Things have changed for me, radically. I left Harvard School of Public Health back in September, with a heavy heart in some ways because of the great opportunity that HSPH  offered. Some people might think I’m crazy, jumping out of Harvard to go to a clinic at a smaller institution like UMDNJ/RWJ. But I had my reasons.

The reason was opportunity and to make a big impact in patients’ day-to-day lives. At HSPH, I was working on more esoteric problems, though many resulting in changes, possibly, to public health policy or our understanding of public health. At RMA/RWJ, I will be changing patients lives daily, and my bioinformatics work and research will end up in many babies being born. Many parents will be walking away from my bioinformatics analyses with babies in their arms…how cool is that?

I took a leap, nearly sight-unseen, into what was, for me, an exotic metaworld of informatics. It’s not really ‘medical informatics’. It’s medical bioinformatics. Medbioinformatics?

Giving it a name is actually important, in a way. If you care to read about why, jump down below.

Looking for an unrelated topic, I stumbled across a transcript of a talk, ‘You and Your Research’
at Bell Labs given by Richard Hamming in 1986. I think it’s worth reading if you’re a scientist, mathematician or computer programmer.

“In summary, I claim that some of the reasons why so many people who have greatness within their grasp don’t succeed are: they don’t work on important problems, they don’t become emotionally involved, they don’t try and change what is difficult to some other situation which is easily done but is still important, and they keep giving themselves alibis why they don’t. They keep saying that it is a matter of luck. I’ve told you how easy it is; furthermore I’ve told you how to reform. Therefore, go forth and become great scientists!”

For me, the most compelling part of his talk is a question we should all be asking ourselves: what are the most important questions/problems in our respective fields? If we’re not working on them — why not?

Technology is accelerating bioinformatics needs, again, while the current need isn’t diminishing.

This post was meant to be just a brief snapshot aimed at students wondering where bioinformatics is going in 2008 and beyond. What’s the future of bioinformatics? What kind of focus should you develop in the near future? What kinds of skills will you need?

More after the jump, below.

Video lectures are sometimes frowned on as being too ‘canned’ or ‘talking head’-like. I think this depends on the teacher. Video lectures will become increasingly popular as talks can be more readily refreshed and recorded, as the technology matures.

Google is creating an archive of science and tech lectures online. There are some gems on Google video and related sites.

Related sites are also linked to, below.

Some of my favorites:

Hans Bethe’s physics lectures makes quantum theory accessible to anyone on Quantum Physics made Relatively Simple:
I suggest everyone take some time to read about his life on the “About” tab if you are not familiar with the man.

Interviews and lectures by Richard Feynman=

There are also some good lectures on biological sequence analysis, genomes, and semantic web (for instance) through Google.
Some bioinformatics-related videos

Some more off-the-beaten path physics:

A lecture on supersymmetry made at Burning Man 2006

A group of engineers, physicists, biologists, chemists, and mathematicians were sitting together drinking beer and chatting, so the conversation wandered a bit. The topic got on somehow to the lottery, and then we all started relating our ultimate dreams: what would happen if one of us suddenly got a lot of money dropped into their lap?

Many of us decided we’d still be scientists or mathematicians, but do research that would never rely on a grant application again.

At least one of us decided we’d open up a commune or institute and invite in all the students and scientists who had interesting ideas, but who would never get a chance to get funding, much like the FQXi is doing these days (and what a good idea).

Still others said they’d leave science forever and just wander around the world.

I asked the table, why couldn’t we do both? Wander the world, do what we want, and still do science, if we had a lot of money? Several people almost immediately said that it was unusual for anyone to expect to ever publish any ideas in any journals without an affiliation or a set-up lab of some kind. The big-brother-aspect of affiliation was an important thing to consider. The impression was that where you publish from may be closely related to where you publish.

Which brings me to the buzz that’s surrounding e8 and Garrett Lisi’s work on a unified theory of everything. My last educational excursion into theoretical physics was over a decade ago, so I’m not qualified to comment on the details, problems, and successes of his unified theory across e8. But, he and I have some things in common: we have apparently gone to some of the same Burning Man festivals, we both share an interest in physics, and we’re generally non-traditional types of people. I don’t feel uncomfortable commenting on that.

I believe that a valuable contribution that Dr. Lisi is offering the world is the view that someone can live outside the mainstream and still love science and “do science”. Dr. Lisi can do his work on computers, and on paper, and seems to have various methods of support these days, but nobody would call them completely “mainstream”.

Lisi is a good example of how there might be ways of “doing science” that doesn’t require that one takes on a traditional trajectory in academia or industry. However, you’ll likely have to be dogged about it (Lisi’s been working at it for a decade), and pick a field that will be open to, and supported by, alternative ways of publishing ideas to your peers for pre-publication review.

An example of a mechanism for pre-publishing would be the site arXiv . When an author commits an article to arXiv, they are able to share papers and leave them open for searching. While it’s not peer-reviewed, it’s a good mechanism to expose your work to objective criticism while mountain biking at Wompy .

I teach at Brandeis (as most of you know) and have been happy to see three of my former students end up at the Broad Institute as analysts/programmers, doing what they always hoped to do. Someday with their permission I’ll tell you about them. Most of them are over 40, had years of experience in programming, but love bioinformatics and modern biology, and moved into the field to do what they love.

So, it was a pleasant surprise for me today to run into one of my former students at the Harvard Medical School lunchtime Systems Biology Theory Lecture, which is a nice tradition of a good lunch, a whiteboard talk (no powerpoint) and always interesting topics. He was there because he was working with the speaker of Friday (today’s) lecture.

The speaker was a mathematical biologist, Caroline Colijn who is studying mycobacterium tuberculosis. She is doing a double duty between the Broad Institute and the Harvard School of Public Health. Her talk was on flux balance analysis of TB, adding in information to the stochiometric matrix using expression data gotten from cultures of TB treated with treatment drugs.

Speaking of Broad, there is a good talk coming up on epigenomics given by Christoph Bock (Max-Planck-Institute for Informatics, Germany) on Wednesday Oct 31 at 10am in room 1001 in the 7CC Broad Institute building. It will be a lecture on EpiGraph (warning: small PDF from ISMB07). I would paste the entire talk abstract here, but it’s pretty long. Suffice today, the main point of the paper is that there is a “statistical epigenome” that needs to be represented, and they’re developing the tool to do it. Will probably prove to be very interesting.

If you haven’t run across this lecture on Time Management yet and you’re a graduate student, take some time and watch it. You can find the corresponding slides here at the Alice Project

The talk is by Dr. Randy Pausch in 1997 and I wish I had seen it when I was a grad student.

If you haven’t run across Dr. Pausch yet through email, or through the media or browsing Wikipedia yet, you may want to get to know him through his lectures and his projects. He’s helped a lot of people in his life, and by extension many more without realizing it was going to happen that way. He’s someone to listen to, if only that he’s naturally earnest and intelligent, and to paraphrase him in the Time Management talk, “experience is valuable”.

For those who want a shortcut, you can find his famous and fabulous CMU lecture here at Google Video

What follows is my own opinion on the issue based on my perceptions.

I want to point in particular to science faculty, but I suspect this applies across the board to anyone employed in the sciences.

Consider that self-identification and projection are probably significant obstacles to increasing faculty diversity

Increasing faculty diversity will likely require individual and institutional sensitivity for typical human bias towards what is usually termed ingroup identification, where individuals tend to exhibit favorable bias to those people they recognize as belonging to their peer group. This subject is difficult and will likely make many people uncomfortable. However, it is not necessarily the most negative feelings within our personal biases that may be hindering attaining reasonable faculty diversity, but rather more importantly positive bias towards those people whom offer us a quick social shortcut into identification.

An integral part of initiating social interaction (as I understand it) is the establishment of common ground—understanding of another. The projection of “self” onto another person greatly simplifies the process of social interaction as common ground can already be assumed. Communication will seem to go more smoothly. Trust is more easily established through a sense of familiarity, so collaboration might be easier. Some of this identification process likely requires social or class clues, but I’m just going to state the obvious and say that like most species, humans also base self-identification strongly on appearance which is then followed by other social cues.

I argue that self-identification is a limiting factor in compromised social interaction skills. The subtle point is that as professionals, we may not be conscious that we are socially discriminating against another individual if we are not feeling identifiably negative feelings about that person. However, without social identification and common ground, the effects of neutrality are likely as damaging as overt negative feelings could be. Neutrality would be acceptable if we could apply neutral social discrimination across the board and not favor some over others. As social animals, we will find perfect neutrality impossible.

Scientists will generally suffer from this kind of unconscious favoritism, I feel, even more than the average person. Although there are exceptions, in my experience, we scientists are not always known for deft socialization skills which would allow for ease in finding important common ground between us and those with diverse backgrounds. Since scientists make decisions on everything from grants to departmental resources and tenure awards on ‘best fit’, the dangers of social categorization and identification could be quite significant, especially if a significant part of any administrative decision is based on subjective perception.

To consider this issue with a real example, see the article by a former senior MIT faculty member, Dr. Frank Douglas that was also mentioned in Corie’s blog. Dr. Douglas makes the observation that the normal tenure process of discriminating for academic excellence is likely affected by more personal forms of discrimination.

Dr. Douglas decided to resign from MIT on June 3, 2007 as a result of his observation that critical issues for minority faculty at MIT were not likely to be addressed, in his estimation, by the Institute’s administration. Dr. Douglas decided he could not properly fit where an administration was unwilling to address the problems of discrimination in the academic environment, nor did he feel he could he advise young Black faculty as to how they could navigate the tenure process themselves.

Dr. Douglas does not question the tenure process itself, but rather the ability of the tenure process to carefully guard against the biases of personal discrimination.

If the success of the tenure process is partly reflected in an expected diversity of faculty, then one could argue some part of the tenure process may be broken for those departments that radically skew from the observed demographics of their field. Can discrimination for academic excellence be protected or separated from personal forms of discrimination? Might neutrally involving an outside group in the tenure evaluation process protect and educate all parties, from the Universities through the faculty to the applicant?

Examine and diversify science pedagogy

Graduate schools need to examine the pedagogy behind graduate science classes at the least. It has been known for quite some time that females and males have different learning styles.
All my graduate science and mathematics classes at the U. of Michigan were taught by men during my time as a graduate student, with one two-week exception.The more mathematical the science being taught, the less accessible the pedagogy seemed to make the subject to a non-linear or collaborative learner who desires synthesis and discussion with the equations. Some of the faculty were very good at presenting synthesis before calculation, but in most classes I found that I had to work harder than many of my male study-group colleagues because the material seemed to be better taught or designed for their overall learning style. I suggest we change the pedagogy for mathematical sciences to include concept before equations or organize additional resources for non-linear thinkers. It makes for thicker books and more effort on the part of instructors, but can yield better scientific intuition.

Is perceived attractiveness a factor?

Many people are socialized from an early age to assign social roles or worth to others based on how attractive they look. I’ve attended meetings where I’ve been the senior scientist in charge of a project but people were not aware of my role (though I was sitting near the head of a table), and as the conversation started I was addressed/attended to much differently than someone who was perceived to be more attractive. Developing a thick skin is important if you want to be a scientist, as is cultivating a healthy sense of humor, so when I notice that kind of odd behavior, it makes for a secret grin on my part and I move on. However, how do we address this? Female faculty at MIT brought evidence to their administration that they were treated differently than male scientists and MIT has conceded bias against women faculty. The same hazards of self-identification apply as above, probably deeply confounded with human socio-sexual roles. As for attractiveness, I’d hazard to say that most women are not perfectly in line with this culture’s ideal of “highly attractive”, and if some people unconsciously gauge how interesting a woman scientist is by her subjective reproductive worth, we’re not going very far with this science thing.

Why does industry attract more minorities and women?

I’ve known many talented minority and/or female scientists in my time. In fact, many of them work in industry. Why are they in industry and not in academia? It’s not as if industry is less demanding of talent than academia is. I’d say that industry is more demanding on many other levels, and from personal experience, the work can be as intense. The reward system, however, is much different and generally there are more minorities and women in the lower-levels of industry than in academia, though going up the ranks it becomes less diverse once again. Despite this, why are many women and minorities deliberately moving to and remaining in industry and not academia?

Change science culture

Since science culture is based on human values, asking science culture to change is probably as difficult as asking people to stop privately gauging attractiveness in their social interactions with others. However, the science culture in many of the physical sciences values independence and personality. The cult of personality and “big names” could be perceived as having greater value than collaboration and consensus. Projects might seem less important than the labs they’re coming out of. I’m not slamming big labs, here. Excellent scientists should continue to be valued and rewarded, and I’m not bashing those who have good names. I’m pro-achievement. I hope established scientists are encouraged to reach out and collaborate with smaller groups, especially those headed by minority and women scientists.

Also, this is not to say that women and minorities are innocent of playing the “big name” game, but we should encourage students to value collaboration and consensus as much as star status if we expect the scientific population to continue to become more diverse. There is the challenge that good collaborative work may not help distinguish a young faculty member during the tenure process, but I hope money continues to go to collaborative projects that have at least a small training grant for minority and women students/postdocs attached if they can’t get diverse people to join. Which brings me to…

Last, but certainly most important: mentoring
We should all attempt to mentor students and postdocs, and make that a priority. In graduate school, I ended up scrambling alone to figure out what I’d do for a postdoc position. My advisor was helpful but perhaps because of his own schedule could only offer minimal guidance. I’ve heard similar stories from other women scientists—mentorship, or the perception of mentorship—was something that seemed to be lacking in their experience. Departments should make (or continue) efforts to provide mentorship to graduate students (and postdocs) in addition to the mentoring offered by their advisor.

Early mentorship or collaborative projects could also give young scientists the ability to tune themselves into the science culture of their field, which might address several of the challenges in the paragraphs above, including allowing students and postdocs to tailor their own work towards obtaining a faculty position as well as becoming part of—and enriching—the culture of the field they want to enter professionally. MentorNet, a website that pairs underrepresented students with mentors drawn from the scientific community, has recently concluded a study that shows underrepresented students are more likely to value mentoring but may not feel they are getting the mentoring they want.

There’s a lot that needs to be done before we can see women and minorities moving into faculty positions. These were just some suggestions.

This post was selected to be part of Openlab 2007: The Best Science Writing on Blogs 2007

As I write this, many of my colleagues are in Vienna, gathering for the 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB).

I’m not going to attend ISMB this year, unfortunately—a confluence of new job and busy schedule. Next year, ISMB will be closer to home in Toronto. I’m looking forward to it, because it will also give me a good reason to stop by and visit a scientist I know, Professor Laurence (Larry) Moran up at U of Toronto.

Dr. Moran is interested in many things, including the molecular-level effects of evolutionary processes. If you read the Usenet newsgroup talk.origins you’ll find some very good posts by Larry on many topics, including neutral selection. His website linked above has other interesting sites he’s authored, I recommend them. He also blogs at Sandwalk: strolling with a skeptical biochemist

Over the past few years, I’ve had some interesting discussions (sometimes heated) online with Larry on neutral selection, biological “noise”, and alternative splicing. For example, in the past discussions Larry’s viewpoint was that the majority of alternative splicing was noise with some functional exceptions. My viewpoint at the time, back in 2003 or so, was that there was a definite use for alternative splicing with specific examples, and we discussed the possibility that many of the alternative forms were in fact nonfunctional noise that yet provided a selectable background of protein forms for evolution.

Until recently, I had been working at a biopharma company that was interested in alternative splice products…like many other biopharmas at the time. The idea was that the discovery of an alternative splice product would be a chance to get some intellectual property rights on a protein and its use. I had seen countless examples of such alternative splicing products when combing through EST databases. Some genes had a plethora of alternatively spliced forms. In fact, we published a paper on the complexity of a particular GPCR family, the LGR receptors, in Molecular Human Reproduction in which we found several alternatively spliced variants of the receptor that seemed to have expressed protein products that had a functional activity in vivo.

There is other evidence for the complexity and functionality of splice variants, see for example this excellent open access review, Benjamin J. Blencowe Cell, Vol 126, 37-47, 14 July 2006 . The review is complex and detailed and I can only suggest you read it if you’re interested, as I can’t hope to do it justice here. One of its subsections gives a discussion of the global consequence of alternative splicing. Acknowledging the stochastic nature of splicing, and that many transcripts may in fact have no apparent biological function, the author proposes a new level of regulatory complexity: an alternative splicing “network” which may further regulate cellular proceses by providing different isoforms in different contexts—essentially, for specific interaction coordination in different tissues. He writes, “An emerging model is that these subsets of genes may comprise “layers” of gene networks that coordinate specific cellular functions.”

At ISMB/ECCE this year will be several talks specifically discussing alternative splicing, both in evolutionary terms (primates), in humans (ENCODE), and in specific cases of certain proteins.

One such presentation will be by Michael Tress, who was the first author of many on a PNAS paper detailing analysis of manually annotated splice variants in the GENCODE project (Tress et. al, The implications of alternative splicing in the ENCODE protein complement. PNAS 2007 Mar 27;104(13):5495-5500 ) where the authors examined a small segment of the human compliment of alternative splicing: about 2600 annotated transcripts for 487 distinct loci, with an average of 2.53 transcripts per locus. Supporting the papers mentioned in the Blencowe review, the Tress publication finds that in the loci they examined, that ”…these functional alternative isoforms appear to be the exception rather than the rule.” They also conclude that many isoforms may be deleterious based on detailed structural analysis of the protein products, but they note “If alternative transcripts in low numbers do not adversely affect the organism, the selection pressure against exon loss or substitution will be reduced, and the new variants will be tolerated, making large evolutionary changes possible.”

So, where is work on alternative splicing going to lead in the future? Blencowe’s review mentioned that there is a significant number of human SNPs that may cause disease phenotypes by affecting splicing. These diseases may result in aberrant splicing in the affected gene, causing loss of a transcript by nonsense-mediated RNA decay (NMD) or causing loss of a protein domain or protein interaction region, thereby disrupting the operating characteristics of the protein. There will likely be future work in discovering these SNPs and variations leading to alternative splicing. Additionally (also in Blencowe) there will likely be further work in examining patterns of alternative splicing between species, between tissues, and between specific developmental and biochemical contexts.

There is a lot of room for new research on alternative splicing. I recently attended a Gordon conference on Bioinformatics which I cannot discuss in detail as many results were not yet published. However, I can mention that I saw some good talks by Boston labs on alternative splicing: “Cooperative, Compensatory and Context Effects in Pre-mRNA Splicing” by Chris Burge at MIT , and “Polymorphic Splicing in Humans” by Hunter Fraser at the Broad Institute.

So, when I return to Toronto for ISMB 2008 , I plan on having a good visit with Larry, and discussing how he was right in that most of alternative splicing is probably noise. A conversation in his lab in Toronto a few years ago was on the right track: it appears most of sampled human alternative splicing may be selectable noise as there are functional splice variants among that noise that might allow interaction networks to fine-tune their behavior in subnetworks of functionality.

Stochastic processes that rule such effects as non-homologous recombination, alternative splicing or non-specific molecular interactions may be tolerated as they generate a selectable background for occasional evolutionary leaps. In the cases where suboptimal splice products may become dominant in a system for a gene with an essential role, a higher population of nonfunctional variants may lead to sub-optimized networks, which in humans yield phenotypes of disease.

I try not to get too concerned with the content of political debates when elections are in the preliminary stages. I inevitably find candidate opinions that I don’t agree with (to put it mildly) and those candidates often don’t make it to the primary stages anyway. For me, examining all candidates at this stage is kind of like watching a forensic snapshot of political opinion in the U.S.

So, when I read the CNN article entitled, Debate evolves into religious discussion I wasn’t surprised to find that three candidates for the Republican Presidential ticket are once again bashing one of the best supported scientific theories in favor of their own faith.

Throwing reason to the winds in favor of a gut feeling or faith might be occasionally viewed as personally irresponsible in a day-to-day setting, but if a religiously-motivated ‘gut feeling’ is held by a public figure with authority and power over armed forces, it could be dangerous.

Suppose a President had a gut feeling that we should go to war with another country with opposing religious views? Suppose that gut feeling was based on faith that he or she was guided by a higher power and shaky evidence rather than reason, logic, and lots of evidence? It seems rather apocalyptic—accepting faith over reason, and then hoping to govern with that philosophy. If your cynicism meter is going off, it’s calibrated correctly.

I’ve been following the anti-evolution political camp for a while. In 2003, I was at a Gordon Conference, sitting at a table with other attendees. The anti-evolution topic came up, along with a discussion of the “intelligent design” (ID) movement. I expressed my concern that the ID camp and creationism was something to be concerned about here in the U.S. The other people at the table pooh-poohed my concern, by holding that creationism and the ID movement are made of a bunch of crackpots that couldn’t possibly have any kind of long-term staying power. Reason, they said, would win out in the long run, and creationism and the ID movement would fall by the wayside. I’m afraid that just pooh-poohing this kind of thing isn’t working. We need more education, and we need it fast.

Maybe someone should mention that part of the U.S. economy relies on the tools given by evolutionary theory. Most of us in the molecular biology field know that we use mathematics based on evolutionary principles regularly in understanding biological systems and genomics. Drug discovery, in many ways, depends on evolutionary theory to supply the logical framework and tools around molecule and sequence analysis, as one example. Evolution isn’t “just” an incredibly supported explanation for an extensive collection of facts. It also defines a mathematical tool that allows us to group sequences into a logical order. The industry needs students ready to embrace this kind of science, not deny it.

So, how to educate the next generation in ways that allow them to see the consequences of evolution with their own eyes? How to introduce the new biology into primary or secondary schools? In fact, how do we educate teachers on this subject?

I’m teaching a graduate-level genomics course this semester, and I’m lucky enough to have a couple of high school teachers in my class. It occurred to me this semester that the material in my class—say, one lecture—could easily be adapted to several high school lesson plans. The evidence for evolution, and with it the reasoning behind it, could be presented to the student, in ways that show the obvious sequence-based evidence.

I think the community could develop a strong collection of lessons including sequence analysis and the basis of molecular evolutionary theory in ways that allow students to view the consequences of evolution with their own eyes.

The ‘new biology’ is at a stage where it’s ready to be taught to the high school level. We need teachers able and willing to teach genomics and sequence analysis, and we need computational resources available that will do the analysis on a server-side, so all the students would need are web browsers to do analysis.

There might be molecular-based or sequence-based biology initiatives out there, but I haven’t found many.

We need future scientists, and we need education of the broader public, so that anti-reason positions, like those found in the CNN article above are very, very rare. Molecular biology is a good place to start, and shouldn’t be a topic that’s left for college.