The Truth

What do you think the truth is? That is what do you think the concept of “truth” actually means? Is it an absolute- a destination that you can reach if you just try hard enough? Or is it something else? A road that stretches out in front of you and constantly changes as you progress and add more evidence?



What is a hypothesis?

So I got this comment from a reviewer on one of my grants:

The use of the term “hypothesis” throughout this application is confusing. In research, hypotheses pertain to phenomena that can be empirically observed. Observation can then validate or refute a hypothesis. The hypotheses in this application pertain to models not to actual phenomena. Of course the PI may hypothesize that his models will work, but that is not hypothesis-driven research.

There are a lot of things I can say about this statement, which really rankles. As a thought experiment replace all occurrences of the word “model” with “Western blot” in the above comment. Does the comment still hold?

At this point it may be informative to get some definitions, keeping in mind that the _working_ definitions in science can have somewhat different connotations.

From Google:

Hypothesis: a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation.

This definition has nothing about empirical observation- and I would argue that this definition would be fairly widely accepted in biological sciences research, though the underpinnings of the reviewer’s comment- empirically observed phenomena- probably are in the minds of many biologists.

So then, also from Google:

Empirical: based on, concerned with, or verifiable by observation or experience rather than theory or pure logic.

Here’s where the real meat of the discussion is. Empirical evidence is based on observation or experience as opposed to being based on theory or pure logic. It’s important to understand that the “models” being referred to in my grant are machine learning statistical models that have been derived from sequence data (that is, observation).

I would argue that including some theory or logic in a model that’s based on observation is exactly what science is about- this is what the basis of a hypothesis IS. All the hypotheses considered in my proposal were based on empirical observation, filtered through some form of logic/theory (if X is true then it’s reasonable to conclude Y), and would be tested by returning to empirical observations (either of protein sequences or experimentation at the actual lab bench).

I believe that the reviewer was confused by the use of statistics, which is a largely empirical endeavor (based on the observation of data- though filtered through theory) and computation, which they do not see as empirical. Back to my original thought experiment, there’s a lot of assumptions, theory, and logic that goes into interpretation of Western blot – or any other common lab experiment. However, this does not mean that we can’t use them to formulate further hypotheses.

This debate is really fundamental to my scientific identity. I am a biologist who uses computers (algorithms, visualization, statistics, machine learning and more) to do biology. If the reviewer is correct, then I’m pretty much out of a job I guess. Or I have to settle back on “data analyst” as a job title (which is certainly a good part of my job, but not the core of it).

So I’d appreciate feedback and discussion on this. I’m interested to hear what other people think about this point.

The Numerology of License Plates

I posted awhile back about encountering two vehicles with the same 3 letter code on their license plates as mine while driving to work one morning. Interestingly, in the following months I found myself paying more and more attention to license plates and saw at least 6-7 other vehicles in the area (a small three-city region with about 200K residents) with the same code.

Spooky. I started to feel like there was some kind of cosmological numerology going on in license plates around me that was trying to send me a message. BUT WHAT WAS IT?

A conclusion I drew from my thinking on the probability of that happening was that:

it is evident that there can be multiple underlying and often hidden explanatory variables that may be influencing such probabilities [from my post]

It was suggested that part of my noticing the plates could have been confirmation bias, I was looking for something so I noticed that thing more than normal given a pretty variable and unconnected background. I’m sure that’s true. However, I was sitting in traffic one evening (yes, we do have *some* traffic around here) and saw three plates that started with the letters ARK in the space of about 5 minutes. Weird.

So THEN I started really looking at the plates around me and noticed a strong underlying variable that pretty much explains it all. But it’s kinda interesting. I first noticed that Washington state seems to have recently switched from three number-three letter plates to three letter-four number plates. I then noticed that the starting letters for both kinds of plates were in a narrow range, W-Z for the old plates and A-C for the new plates. There don’t seem to be *any* plates outside that range right now (surveying a couple of hundred plates over the last couple of days). W is really underrepresented as is C – the tails of the distribution. This makes me guess that there’s a rolling distribution with a window of about 6 letters for license plates (in the state of Washington, other states have other systems or are on a different pattern). This probably changes with time as people have to renew their plates, buy new vehicles and get rid of the old. So the effective size of the license plate universe I tried to calculate in my previous post is much smaller than what I was thinking.

I don’t know why I find this so interesting but it really is. I know this is just some system that the Washington State Department of Licensing has and I could probably go to an office and just ask, but it seems like it’s a metaphor for larger problems of coincidence, underlying mechanisms, and science. I’m actually pretty satisfied with my findings, even though they won’t be published as a journal article (hey- you’re still reading, right?). On my way to pick up lunch today I noticed some more ARK plates (4) and these two sitting right next to each other (also 3 other ABG plates in other parts of the parking lot).


The universe IS trying to tell me something. It’s about science stupid.


Well, there probably ARE some exceptions here.

Well, there probably ARE some exceptions here.

So I first thought of this as a funny way of expressing relief over a paper being accepted that was a real pain to get finished. But after I thought about the general idea awhile I actually think it’s got some merit in science. Academic publication is not about publishing airtight studies with every possibility examined and every loose end or unconstrained variable nailed down. It can’t be. That would limit scientific productivity to zero because it’s not possible. Science is an evolving dialogue, some of it involving elements of the truth.

The dirty little secret (or elegant grand framework, depending on your perspective) of research is that science is not about finding the truth. It’s about moving our understanding closer to the truth. Often times that involves false positive observations- not because of the misconduct of science but because of it’s proper conduct. You should never publish junk or anything that’s deliberately misleading. But you can’t help publishing things that sometimes move us further away from the truth. The idea in science is that these erroneous findings will be corrected by further iterations and may even provide an impetus for driving studies that advance science. So publish away!

The World Is Magical

Arthur C. Clarke famously wrote:

Any sufficiently advanced technology is indistinguishable from magic.

An excellent quote to be sure, but wrong. And here’s the reason: There is no meaningful difference between magic and science. Stick with me for a minute.

Magic, to be useful, must operate under some rules. We may not know them (as people in the real world or as readers of fiction) but without rules magic simply wouldn’t be very interesting or useful. Gandalf figured out or was taught how to do things. Harry Potter had to go to school to learn the arts of magic. If the magic envisioned in these fictional accounts didn’t adhere to rules it would be pretty useless, right? You can imagine that there may be influences from outside the magician or spell-caster (for example some source of magic that they have to return to, or something similar). And there could be stochastic influences that might render spells useless once in a while. These also are rules and principles. So magic, to be useful, must follow rules.

If you accept that magic has to follow rules (not necessarily the rules of science as currently understood, mind you) then these rules have a basis- a fundamental, underlying structure that allows them to function. And allows witches, warlocks, magicians, and whoever to access them and make use of them. If there is an underlying fundamental structure then humans, using reasonable and careful approaches, should be able to figure out these principles.

How would they do this? Well they would first make a guess about how the magic should function (a hypothesis)- that saying “exploso lignum” and moving your wand in a circle should make wood explode- then test that hypothesis- cast that spell- then evaluate the results. Did the results support the hypothesis?

So magic, as an operating principle of this or a fictional world, can be figured out by a method that is, in fact, the scientific method. Therefore, once you can apply the scientific method, the object of your study is just science. Of course, if your hypothesis isn’t supported (for example, that subjects can correctly identify symbols on cards that are held by another person and not shown to them) then it isn’t magic, and it isn’t science. It isn’t anything.

Science is just a way of figuring out how the world functions. And if one of the organizing structures of a world is magic, then science would be able to figure it out. So any magic we can imagine must be just science (once the rules governing it have been figured out). Note that invoking a divine power doesn’t get around this- the divine power still has to obey rules, even if they can change those rules (how do they decide to change a rule? we should be able to figure that out).


Gandalf, the scientist.


Magic Hands

Too good to be true or too good to pass up?

Too good to be true or too good to pass up?

There’s been a lot of discussion about the importance of replication in science (read an extensive and very thoughtful post about that here) and notable occurrences of non-reproducible science being published in high-impact journals. The recent retraction of the two STAP stem cell papers from Nature and accompanying debate over who should be blamed and how. The publication of a study (see also my post about this) in which research labs responsible for high-impact publications were challenged to reproduce their findings showed that many of these findings could not be replicated, in the same labs they were originally performed in. These, and similar cases and studies, indicate serious problems in the scientific process- especially, it seems, for some high-profile studies published in high-impact journals.

I was surprised, therefore, at the reaction of some older, very experienced PIs recently after a talk I gave at a university. I mentioned these problems, and briefly explained the results of the study on reproducibility to them- that, in 90% of the cases, the same lab could not reproduce the results that they had previously published. They were generally nonplussed. “Oh”, one said, “probably just a post-doc with magic hands that’s no longer in the group”. And all agreed on the difficulty of reproducing results for difficult and complicated experiments.

So my question is: do these fabled lab technicians actually exist? Are there those people who can “just get things to work”? And is this actually a good thing for science?

I have some personal experience in this area. I was quite good at futzing around with getting a protocol to work the first time. I would get great results. Once. Then I would continue to ‘innovate’ and find that I couldn’t replicate my previous work. In my early experiences I sometimes would not keep notes well enough to allow me to go back to the point where I got it to work. Which was quite disturbing and could send me into a non-productive tailspin of trying to replicate the important results. Other times I’d written things down sufficiently that I could get them to work again. And still others I found that someone else in the lab could consistently get better results out of the EXACT SAME protocol- apparently followed the same way. They had magic hands. Something about the way they did things just *worked*. There were some protocols in the lab that just seemed to need this magic touch- some people had it and some people didn’t. But does that mean that the results these protocols produced were wrong?

What kinds of procedures seem to require “magic hands”? One example is from when I was doing electron microscopy (EM) as a graduate student. We were working constantly at improving our protocols for making two-dimensional protein crystals for EM. This was delicate work, which involved mixing protein with a buffer in a small droplet, layering on a special lipid, incubating for some amount of time to let the crystals form, then lifting the fragile lipid monolayer (hopefully with protein crystals) off onto an EM grid and finally staining with an electron dense stain or flash freezing in liquid nitrogen. The buffers would change, the protein preparations would change, the incubation conditions would change, and how the EM grids were applied to our incubation droplets to lift off the delicate 2D crystals was subject to variation. Any one of these things could scuttle getting good crystals and would therefore produce a non-replication situation. There were several of us in the lab that did this and were successful in getting it to work- but it didn’t always work and it took some time to develop the right ‘touch’ to get it to work. The number of factors that *potentially* contributed to success or failure was daunting and a bit disturbing- and sometimes didn’t seem to be amenable to communication in a written protocol. The line between superstition and required steps was very thin.

But this is true of many protocols that I worked with throughout my lab career* – they were often complicated, multi-step procedures that could be affected by many variables- from the ambient temperature and humidity to who prepared the growth media and when. Not that all of these variables DID affect the outcomes but when an experiment failed there were a long list of possible causes. And the secret with this long list? It probably didn’t include all the factors that did affect the outcome. There were likely hidden factors that could be causing problems. So is someone with magic hands lucky, gifted, or simply persistent? I know of a few examples where all three qualities were likely present- with the last one being, in a way, most important. Yes, my collaborator’s post-doc was able to do amazing things and get amazing results. But (and I know this was the case) she worked really long and hard to get them. She probably repeated experiments many, many times ins some cases before she got it to work. And then she repeated the exact combination to repeat the experiments again. And again. And sometimes even that wasn’t enough (oops, the buffer ran out and had to be remade, but the lot number on the bottle was different, and weren’t they working on the DI water supply last week? Now my experiment doesn’t work anymore.)

So perhaps it’s not so surprising that many of these key findings from these papers couldn’t be repeated, even in the same labs. There was not the same incentive to get it to work for one thing- so that post-doc or another graduate student who’s taken over the same duties, probably tried once to repeat the experiment. Maybe twice. Didn’t work. Huh? That’s unfortunate. And that’s about as much time as we’re going to put in to this little exercise. The protocols could be difficult, complicated, and have many known and unknown variables affecting their outcomes.

But does it mean that all these results are incorrect? Does it mean that the underlying mechanisms or biology that was discovered was just plain wrong? No. Not necessarily. Most, if not all, of these high-profile publications that failed to repeat spawned many follow-on experiments and studies. It’s likely that many of the findings were borne out by orthogonal experiments, that is, experiments that test implications of these findings, and by extension the results of the original finding itself. Because of the nature of this study it was conducted anonymously- so we don’t really know, but it’s probably true. This was an important point, and one that was brought up by these experienced PIs I was talking with, is that sometimes direct replication may not be the most important thing. Important, yes. But perhaps not deal-killing if it doesn’t work. The results still might stand IF, and only if, second, third, and fourth orthogonal experiments can be performed that tell the same story.

Does this mean that you actually can make stem cells by treating regular cultured cells with an acid bath? Well, probably not. For some of these surprising, high-profile findings the ‘replication’ that is discussed is other labs trying to see if the finding is correct. So they try the protocols that have been reported, but it’s likely that they also try other orthogonal experiments that would, if positive, support the original claim.

"OMG! This would be so amazing if it's true- so, it MUST be true!"

“OMG! This would be so amazing if it’s true- so, it MUST be true!”

So this gets back to my earlier discussions on the scientific method and the importance of being your own worst skeptic (see here and here). For every positive result the first reaction should be “this is wrong”, followed by, “but- if it WERE right then X, Y, and Z would have to be true. And we can test X, Y, and Z by…”. The burden of scientific ‘truth’** is in replication, but in replication of the finding– NOT NECESSARILY in replication of the identical experiments.

*I was a labbie for quite a few of my formative years. That is, I actually got my hands dirty and did real, honest-to-god experiments, with Eppendorf tubes, vortexers, water baths, cell culture, the whole bit. Then I converted and became what I am today – a creature purely of silicon and code. Which suits me quite well. This is all just to add to my post a “I kinda know what I’m talking about here- at least somewhat”.

** where I using a very scientific meaning of truth here, which is actually something like “a finding that has extensive support through multiple lines of complementary evidence”

Always use the right pen

Spike Lee’s 1989 classic “Do the Right Thing” is about a lot of things. It’s about life in general and I still don’t fully understand it’s message- why did Mookie throw the garbage can through Sal’s window. Was it the right thing to do?

It was NOT about life in academia – but did have elements about the conflict between the creative and destructive influences that I find very compelling. And Radio Raheem’s Love/Hate speech seemed to speak to me in a different way. Anyway, here’s an homage I did for fun.


I dream of science

I had a dream last night- after yesterday hearing about possible furloughs at the lab due to the government shutdown. Here it is:

I was trying to go into a building and needed to go through security. Now that I think of it, it had a lot of similarities with the NIH campus main entrance. I needed to talk to a security guard so I put my bag down. After he asked me what I did- that is, what I studied, I was surprised to find that he was a scientist too. We had an interesting conversation about science. Then I turned around to get my bag (presumably to enter the building). However, I found that someone had completely taken apart my 35 mm camera while my back was turned- it was entirely in pieces, even the lens was just a pile of glass and black metal and plastic parts. I was shocked, angry, and despondent all at the same time.

I’ve been thinking about this dream all day and it seems to sum up my career stage, my concerns about making it to the next step and succeeding in science, and my concern over the state of science in the US currently- especially during the shutdown. Imagine that the camera represents my vision of science and security represents the grant/career process, especially with an emphasis on funding organizations. Also the security guard? An alternate ending to the career story. The mind is a wonderful and terrible place when it’s worried about something.

A case for failure in science

If you’re a scientist and not failing most of the time you’re doing it wrong. The scientific method in a nutshell is to take a best guess based on existing knowledge (the hypothesis) then collect evidence to test that guess, then evaluate what the evidence says about the guess. Is it right or is it wrong? Most of the time this should fail. The helpful and highly accurate plot below illustrates why.

Science is about separating the truth of the universe from the false possibilities about what might be true. There are vastly fewer true things than false possibilities in the universe. Therefore if we’re not failing by disproving our hypotheses then we really are failing at being scientists. In fact, as scientists all we really HAVE is failure. That is, we can never prove something is true, only eliminate incorrect possibilities. Therefore, 100% of our job is failure. Or rather success at elimination of incorrect possibilities.

So if you’re not failing on a regular repeated basis, you’re doing something wrong. Either you’re not being skeptical and critical enough of your own work or you’re not posing interesting hypotheses for testing. So stretch a little bit. Take chances. Push the boundaries (within what is testable using the scientific method and available methods/data, of course). Don’t be afraid of failure. Embrace it!

How much failure, exactly, is there to be had out there? This plot should be totally unhelpful in answering that question

How much failure, exactly, is there to be had out there? This plot should be totally unhelpful in answering that question



Us versus them in science communication

This Tweet got me thinking about my grandfather. Gideon Kramer was a great thinker who read widely and was very spiritual and philosophical. He also placed a great emphasis on science, but did not consider himself to be a scientist. When he was alive he would continually challenge me to make my science more approachable by a broader audience. He still does. He once suggested that all scientists should publish a lay version of every technical paper they published so that he (and, of course, others who are interested in science but don’t have the full background) could understand. Something I’m still interested in doing- but totally challenged by. How do you communicate a large amount of assumed knowledge in a way that’s accessible to everyone? He also suggested that I could write a scientific paper not in prose, but in poetry- an idea that is pretty antitheitic to the standard by-the-book scientific paper. Also a challenge I’m still wrestling with.

To a certain extent this is the role that scientific journalism plays – distilling the essence of a scientific study down to easily readable terms and placing it in the broader context of the field and previous research. Some journals (PLoS journals, for example) now require a synopsis of the papers to be provided that will be accessible to a wider audience. I believe for exactly this purpose. This is a more general problem since it does not just pertain to the scientist-layperson  divide, but also within the sciences. I am highly educated. I spent something like 22 years of my life being formally educated in one form or another- and another five in post-doctoarl training, and I’m still educating myself. The problem is, I, like every other scientist I know, have a pretty narrow focus of what I know and what I’m comfortable with. I can’t read physics papers, or chemistry papers, or neuroscience papers, and immediately know what the important parts are or even how to interpret the results from sometimes highly specialized methods of exploring the universe around us. I’m essentially in the same boat as a ‘layperson’ when reading and evaluating these kinds of papers. Of course, just knowing the scientific method and how to read a technical paper in general helps immensely.

So, back to the point of the Tweet: this is certainly a problem. The “them versus us” issues is alive and well. On one side we consider scientists to be living in ivory towers, isolated and above everyone else- and maybe being disconnected from real-world problems (who can support research on duck mating habits?). On the other side we consider laypeople to be slack jawed ignoramuses ready to lay aside the wealth of scientific evidence available for the extremely important issues that confront our world (why don’t people see what a problem the emergence of antibiotic resistance is?). So the divide is as real as we choose to make it.

But here’s the thing: the divide is not nearly as pronounced as we (either side) would seem to make it out. There are plenty of “laypeople” who understand as much, or more, about physics, psychology, or soil ecology, than I do. And there are plenty of “scientists” who think about many things: economics, politics, gender equality issues, and are thought leaders in these areas. There is a great need for better communication though- perhaps through Twitter or similar social media. In fact, there have been several recent social media events that have challenged these boundaries, making science and the process of doing science more real to the general public. I’m talking about the #overlyhonestmethods hashtag (as well as several other similar events), which was criticized for laying things too bare in places, but that I think was a boon to this relationship.

We are human. We make human mistakes. We think about human problems. We do not exist in an ivory tower. We are also athletes, foodies, hipsters, enthusiasts, wives, husbands, partners, parents, lovers, artists, humorists, and trolls. I can only think, and hope, that this will bring down walls rather than putting up more of them.