being upset that they’ll pay more (anywhere between $350-1200 per year, depending on who’s actually telling the truth), the current government felt enough pressure to agree to reduce the HST to 10% from 12% AND to hold a referendum on the tax itself.

So, here I sit, with a referendum ballot on my desk, choosing between the Anti-HST side [Warning, following that link will expose you irrational arguments], claiming that a tax is undemocratic, and the pro-HST side that now thinks it’ll be able to operate with the equivalent of a ~20% cut to revenue. Neither one is looking too smart going into this battle.

Furthermore, the referendum, being conducted by mail, comes with the following instructions:

  1. Mark an X or Checkmark in ONE of the two circles next to the question
  2. Remove the ballot allong the dotted line
  3. Put the ballot in the Secrecy Envelope (A), close and seal the envelope
  4. Put the Secrecy Envelope (A) in the Certification Envelope (B), close and seal the envelope
  5. Complete the [form on the] Certification Envelope (B) […]
  6. Put the Certification Envelope (B) in the yellow ballot package envelope (C), seal the envelope
  7. Put the yellow ballot package envelope in the mail […]

The ratio of envelope to ballot is obscene (BC probably lost a forest for this ballot) and, in case you didn’t notice, step 6 forgets to tell you to close the envelope before you seal it. Oops.

So, in the end, I’ve cast my vote and checked off the No to “extinguishing the HST“, and see if the government can operate with a 10% HST, instead of going back to a system in which taxes are collected twice on the same items.  We might all be poor in the future, but we will at least be a little more efficient.

British Columbia, you may be the best place on earth ™ but this whole affair is insane.

Copenhagenomics 2011, in review

It’s early Saturday morning in Copenhagen and Copenhagenomics 2011 is done.  I was going to say that the sun has set on it, but the city is far enough north that the sun really doesn’t do much more than sink a bit below the horizon at night.  That said, the bright summer sunshine has me up early – and ready to write out a few thoughts about the conference.

[Yes, for what it’s worth, I was invited to blog the conference so I may not be completely impartial in my evaluation, but I think my comments also reflect the general consensus of the other attendees I spoke to as well.  Dissenters are welcome to comment below.]

First, I have to say that I think it was an unqualified success.  Any comments I might have can’t possibly amount to more than suggestions for the next year.  The conference successfully brought together a lot of European bioinformaticians and biologists and provided a forum in which some great science could be shown off.

The choice of venue was inspired and the execution was flawless, despite a few last minute cancellations.  These things happen, and the conference rolled on without a pause.  Even the food was good (I didn’t even hear Sverker, a vegetarian Swede, complain much on that count) and the weather cooperated, clearing up after the first morning.

As well, the conference organizers’ enlightened blogging and twittering policy was nothing short of brilliant, as it provided ways for people to engage in the conversation without being here first hand.  Of course, notes and tweets can only give you so much of the flavour – so those who did attend had the benefits of the networking sessions and the friendly discussions over coffee and meals.  The online presence of the conference seemed disproportionately high for such a young venue and the chat on the #CPHx hashtag was lively.  I was impressed.

With all that said, there were things that could be suggested for next year.  Personally, I would have liked to have seen a poster session as part of the conference.  It would have been a great opportunity to showcase next-gen and bioinformatics work from across europe.  I know that the science must be there, hiding in the woodwork somewhere, but it didn’t have the opportunity to shine as brightly as it might have.  It also would have served to bring out more graduate students, who made up a small proportion of the attendees (as far as I could tell). Next year, I imagine that this conference will be an ideal place for European companies and labs to do some recruiting of young scientists – and encouraging more graduate students to attend by submitting posters and abstracts would be a great way to facilitate that.

Another element that seemed slightly off for me was the vendors.  They certainly had a presence and were able to make their presence noticed, but the booths at the back of the room might not have been the best way for companies to showcase their contributions.  That said, I suspect that copenhagenomics will have already outgrown this particular venue by the next year anyhow and that it won’t be a concern moving forward.

While I’m on the subject of vendors, what happened to European companies like Oxford Nanopore, or the usual editor or two from Nature?  Were some UK attendees scared off by the name of the conference?  I’m just putting it out there – it’s entirely possible that I simply failed to bump into their reps.

In any case, the main focus of the conference, the science, was excellent.  There were a few fantastic highlights for me.  Dr. John Quackenbush‘s talk challenged everyone to seriously re-consider how we make sense of our data – and more importantly, the biology it represents.  Dr. Elizabeth Murchison‘s talk on transmissible cancers was excellent as well and became a topic of much conversation.  Heck, three of my fellow twitter-ers were there and each one did a great job with their respective talks. (@rforsberg, @dgmacarthur and @bioinfo)

In summary, I think the conference came off about as smoothly as any I’ve seen before – and better than most.  If I were given the opportunity, this would be a conference I’d pick to come back to again. Congratulations to the organizers and the speakers!

New ideas

It’s 6:00am, with three hours before Copenhagenomics and I’m solidly awake.  Jet lag is annoying, at best, but it’s been a great week of travelling and visiting in Denmark.  The interesting thing for me has been how stimulating it has been as well – even before the conference has started.

Part of that has just been getting myself out of the thesis mindset.  I’ve gone from being focussed on wrapping up my project to thinking a little further out.  That is, what would I work on if I were not summarizing my past work for my thesis. It was a question put to me by a bioinformatician at CLC bio, and I like sore tooth, I just can’t stop playing with it.

Because of it, I’ve come up with some wonderful ideas.  I guess this, to me, is just reinforcing the idea that sabbaticals really do work.  Even if the break from writing is short, just breaking out of the artificial walls I’d built around myself to keep myself from getting distracted from my thesis and papers has been a productive change.  Interacting with new people has been a great catalyst.

I’m really looking forward to the conference this morning and the opportunity to interact with more people and spark even more new ideas, but now I’m also looking forward to going home and getting my thesis done.  I have things I want to do and all this writing is standing in the way.

Interview with the Student Biotech Network

The Student Biotech Network is a really neat organization, and one that has played a big part in my career – both directly and indirectly.  One of the original three founders, Ali Tehrani, sat across the lab bench from me when I was doing my masters degree – and became my “partner-in-crime” during the founding of Zymeworks.  In fact, Zymeworks had some early ties to the SBN in terms of leadership, mentoring and contacts.  Furthermore, it was through my participation in the SBN that I was introduced to entrepreneurship – and that was really the first time I’d considered a non-academic path for my career.

In any case, when the SBN asked, I was very happy to do a quick interview with them via email and share a bit back with an organization that has had a really big influence on my career. If you’re interested in reading it, you can find it here.

If you’re looking for interviews with Ali, here are three that I am aware of (and they’re pretty good too!):  Capitalist Chicks (2007), Business in Vancouver (2008) and BioscienceWorld. You’ll notice that the SBN gets a few mentions there as well. (-;

Cancer as a network disease

A lot of my work these days is in trying to make sense of a set of cancer cell lines I’m working on, and it’s a hard project.  Every time I think I make some headway, I find myself running up against a brick wall – Mostly because I’m finding myself returning back to the same old worn out linear cancer signaling pathway models that biochemists like to toss about.

If anyone remembers the biochemical pathway chart you used to be able to buy at the university chem stores (I had one as a wall hanging all through undergrad), we tend to perceive biochemistry in linear terms.  One substrate is acted upon by one enzyme, which then is picked up by another enzyme, which acts on that substrate, ad nauseum.  This is the model by which the electron transport cycle works and the synthesis of most common metabolites.  It is the default model to which I find myself returning when I think about cellular functions.

Unfortunately, biology rarely picks a method because it’s convenient to the biologist.  Once you leave cellular respiration and metabolite synthesis and move on to signaling, nearly all of it, as far as I can tell, works along a network model.  Each signaling protein accepts multiple inputs and is likely able to signal to multiple other proteins, propagating signals in many directions.  My colleague referred to it as a “hairball diagram” this afternoon, which is pretty accurate.  It’s hard to know which connections do what and if you’ve even managed to include all of them into your diagram. (I wont even delve into the question of how many of the ones in the literature are real.)

To me, it rather feels like we’re entering into an era in which systems biology will be the overwhelming force for driving the deep insight.  Unfortunately, our knowledge of systems biology in the human cell is pretty poor – we have pathway diagrams which detail sub-systems, but they are next to imposible to link together. (I’ve spent a few days trying, but there are likely people better at this than I am.)

Thus, every time I use a pathway diagram, I find myself looking at the “choke points” in the diagram – the proteins through which everything seems to converge.  A few classic examples in cancer are AKT, p53, myc and the Mapk’s.  However, the more closely I look into these systems, the more I realize that these choke points are not really the focal points in cancer.  After all, if they were, we’d simply have to come up with drugs that target these particular proteins and voila – cancer would be cured.

Instead, it appears that cancers use much more subtle methods to effect changes on the cell.  Modifying a signaling receptor, which turns on a set of transcription factors that up-regulates proto-oncogenes and down-regulates cancer-supressors, in turn shifting the reception of signalling that reinforce this pathway…

I don’t know what the minimum number of changes required are, but if a virus can do it with only a few proteins (EBV uses no more than 3, for instance), then why should a cell require more than that to get started?

Of course, this is further complicated by the fact that in a network model there are even more ways to create that driving mutation.  Tweak a signaling protein here, a receptor there… in no time at all, you can drive the cell in to an oncogenic pattern.

However, there’s one saving grace that I can see:  Each type of cell expresses a different set of proteins, which affects the processes available to activate cancers.  For instance inherited mutations to RB generally cause cancers of the eye, inherited BRCA mutations generally cause cancers of the breast and certain translocations are associated with blood cancers.  Presumably this is because the internal programs of these cells are pre-disposed to disruption by these particular pathways, whereas other cell types are generally not susceptible because of a lack of expression of particular genes.

Unfortunately, the only way we’re going to make sense of these patterns is to assemble the interaction networks of the human cells in a tissue specific manner.  It won’t be enough to know where the SNVs are in a cell type, or even which proteins are on or off (although it is always handy to know that).  Instead, we will have to eventually map out the complete pathway – and then be capable of simulating how all of these interactions disrupt cellular processes in a cell-type specific manner.  We have a long way to go, yet.

Fortunately, I think tools for this are becoming available rapidly.  Articles like this one give me hope for the development of methods of exposing all sorts of fundamental relationships in situ.

Anyhow, I know where this is taking us.  Sometime in the next decade, there will need to be a massive bioinformatics project that incorporates all of the information above: Sequencing for variations, indels and structural variations, copy number variations and loss of heterozygosity, epigenetics to discover the binding sites of every single transcription factor, and one hell of a network to tie it all together. Oh, and that project will have to take all sorts of random bits of information into account, such as the theory that cancer is just a p53 aggregation disease (which, by the way, I’m really not convinced of anyhow, since many cancers do not have p53 mutations).  The big question for me is if this will all happen as one project, or if science will struggle through a whole lot of smaller projects.  (AKA, the human genome project big-science model vs. the organized chaos of the academic model.)  Wouldn’t that be fun to organize?

In the meantime, getting a handle on the big picture will remain a vague dream at best, and tend to think cancer will be a tough nut to crack.  Like my own work and, for the time being, will be limited to one pathway at a time.

That doesn’t mean there isn’t hope for a cure – I just mean that we’re at a pivotal time in cancer research.  We now know enough to know what we don’t know and we can start filling in the gaps. But, if we thought next gen sequencing was a deluge of data, the next round of cancer research is going to start to amaze even the physicists.

I think we’re finally ready to enter the realms of real big biology data, real systems biology and a sudden acceleration in our understanding of cancer.

As we say in Canada… “GAME ON!”

My lesson learned.

One shouldn’t often engage in a war of words with people who comment on blogs on the Internet.  It’s rarely productive.  In this case, there are a few points I could clarify by responding to a comment with a particularly ugly tone, especially given that it was written by someone with an illustrious career in a field related to my own.  They’ve held the position of chair and vice chair of multiple departments, have been a professor since before I was born and have hundreds of publications…  And yet, this individual has chosen to send me a message with the identity “fuckhead” – accusing me of intimidating a junior grad student.  Instead of using his real name, I’ll use the moniker “fuckhead” that he chose for himself, and I’ll post fuckhead’s comments below, interspersed with my reply.

I do need to acknowledge that my tone in my “Advice to graduate students” was somewhat condescending, due to some rather unfortunate word choices on my part.  I have since edited the post for tone, but not for content.  That said, fuckhead’s comment (and unfortunate choice of moniker) was still inappropriate and deserves a reply – and yes, it is a great cathartic release to reply to a negative comment once in a while.

“Coming on the heels of the previous “why I have not graduated yet” post, this is telling”.

Oddly enough, the point of my post on why I haven’t graduated yet was because I’m unable to find any clear signals in the noise in my data set, while my point on advice to other graduate students was about respecting your colleagues, even if it wasn’t necessarily obvious in my first released version of the post.  Putting the two together might allow for a few interesting conclusions – although I would suggest that it is not the ones that are suggested in the comment.

“It’s one thing to intimidate a student out of the way (rather simple, actually, if you have the slightest clue what you are doing), but what you espouse here will poison you. So you’ve been working on the topic for a while, and some meatball comes along and asks you about the topic, and your reaction is ‘get bent’? What will you tell people when they ask what you spent X years of your life on in graduate school? ‘Get bent’?”

It should be clear right away that fuckhead really doesn’t know me well.  I run a blog to share information and help other people, I have more than 200 posts (answering questions) on, all of the code I’ve written towards my thesis has been available freely on source forge for 3 years, I’ve dedicated countless hours to helping other bioinformaticians online and always make time to help out my fellow students. (My resume is online somewhere, if you want more than that.) I probably have told a few people to “get bent”, as it were, but in this case, I most certainly didn’t.

It’s rather telling to me that fuckhead didn’t take the time to find out who I am before jumping to the conclusion that I’m obstructive and surly towards my colleagues.  I can be gruff when people don’t take the time to think through their questions, but I always take the time to listen to my colleagues and help them find the information they need.  If my tone is a bit gruff sometimes, we all have off days – and it’s an inherent danger of insufficient blog editing as well.

“Do you think that you are going to cure cancer, or are you trying to make a little tiny dent in the vast universe of ignorance that surrounds humankind?”

Wow… leading question.  While I do joke that my job is to “cure cancer”, I’m fully aware that expectations for graduate students are low and making a “little tiny dent in the vast universe of ignorance” is where the bar is normally set.  In case it wasn’t clear, no one expects me to cure cancer while working on my doctorate.

That said, who’s to say that neither myself nor the incoming graduate student can’t be the one who does find an important cure? Why hobble myself by agreeing to do no more than meet your base expectations.? Fuckhead doesn’t say why he thinks I shouldn’t have big goals – or why he thinks I’m incapable of meeting them.  Nor does he explicitly state his underlying assumption, which is clear here.  To paraphrase: “You’re just a lowly graduate student, and thus you aren’t the one doing the important work.”

For the record, I like to think big – and I like to achieve my goals.

“And if you are after the latter, why not start off with the ignorant student that approached you?”

Ironically, since fuckhead’s main point is that he thinks I’m intimidating junior colleagues, his tone is oddly lacking in self reflection.  The implication that I haven’t helped the graduate student already is plain – and plain wrong.  However, that is between myself and the student, and we are in the process of establishing a better relation on stronger co-operation where my time is respected and the students needs are better met.  After all, that is the goal:  By getting the student to ask more focused questions, he’ll get better answers.

Further, given that I am fuckhead’s junior colleague, I have to ask why he chose to respond to my post with such venom.  He could have taken the time to set me straight by leading me to see his point, rather than writing a biting comment that chastises me for being rude to those who have less experience than I.

Irony, anyone?

“If you have lots of good ideas, some dolt stealing one of them won’t hurt you.”

I’m not afraid of people stealing my work, but one should recall the context of my comments.  Frankly, I am a strong believer in open source and collaborative work and if you want to see the code I’m working on this week, all you have to do is download my work from source forge.

Unfortunately, in academia, one generally doesn’t release data until it’s published – that is the default position – and one I have openly questioned in the past.  But, if I want someone’s unpublished results, I go to them with the respect for the work that went into it.  It is as simple as that.

Besides, as someone with an entrepreneurial past, I’m well aware of the value of ideas. One does not disclose the “secret sauce” to competitors without an NDA (non-disclosure agreement), but when it comes to investors, you have to respect their time and effort and be aware that your idea has no value until you’ve done something with it – and even then, it’s still not the idea itself that has value.

However, the proof is in the pudding, as they say.  If I were afraid of people stealing my ideas, would I be blogging them?

“If you don’t have lots of good ideas, how the hell will you survive on your own as a researcher?”

I haven’t the foggiest clue.  I’ve never found myself lacking in ideas, although I’m shying away from the academic career path for this very reason.  I know the value of sharing ideas and of working in a group to combine and improve ideas.  Unfortunately, I don’t see that kind of environment being created in academia where professors competing for a small pool of grant money hoard their findings so that others will be less effective in competing with them.

If there’s one thing that I hate, it is wasting time reinventing the wheel.  Unfortunately, that appears to be an inherent part of the academic process.  (I’m not talking about independently confirming results, which is an inherent and important part of the scientific method.)

To wrap things up, yes, I’ll go quietly back into my little bubble of the universe in which I will quietly battle the raging sea of ignorance around me, but I can’t promise that I’ll stay there.  However, even as I fade quietly back into obscurity, I do plan to learn from my mistakes and to let others learn from them as well.

The hard lesson I learned today was to watch my own tone when communicating on the Internet, to keep myself from unintentionally sounding arrogant and condescending.  I’d be happy to pass the same lesson on to you, fuckhead.

Why I haven’t graduated yet and some corroborating evidence – 50 breast cancers sequenced.

Judging a cancer by it’s cover tissue of origin may be the wrong approach.  It’s not a publication yet, as far as I can tell, but summaries are flying around about a talk presented at AACR 2011 on Saturday, in which 50 breast cancer genomes were analyzed:

Ellis et al. Breast cancer genome. Presented Saturday, April 2, 2011, at the 102nd Annual Meeting of the American Association for Cancer Research in Orlando, Fla.

I’ll refer you to a summary here, in which some of the results are discussed.  [Note: I haven’t seen the talk myself, but have read several summaries of it.] Essentially, after sequencing 50 breast cancer genomes – and 50 matched normal genomes from the same individuals – they found nothing of consequence.  Everyone knows TP53 and signaling pathways are involved in cancer, and those were the most significant hits.

“To get through this experiment and find only three additional gene mutations at the 10 percent recurrence level was a bit of a shock,” Ellis says.

My own research project is similar in the sense that it’s a collection of breast cancer and matched normal samples, but using cell lines instead of primary tissues.  Unfortunately, I’ve also found a lot of nothing.  There are a couple of genes that no one has noticed before that might turn into something – or might not.  In essence, I’ve been scooped with negative results.

I’ve been working on similar data sets for the whole of my PhD, and it’s at least nice to know that my failures aren’t entirely my fault. This is a particularly difficult set of genomes to work on and so my inability to find anything may not be because I’m a terrible researcher. (It isn’t ruled out by this either, I might add.)  We originally started with a set of breast cancer cell lines spanning across 3 different types of cancer.  The quality of the sequencing was poor (36bp reads for those of you who are interested) and we found nothing of interest.  When we re-did the sequencing, we moved to a set of cell lines from a single type of breast cancer, with the expectation that it would lead us towards better targets.  My committee is adamant  that I be able to show some results of this experiment before graduating, which should explain why I’m still here.

Every week, I poke through the data in a new way, looking for a new pattern or a new gene, and I’m struck by the absolute independence of each cancer cell line.  The fact that two cell lines originated in the same tissue and share some morphological characteristics says very little to me about how they work. After all, cancer is a disease in which cells forget their origins and become, well… cancerous.

Unfortunately, that doesn’t bode well for research projects in breast cancer.  No matter how many variants I can filter through, at the end of the day, someone is going to have to figure out how all of the proteins in the body interact in order for us get a handle on how to interrupt cancer specific processes.  The (highly overstated) announcement of p53’s tendency to mis-fold and aggregate is just one example of these mechanisms – but only the first step in getting to understand cancer. (I also have no doubts that you can make any protein mis-fold and aggregate if you make the right changes.)  The pathway driven approach to understanding cancer is much more likely to yield tangible results than the genome based approach.

I’m not going to say that GWAS is dead, because it really isn’t.  It’s just not the right model for every disease – but I would say that Ellis makes a good point:

“You may find the rare breast cancer patient whose tumor has a mutation that’s more commonly found in leukemia, for example. So you might give that breast cancer patient a leukemia drug,” Ellis says.

I’d love to get my hands on the data from the 50 breast cancers, merge it with my database, and see what features those cancers do share with leukemia.  Perhaps that would shed some light on the situation.  In the end, cancer is going to be more about identifying targets than understanding its (lack of ) common genes.