 Thanks, Larry. So it's a pleasure to be here on this occasion, the opening of the exhibit that salutes the work that's been done, the field of genomics, and the promise of genomics. And I think my job is to give you the perspective of somebody whom over the last 30 years is gone from being one of the foot soldiers in the trenches to try to figure out how to actually do all this DNA sequencing stuff to about 10 years ago becoming the director of one of the three large-scale genome centers that are funded by the NHGRI. So about in the mid-to-late 1980s, I was a postdoctoral fellow at Caltech working with a guy named Leroy Hood. And the group that I was working in was trying to develop automated DNA sequencing. We'd been doing DNA sequencing for several years. We used lots of radioactivity and things like that to actually get results. It was slow, manual, hard to do, and we didn't really get all that much data out of every experiment that we did. So we set about developing a technology that was much safer, much more automated, much more efficient, and hopefully cost quite a bit less than what it cost to do sequencing the way we did it in the mid-80s. And while I was working in the lab, my boss would occasionally come back from these meetings where they discussed the possibility of sequencing the human genome project. What did we think about that? And we said, yeah, that's a great idea. We think you should continue going to these meetings. But we'd get together at our post-doc lunches and say, this is crazy, but what the heck? Sounds like a good idea. And yeah, you know, we can kind of see what the benefits for this would be. So I think we should go for it. In 1990, I moved to Washington University in St. Louis with one of the first genome sequencing grants that came from what was then known as the National Center for Human Genome Research. And our grant basically had two goals. The first was to begin to sequence the genome of a model organism called C. elegans, which is a little roundworm, that is interesting mainly because it's taught us a lot of important biology, including apoptosis, which is programmed cell death, which has become very important in a number of human diseases, including cancer. As well as to start to build the infrastructure, the methods, some of the software, et cetera, that would be instrumental or indeed critical for actually thinking about sequencing even the first human chromosome, let alone the human genome. So this went well. Back in those days, we did draw parallels to the space program, as Eric touched on. And you know, we made a goal as a nation to land a man on the moon and bring him safely back to the planet Earth only after we'd realized very modest success in launching a few rockets, a few of which didn't explode, and the most recent at the time of which actually carried a human into suborbital flight. And that's kind of the same situation that we sort of saw in front of us. So we had to sequence three billion base pairs of genome, and we really needed to do about six times that. That's what we needed, we believed to be very accurate. So about 18 billion bases of the genome. And at the time, in 1990, one person could go off, spend a day in the lab, and generate about 12,000 base pairs of DNA sequence information. So we figured we needed about a million and a half person days, about 4,000 years, to actually get the job done. And it was expensive sequencing. This is why we just didn't get 1,000 people and expect them each to spend four years getting the job done. You know, the goal for the genome project in the early 90s was to be able to sequence a genome for less than a dollar a base. And I can remember going to the Cold Spring Harbor meeting, I think in about May of 1992 and reporting on the beginnings of the C. elegans genome sequencing project. And we'd done about a half a million bases, which was amazing accomplishment in those days. But Richard Gibbs, who is now the director of one of the other centers, raised his hand at the beginning of the Q&A and said, how much was the cost per base, Rick? And I said, well, it was $17 a base. There was a lot more than sequencing that had been done with those funds, a lot of development and so forth. But that's about the level that we were at, and we still had a long way to go. And if you think about computing, which was another challenge that we had back then, I actually had a portable computer in 1990. It didn't have a battery. You couldn't call it a laptop. If you actually tried to use it on your laptop, you might injure your leg. You could take it home and plug it in. And if you think about what we have 10 years later and about the time the genome project was finished the first time, the advances in computing technology are incredible. But we did it. By 2000, we had a draft of the human genome sequence. By 2003, we had a largely finished encyclopedia of the human genome that we could use. Sequencing technology evolved rapidly, but large-scale centers were really critical in this project. There were several large centers in the U.S. at the time, funded by either what had then become NHGRI or by the Department of Defense. But there were also centers in many other countries around the world, including the Sanger Center in the U.K. At the peak of our sequencing work, about the time the genome project was finished, we had 135 of these expensive, complicated DNA sequencers. As Eric touched upon, one of the key things that we had going for us were companies like Applied Biosystems, who was really the major manufacturer of the key technology throughout the 90s. The companies could take technology that was developed sometimes in academia, sometimes at companies, and commercialize and most importantly harden these technologies into boxes that we could use in the labs to get the job done. They were supported and they were repaired by the companies. But the centers really had a key role in sort of focusing on the methods, the applications, the software development, all the things that really made those sequencing instruments a powerhouse. So by 2003, we could sequence a human genome, as Eric sort of said, for something in the $15 to $20 million range. I would argue that it probably took a couple of years, at least, rather than a few months. But as sequencing technology has continued to develop in the years since the Human Genome Project was finished, I mean, it's been amazing. The biggest breakthroughs came in the mid-2000s as we started to get our hands on what is known as next-generation sequencing technology. And today, in 2013, we can actually sequence an individual human genome and analyze that sequence for a cost of around $10,000, and we can do that in two to three months. Sorry, two to three weeks. And I'll talk a little bit more about this in a minute. Well, since 2003, we've really focused on several crucial next steps that have really built upon the Human Genome Project. We continued to refine the reference human genome sequence. It's the gold standard by which genomic sequencing and medicine is currently performed. It's what we use to understand the biology of genomes and of human cells and animal cells as well. It was about 98 percent complete in 2003 when we declared victory. Some of the regions that remained unfinished were essentially impossible to resolve with the technology and the methods that we had then. And we knew that some of these regions contained important human disease genes. Several of them contain the kind of variation that Eric touched upon in his talk, which we refer to as structural variation. And those regions are characterized by very repetitive elements and are just almost impossible to sort out with the technologies that we were using even six or seven years ago. Well, we've resolved many of these through the aegis of the Genome Reference Consortium. My lab in St. Louis is part of this, as is the Sanger Institute, the National Center for Biotechnology Information in the European Bioinformatics Institute. And by bringing in some of the new technology that's come available over the last couple of years, we've laid in plans to sort of take this gold standard to a platinum standard. The other key thing about the reference human genome sequence is that it largely comes from a single individual. And as you just heard Eric very nicely illustrate, there's a tremendous amount of variation within the human population around the globe. And it's really critical that we start to capture more and more of that. A thousand genomes project was a great start that we need to get deeper into key ethnic groups and really build sort of that utility into the reference. This is going to be absolutely critical as we move ahead and start to bring genomics into the clinic. With projects like ENCODE, we've come a long way in understanding all of that non-coding DNA. There are regions where, as Eric mentioned, they code for little bits of RNA that have their own sort of atypical function. There are places where important proteins bind with the genome to turn genes on and off. And I would argue that an understanding in diseases like cancer of what secondary functions turn genes on and off at the right time or in the right or even more concernedly, in the wrong cell type, is perhaps more critical than the mutations that we find in the genes themselves. And with projects like HapMap and Thousand Genomes, we've really made a huge leap forward in starting to understand the diversity of the human population. It's going to be absolutely critical to better understand this so we can start to understand why some population groups are more susceptible to certain types of diseases. And by sequencing animal and pathogen and plant genomes and understanding their biology and comparing their genome sequences and their biology to our own genome sequence and our own biology, we've come to better understand not only ourselves but the other living things on the planet that might help or harm us. Again, NHGRI and the large scale centers have really been key in driving this work forward. When the Human Genome Project was proposed back in the mid to late 1980s, one reason to do this was that we would better understand disease. We would accelerate our ability to diagnose disease effectively, develop new treatments, and eventually cure many human diseases. I'm proud to have played a role in two of the signature projects that are both represented in the exhibit down on the second floor. And these had made very, very fundamental use of the human genome reference sequence and the methods and technologies that we developed to get to that point and in the years since. So the two I'll just give you quick examples of are TCGA and HMP, known by acronyms as many things at NIHR. You heard about TCGA, the Cancer Genome Atlas, which was a joint project between NHGRI and the National Cancer Institute. And basically what's going on in that project is that the large scale centers, sequencing centers, have collaborated with a number of cancer biology labs to start to build a very comprehensive genetic catalog of several different types of cancer. It's been amazing to see the results that have come out of that, and I'll touch on a few of those in a minute. But basically for several different types of cancer, like breast cancer, like lung cancer, we've been able to genetically dissect several different forms of those cancers. So for example, in both lung cancer and breast cancer, there are several subtypes of disease, which really weren't even known very well five, 10 years ago. So now we can understand that some of these patients come to the clinic with a completely different disease. And in the case of lung cancer patients, quite often, lung cancer patients who have no smoking history are often expected to have a mutation in a gene called EGFR, Epidermal Growth Factor Receptor. And we can now test for that. And if they have a mutation in their EGFR gene, instead of giving them the very nasty types of radiation and chemotherapy, we can give them a new class of drugs called tyrosine kinase inhibitor with very few side effects. And in some patients, a very dramatic response. In some patients, the tumors just essentially melt away. But not all patients respond the same way. And so again, we need to dig a little deeper and better understand what populations are gonna be more susceptible to this particular subtype of cancer, which types of patients are gonna be more apt to respond to these new classes of drugs. The other project that I wanna mention was called HMP, the Human Microbiome Project. And here we've been able to use all of this large scale sequencing technology to start to catalog the population of microbes that are present in our GI tract, in the insides of our mouth and nasal passages that are carried around with us all the time. And there's a pretty good hypothesis that as our health status changes, if we become ill, or maybe as a cause of becoming ill, there's a change in these microbial populations. And so this is sort of one of the new areas over the last few years of genomics. And again, the technology, the methods, the software, the infrastructure that were developed during the genome project have made these kinds of things possible. Well, to talk a little bit more about cancer, in 2008, using this next generation sequencing technology that I mentioned a little earlier, my lab at Washington University was able to publish the first report of the genome sequencing of a cancer patient. And the patient was a woman who lived in St. Louis and had been diagnosed with acute myeloid leukemia. We actually sequenced two genomes from that patient. Her normal genome, which came from some skin cells, which were taken at the time that she had her first bone marrow biopsy, and her tumor DNA, which actually came from the bone marrow biopsy itself. So it blew our mind that we could actually make this work. We used this new technology. It actually took us a couple years, not so much to do all the sequencing for that patient, but to develop the software tools and to try to understand how to deal with the enormous amount of data that we had generated from this new technology. But it worked. In her tumor genome, we found 10 mutations in genes. And we now know several years later after sequencing a couple hundred more patients with acute myeloid leukemia, we know the two genes that we saw mutations in that ultimately caused her disease. So just in our lab alone, since that first cancer patient's genome, we've sequenced the genomes of over 1500 cancer patients. This, again, is something that I would have had hard time believing around 2000, 2003. But we've done it, again, because of all these new developments. This number includes almost a thousand genomes from pediatric cancer patients. And combined with the work that we've done as part of TCGA, all of this work has really led to some amazing new insights into the biology of cancer. So I could give you examples. One of the things that we learned in our pediatric cancer genome project is we learned how to look at the genome and begin to differentiate in children that have acute lymphocytic leukemia, the ones that have a fairly standard subtype of that disease and probably will do very well on standard chemotherapy from a smaller group of kids who have a very severe and aggressive form of the disease called ETP-AOL, who typically don't fare well unless their treatment is accelerated and very aggressive. So now we can start to think about how we pinpoint those kids very early on in the diagnostic process. In an adult form of a brain cancer called glioblastoma, one of the things that we learned was that in some cases of this brain cancer, there are major mutations made to the mechanism that we all have in ourselves to repair DNA damage. And if you didn't know about that, in a particular patient ahead of time, you might give them one of the most common chemotherapeutic drugs. But what we learned is that in these patients, that particular drug does more harm than good. In fact, it just continues to ravage their genomes and cause even more mutation. So now we can think about how we check for that before we start treatment in those glioblastoma patients. And finally, in the disease I first mentioned, adult acute myeloid leukemia or AML, we now have what we call a genetic playbook that sort of gives us some direction as to which patients probably will fare best with specific treatments. And as we go forward and we get a better association with the things that we found in the genome, with what actually happens as those patients are treated, we're gonna be able to pull this together and really use it in clinical practice. As you heard Eric mention, a number of places around the US have now started to have some very interesting and early experiences with actually trying to do genome sequencing of patients who are currently in the clinic and may have a particularly bad form of cancer or children that have a rare genetic disease. And we've had several cases of these. It's still very hard to do. As I said, the workup, the turnaround time is about a month for a cancer patient and you'd like to turn an answer back to the oncologist much more quickly than that. But that's the best we can do now, although we see a great promise and I'll talk about that in a moment. But for several of these cancer patients whose genomes we've sequenced and be able to give that information back to the treating physicians, this has already saved lives and perhaps the most dramatic example of this, at least in our own experience, was written up in the New York Times by Gina Collada last spring. A case of a physician who was actually part of our group who was diagnosed with a second relapse of acute lymphocytic leukemia, wasn't given a very good prognosis. But in sequencing his genome, we found a mutation that could be targeted with a drug that was approved for kidney cancer. And that was effective, within 12 days he was in a complete remission and he just accepted a position to join the full-time faculty on the 1st of July of this year. So this has been exciting and as Eric touched upon as well, cancer is really one of the first places that we've seen a big impact of the new genomics technology. One of the things about cancer that sort of puts it right in the wheelhouse of modern genomics is that every patient essentially has a built-in control experiment, their normal genome. So we can sequence their normal genome, we can sequence their tumor genome and we can compare and look in the tumor genome for the mutations that have arisen and probably get clues to what actually not only cause their disease, but how we might be able to effectively kill it. And we're now in the large-scale center starting to target these more complex diseases. As Eric mentioned, that include Alzheimer's disease. The large-scale approach is really critical for these because there is no built-in control for every patient. So what we need to do is to sequence lots of people, cases in controls, cases are folks that have a particular disease, controls are the folks that don't have the disease, but because each person is already three million base pairs different within their genome, it's difficult to say is that particular variant related to their disease or simply due to the fact that they're not the same individual whose genome we sequenced earlier. So there's a real need for scale here. We have to look at thousands of people with and without disease. So we've come a long way since those often contentious discussions about whether we should or shouldn't sequence the human genome or whether we would learn much from doing it. We've learned a tremendous amount. We did it, we did it well. And through the human genome project and in the 10 years since, we've developed incredibly powerful methods, technologies, software tools, as well as infrastructure and the ability to manage huge amounts of data. We've learned an amazing amount of relevant human biology. We've also learned an amazing amount of, and useful amount of information about animal and pathogen biology. We've learned valuable and applicable things about human disease and we can start to see how we move those into the clinic. So for somebody like me who's been a part of all of this since the beginning, I can't even remember, 20, 25, 30 years ago, it's exciting and it's satisfying, but I have to say that I'm really the most excited about the next 10 years. I told you earlier that we can now sequence and analyze an individual human genome for about $10,000 in a couple of weeks. But since I sort of sit in this position where I'm able to have a pretty clear understanding of the trajectory for the advancement of sequencing technology, I'm ultimately looking forward to having one of these before 2023. So you guys are sitting there saying, what the hell is he talking about? He already has one of those. It's an iPhone. Well, you're only partially right. This is a prototype Iseak. And the really cool thing about the Iseak is what you can do is there's a little small attachment that hooks on here at the data port. I can pipe that in a drop of blood. I wait a little while. Data is generated. It hits the cloud, uses the knowledge base that we've developed over the next 10 years. That's why it doesn't work now. And in a few minutes to a couple of hours, I get an answer, right? So when the technology gets there and it's fast and it's inexpensive and it's able to take a benefit of all of the work from projects like TCGA, HMP, 1000 Genomes, et cetera, every cancer patient, every child that comes into the hospital with a rare genetic disease will have their genome sequenced effectively, accurately, and at a low cost. So of course to become reality, this will require more hard work. Additional large scale projects to build the underlying knowledge base. And the question earlier about how we do this in a time of ever decreasing budgets is an excellent one. But we have to be optimistic and we have to continue to work hard. And I think just having seen what's happened over the last 25 years with this technology, I told you about my portable computer in 1990, I have no doubt that that vision can become reality. So I'll stop there and I'd be happy to answer questions. So I was gonna hold all questions for maybe the next three of you together. So let me, so I'll go too far though. What I'd like to do is ask Greg Lassiere, the chairman and CEO of Life Technologies to come up and give us a little sense of the state of the industry and tell Rick how long it'll be till you guys make the IC phone and attachment that he would like.