WEBVTT 00:00:00.000 --> 00:00:02.440 align:middle line:84% - The following content is provided 00:00:02.440 --> 00:00:06.340 align:middle line:84% by MIT OpenCourseWare under a Creative Commons license. 00:00:06.340 --> 00:00:08.470 align:middle line:84% Additional information about our license 00:00:08.470 --> 00:00:10.870 align:middle line:84% and MIT OpenCourseWare in general 00:00:10.870 --> 00:00:12.730 align:middle line:90% is available at ocw.mit.edu. 00:00:12.730 --> 00:00:33.832 align:middle line:90% 00:00:33.832 --> 00:00:35.840 align:middle line:90% GEORGE CHURCH: OK, welcome back. 00:00:35.840 --> 00:00:39.290 align:middle line:90% 00:00:39.290 --> 00:00:42.500 align:middle line:84% We just finished our discussion of predator, prey, and host 00:00:42.500 --> 00:00:47.300 align:middle line:84% parasites illustrating it with ways 00:00:47.300 --> 00:00:53.180 align:middle line:84% that we can have an impact on ecological modeling 00:00:53.180 --> 00:00:58.230 align:middle line:90% in oceans and in public health. 00:00:58.230 --> 00:01:00.800 align:middle line:84% And these kind of considerations start 00:01:00.800 --> 00:01:05.030 align:middle line:84% getting us into what are the global and socioeconomic 00:01:05.030 --> 00:01:06.950 align:middle line:90% considerations? 00:01:06.950 --> 00:01:10.460 align:middle line:84% What kind of impact do these kind of models 00:01:10.460 --> 00:01:14.970 align:middle line:90% have on how we make decisions? 00:01:14.970 --> 00:01:23.310 align:middle line:84% And in this context, I'm glad to be associated with the Genome 00:01:23.310 --> 00:01:23.810 align:middle line:90% Project. 00:01:23.810 --> 00:01:26.360 align:middle line:84% It's one of the first scientific projects 00:01:26.360 --> 00:01:31.850 align:middle line:84% of any reasonable scale that had from the very start, 00:01:31.850 --> 00:01:37.640 align:middle line:84% from the very first proposed funding for it in 1990, 00:01:37.640 --> 00:01:43.500 align:middle line:84% a component of 3% set aside for ethical, legal, 00:01:43.500 --> 00:01:47.450 align:middle line:90% and social issue or LC. 00:01:47.450 --> 00:01:49.520 align:middle line:84% And some of the conflicts that are covered 00:01:49.520 --> 00:01:54.440 align:middle line:84% by the grantees in this part of the Genome Project 00:01:54.440 --> 00:01:59.180 align:middle line:84% were genetic non-discrimination, privacy, reproductive rights, 00:01:59.180 --> 00:02:02.480 align:middle line:84% cloning, psychological stigmatization 00:02:02.480 --> 00:02:05.910 align:middle line:84% that can come from maybe too much knowledge, 00:02:05.910 --> 00:02:07.580 align:middle line:84% clinical quality control, what can 00:02:07.580 --> 00:02:10.009 align:middle line:84% happen with false positives and false negatives 00:02:10.009 --> 00:02:12.975 align:middle line:84% in clinical exams, safety and environmental issues, 00:02:12.975 --> 00:02:15.350 align:middle line:84% such as the ones we were just talking about and some more 00:02:15.350 --> 00:02:18.320 align:middle line:90% that I'll raise. 00:02:18.320 --> 00:02:21.030 align:middle line:84% Uncertainties, not just in quality control, 00:02:21.030 --> 00:02:24.725 align:middle line:84% but in the uncertainties in testing minors. 00:02:24.725 --> 00:02:27.440 align:middle line:90% 00:02:27.440 --> 00:02:31.760 align:middle line:84% Issues of diversity, both biodiversity and human 00:02:31.760 --> 00:02:35.420 align:middle line:84% diversity, and commercialization of the products. 00:02:35.420 --> 00:02:41.540 align:middle line:84% Who owns my cells when I give them to a hospital or a company 00:02:41.540 --> 00:02:42.710 align:middle line:90% to help cure me? 00:02:42.710 --> 00:02:47.120 align:middle line:84% Do they then own all the patent rights? 00:02:47.120 --> 00:02:49.850 align:middle line:84% So the underlined topics are the ones, 00:02:49.850 --> 00:02:51.680 align:middle line:84% the four underlined topics we'll talk about 00:02:51.680 --> 00:02:53.930 align:middle line:90% in the next few slides. 00:02:53.930 --> 00:02:56.750 align:middle line:84% In terms of non-discrimination, this can go any direction. 00:02:56.750 --> 00:02:59.498 align:middle line:84% It will go the direction the market forces push it, 00:02:59.498 --> 00:03:00.290 align:middle line:90% meaning the voters. 00:03:00.290 --> 00:03:02.960 align:middle line:90% 00:03:02.960 --> 00:03:06.710 align:middle line:84% If we want to pass really laws that 00:03:06.710 --> 00:03:10.280 align:middle line:84% say that if George Church sequences his genome 00:03:10.280 --> 00:03:12.860 align:middle line:84% and he has to report that sequence to his insurance 00:03:12.860 --> 00:03:16.140 align:middle line:84% company or worse yet the insurance company is going 00:03:16.140 --> 00:03:18.330 align:middle line:84% and get it before he wants it or not. 00:03:18.330 --> 00:03:20.240 align:middle line:84% But on the other end of the spectrum, and I 00:03:20.240 --> 00:03:23.720 align:middle line:84% hope the trend which will make it much easier for us to share 00:03:23.720 --> 00:03:25.640 align:middle line:90% our data, or use our data-- 00:03:25.640 --> 00:03:30.260 align:middle line:84% that's it-- is that the Non-Discrimination in Health 00:03:30.260 --> 00:03:35.570 align:middle line:84% Insurance and Employment Act was [? docked ?] in 1999, 00:03:35.570 --> 00:03:43.670 align:middle line:84% was introduced and passed, which would extend employment 00:03:43.670 --> 00:03:46.760 align:middle line:84% protections in the government sector 00:03:46.760 --> 00:03:51.830 align:middle line:84% to the private sector to the extent 00:03:51.830 --> 00:03:54.740 align:middle line:90% that that can be generalized. 00:03:54.740 --> 00:03:56.360 align:middle line:84% I don't know exactly where that's 00:03:56.360 --> 00:03:58.550 align:middle line:90% going but one can hope that-- 00:03:58.550 --> 00:04:01.970 align:middle line:84% I mean clearly we will always do some kind of discrimination 00:04:01.970 --> 00:04:08.780 align:middle line:84% based on genetics which can be assessed 00:04:08.780 --> 00:04:15.428 align:middle line:84% such as in an interview, you know, height, friendliness, 00:04:15.428 --> 00:04:16.220 align:middle line:90% that sort of thing. 00:04:16.220 --> 00:04:18.380 align:middle line:84% But we won't necessarily be doing it 00:04:18.380 --> 00:04:21.140 align:middle line:90% based on genetic sequence. 00:04:21.140 --> 00:04:24.080 align:middle line:90% And these are tough issues. 00:04:24.080 --> 00:04:26.420 align:middle line:84% It's the probabilistic nature of the decisions 00:04:26.420 --> 00:04:28.220 align:middle line:84% that you make during an interview 00:04:28.220 --> 00:04:31.080 align:middle line:84% different from the probabilistic decision 00:04:31.080 --> 00:04:33.380 align:middle line:84% you would make based on a DNA scan? 00:04:33.380 --> 00:04:34.692 align:middle line:90% Which is more accurate? 00:04:34.692 --> 00:04:36.150 align:middle line:84% Do you want it to be more accurate? 00:04:36.150 --> 00:04:37.830 align:middle line:84% Do you want it to be less accurate? 00:04:37.830 --> 00:04:38.640 align:middle line:90% So on and so forth. 00:04:38.640 --> 00:04:42.560 align:middle line:84% But clearly there's the trend in terms of legislation 00:04:42.560 --> 00:04:49.370 align:middle line:84% is towards less information being used for discrimination. 00:04:49.370 --> 00:04:51.380 align:middle line:84% Certainly in the insurance level. 00:04:51.380 --> 00:04:54.140 align:middle line:84% And it's appropriate in insurance 00:04:54.140 --> 00:04:59.970 align:middle line:84% because in a way that's supposed to be a process by which risk 00:04:59.970 --> 00:05:00.470 align:middle line:90% is shared. 00:05:00.470 --> 00:05:03.620 align:middle line:90% 00:05:03.620 --> 00:05:05.810 align:middle line:90% So the issue of races. 00:05:05.810 --> 00:05:12.440 align:middle line:84% Typically races, some people feel 00:05:12.440 --> 00:05:14.720 align:middle line:84% this is a scientifically rigorous definition, 00:05:14.720 --> 00:05:15.800 align:middle line:90% others do not. 00:05:15.800 --> 00:05:22.610 align:middle line:84% Some feel that it involves very, very broad strokes 00:05:22.610 --> 00:05:25.280 align:middle line:90% in other organisms at least. 00:05:25.280 --> 00:05:30.510 align:middle line:84% It can cover fairly detailed bottlenecks in populations. 00:05:30.510 --> 00:05:33.080 align:middle line:84% But in any case, there are elements 00:05:33.080 --> 00:05:36.830 align:middle line:84% of population structure which certainly are important, 00:05:36.830 --> 00:05:39.170 align:middle line:84% whether you ascribe it to the major races 00:05:39.170 --> 00:05:44.540 align:middle line:84% or to minor, smaller populations. 00:05:44.540 --> 00:05:46.490 align:middle line:84% And examples here, we've already talked 00:05:46.490 --> 00:05:49.895 align:middle line:84% about hemoglobin variants evolved to resist malaria. 00:05:49.895 --> 00:05:51.950 align:middle line:84% It's going to be one of the themes today. 00:05:51.950 --> 00:05:56.390 align:middle line:90% 00:05:56.390 --> 00:05:58.738 align:middle line:84% And as with the differences in skin pigmentation, 00:05:58.738 --> 00:06:01.280 align:middle line:84% the pressure of the environment to develop a group-wide trait 00:06:01.280 --> 00:06:08.210 align:middle line:84% was powerful and can involve a very small number of genes. 00:06:08.210 --> 00:06:14.330 align:middle line:84% You get founder effects where a particular population 00:06:14.330 --> 00:06:16.970 align:middle line:84% is highly enriched for a particular disease 00:06:16.970 --> 00:06:22.610 align:middle line:84% such as Huntington's in the case of Lake Maracaibo in Venezuela 00:06:22.610 --> 00:06:29.000 align:middle line:84% or Tay-Sachs in some Jewish populations. 00:06:29.000 --> 00:06:31.990 align:middle line:84% So when you have these well isolated populations, 00:06:31.990 --> 00:06:34.690 align:middle line:84% I think, you can see in the population genetic literature 00:06:34.690 --> 00:06:38.260 align:middle line:84% how they can be used in various ways. 00:06:38.260 --> 00:06:42.070 align:middle line:84% But, overall, and it's sort of the broadest level 00:06:42.070 --> 00:06:47.560 align:middle line:84% we all share a large set of commonly acquired 00:06:47.560 --> 00:06:48.970 align:middle line:90% polymorphisms. 00:06:48.970 --> 00:06:53.260 align:middle line:84% And even with ants, the smallest subpopulation, 00:06:53.260 --> 00:06:55.720 align:middle line:84% it still behooves us to look at the details 00:06:55.720 --> 00:06:58.630 align:middle line:84% of the individual variations in DNA sequence 00:06:58.630 --> 00:07:02.290 align:middle line:90% in the haplotypes or genotypes. 00:07:02.290 --> 00:07:04.630 align:middle line:84% I have two dangerous slides in a row. 00:07:04.630 --> 00:07:08.140 align:middle line:84% I could probably come up with quite a few more, so could you. 00:07:08.140 --> 00:07:09.610 align:middle line:90% But one of them is-- 00:07:09.610 --> 00:07:13.780 align:middle line:84% this is really a very strong advocate for her modeling. 00:07:13.780 --> 00:07:16.950 align:middle line:84% And it's totally anecdotal slide itself 00:07:16.950 --> 00:07:18.970 align:middle line:84% is that is non-scientific, historical. 00:07:18.970 --> 00:07:25.430 align:middle line:84% But this is one critics' view of the huge influence 00:07:25.430 --> 00:07:29.360 align:middle line:84% that Lysenko had on genetics and biology in the Soviet 00:07:29.360 --> 00:07:34.130 align:middle line:84% Union from the early days of the revolution. 00:07:34.130 --> 00:07:42.380 align:middle line:84% And his real pet theory was the inheritance 00:07:42.380 --> 00:07:43.760 align:middle line:90% of acquired characteristics. 00:07:43.760 --> 00:07:45.135 align:middle line:84% And there's nothing intrinsically 00:07:45.135 --> 00:07:47.090 align:middle line:84% wrong with in broad strokes the inheritance 00:07:47.090 --> 00:07:50.300 align:middle line:90% of acquired characteristics. 00:07:50.300 --> 00:07:53.840 align:middle line:84% It's not certainly not common biological phenomenon. 00:07:53.840 --> 00:08:00.860 align:middle line:84% And at the time, it was not helping their biology progress 00:08:00.860 --> 00:08:03.980 align:middle line:84% at the same rate as the rest of the world which was mainly 00:08:03.980 --> 00:08:08.960 align:middle line:84% pursuing the Mendelian inheritance models. 00:08:08.960 --> 00:08:12.530 align:middle line:84% And this critic in quotes felt that his habit 00:08:12.530 --> 00:08:15.050 align:middle line:90% was to report only successes. 00:08:15.050 --> 00:08:17.150 align:middle line:84% This is a really feel good habit. 00:08:17.150 --> 00:08:21.410 align:middle line:84% And his results were based on extremely small sample sizes, 00:08:21.410 --> 00:08:25.310 align:middle line:84% inaccurate records, and the almost total absence of control 00:08:25.310 --> 00:08:27.560 align:middle line:90% groups. 00:08:27.560 --> 00:08:30.110 align:middle line:84% He made an early mistake in the calculation which 00:08:30.110 --> 00:08:33.690 align:middle line:84% caused comments among other specialists in his field 00:08:33.690 --> 00:08:36.710 align:middle line:84% and made him extremely negative towards the use of mathematics 00:08:36.710 --> 00:08:38.510 align:middle line:90% and science. 00:08:38.510 --> 00:08:41.000 align:middle line:84% Making mistakes should not cause you 00:08:41.000 --> 00:08:45.320 align:middle line:84% to drop the use of mathematics and science. 00:08:45.320 --> 00:08:48.453 align:middle line:84% Hopefully, those of you, probably 00:08:48.453 --> 00:08:50.870 align:middle line:84% everybody in this class has made a mistake in mathematics. 00:08:50.870 --> 00:08:53.990 align:middle line:84% And, hopefully, none of you will drop mathematics 00:08:53.990 --> 00:08:56.870 align:middle line:90% in your future biology. 00:08:56.870 --> 00:09:03.680 align:middle line:84% And the second danger is the danger of ethics-free science. 00:09:03.680 --> 00:09:07.880 align:middle line:84% Now you get to the truly remarkable story 00:09:07.880 --> 00:09:14.840 align:middle line:84% that in 1979, there was a release of anthrax 836 spores 00:09:14.840 --> 00:09:21.140 align:middle line:84% and part of the former Soviet Union. 00:09:21.140 --> 00:09:26.900 align:middle line:84% And a few years later, actually 1999, this book 00:09:26.900 --> 00:09:31.580 align:middle line:84% was published describing what was behind that. 00:09:31.580 --> 00:09:37.580 align:middle line:84% And what was behind that was decades earlier in 1953. 00:09:37.580 --> 00:09:41.870 align:middle line:84% There was a leak in one, I guess, 00:09:41.870 --> 00:09:47.830 align:middle line:90% of their anthrax developments. 00:09:47.830 --> 00:09:52.180 align:middle line:84% And then 1956, they found that one of the rodents 00:09:52.180 --> 00:09:55.930 align:middle line:84% that they captured in their routine surveys of the sewers 00:09:55.930 --> 00:09:58.720 align:middle line:84% searching down a possible anthrax, 00:09:58.720 --> 00:10:01.060 align:middle line:84% that actually a strain had become 00:10:01.060 --> 00:10:02.630 align:middle line:84% much more virulent than the original 00:10:02.630 --> 00:10:04.420 align:middle line:90% that they were working with. 00:10:04.420 --> 00:10:09.160 align:middle line:84% And usually the response of public health official 00:10:09.160 --> 00:10:12.190 align:middle line:84% or even a reasonable person would be to kill this thing. 00:10:12.190 --> 00:10:17.170 align:middle line:84% But instead they decided that this was great. 00:10:17.170 --> 00:10:18.160 align:middle line:90% Let's cultivate it. 00:10:18.160 --> 00:10:25.330 align:middle line:84% And the idea was to install it into these rockets that were 00:10:25.330 --> 00:10:27.910 align:middle line:90% targeted on Western cities. 00:10:27.910 --> 00:10:32.140 align:middle line:84% And then that led eventually to them depositing spores 00:10:32.140 --> 00:10:35.770 align:middle line:84% on their own people accidentally of this greatly 00:10:35.770 --> 00:10:37.480 align:middle line:90% enhanced strain. 00:10:37.480 --> 00:10:42.790 align:middle line:84% So the question to our community as this genome engineering 00:10:42.790 --> 00:10:45.940 align:middle line:84% tools get easier and easier where you basically 00:10:45.940 --> 00:10:49.480 align:middle line:84% can sequence genomes inexpensively and even 00:10:49.480 --> 00:10:52.210 align:middle line:84% synthesize genomes inexpensively. 00:10:52.210 --> 00:10:55.720 align:middle line:84% And much of this is going to be in the public domain, what 00:10:55.720 --> 00:10:58.360 align:middle line:84% is to stop this from being a very easily 00:10:58.360 --> 00:11:07.750 align:middle line:84% disguised and potentially very inexpensive form of terrorism? 00:11:07.750 --> 00:11:10.510 align:middle line:84% And part of that is that we do what 00:11:10.510 --> 00:11:14.680 align:middle line:84% we can do to improve either detection tools 00:11:14.680 --> 00:11:19.960 align:middle line:84% or genome engineering tools to make them more of a defense 00:11:19.960 --> 00:11:22.330 align:middle line:90% type than offense. 00:11:22.330 --> 00:11:28.570 align:middle line:84% But this was done in the early days of recombinant DNA 00:11:28.570 --> 00:11:30.700 align:middle line:84% where the vectors were designed such 00:11:30.700 --> 00:11:34.600 align:middle line:84% that if the vector ever were to escape from the lab, 00:11:34.600 --> 00:11:35.920 align:middle line:90% it would die immediately. 00:11:35.920 --> 00:11:39.190 align:middle line:84% It would be lacking the nutrients it needed to grow. 00:11:39.190 --> 00:11:41.890 align:middle line:84% It would be very sensitive to detergents that occur typically 00:11:41.890 --> 00:11:44.360 align:middle line:90% in sewers and so forth. 00:11:44.360 --> 00:11:47.170 align:middle line:84% Now the vectors we use today, those were not very robust. 00:11:47.170 --> 00:11:48.820 align:middle line:84% They didn't grow very well in the lab 00:11:48.820 --> 00:11:51.730 align:middle line:90% as much less in the sewers. 00:11:51.730 --> 00:11:56.710 align:middle line:84% But it turns out that random release is fairly low risk 00:11:56.710 --> 00:11:57.310 align:middle line:90% problem. 00:11:57.310 --> 00:12:00.130 align:middle line:84% That was what we were worried about in the 1970s 00:12:00.130 --> 00:12:01.270 align:middle line:90% with recombinant DNA. 00:12:01.270 --> 00:12:06.370 align:middle line:84% But purposeful release of genetically modified organisms 00:12:06.370 --> 00:12:08.350 align:middle line:90% is more of the issue today. 00:12:08.350 --> 00:12:11.200 align:middle line:84% And, of course, genetically modified organisms 00:12:11.200 --> 00:12:14.890 align:middle line:84% on this slide have been created and engineered 00:12:14.890 --> 00:12:20.290 align:middle line:84% over the millennium, maybe 10 millennium or so, 00:12:20.290 --> 00:12:23.980 align:middle line:90% without a license. 00:12:23.980 --> 00:12:25.880 align:middle line:84% And they've been very successful. 00:12:25.880 --> 00:12:27.505 align:middle line:84% You picture this little weed-like thing 00:12:27.505 --> 00:12:32.650 align:middle line:84% at the top left, and you end up with this great 4th of July 00:12:32.650 --> 00:12:34.150 align:middle line:90% corn on the cob. 00:12:34.150 --> 00:12:36.220 align:middle line:90% And it's a hybrid corn. 00:12:36.220 --> 00:12:43.660 align:middle line:84% And similarly, these dogs range over three logarithms 00:12:43.660 --> 00:12:49.660 align:middle line:84% in adult mass would barely be recognized as the same species 00:12:49.660 --> 00:12:53.050 align:middle line:84% if we didn't know them and love them very well. 00:12:53.050 --> 00:12:56.140 align:middle line:84% But these are examples of genetic engineering 00:12:56.140 --> 00:12:59.050 align:middle line:90% that was done pre-genomics. 00:12:59.050 --> 00:13:03.550 align:middle line:84% But now when we use recombinant DNA in particular, 00:13:03.550 --> 00:13:09.010 align:middle line:84% but genetic any kind of interspecific genetic 00:13:09.010 --> 00:13:15.350 align:middle line:84% modification, this definitely raises environmental issues, 00:13:15.350 --> 00:13:16.840 align:middle line:90% especially in the developing-- 00:13:16.840 --> 00:13:23.860 align:middle line:84% I'm sorry, in the say European nations where they are wealthy, 00:13:23.860 --> 00:13:25.660 align:middle line:84% and they don't need much improvement 00:13:25.660 --> 00:13:28.186 align:middle line:90% in their agricultural needs. 00:13:28.186 --> 00:13:32.080 align:middle line:90% 00:13:32.080 --> 00:13:34.540 align:middle line:84% Some of the developing world has very definite needs 00:13:34.540 --> 00:13:37.180 align:middle line:84% for genetics, or feel they do, for genetically modified 00:13:37.180 --> 00:13:38.030 align:middle line:90% organisms. 00:13:38.030 --> 00:13:41.980 align:middle line:84% Some of these include producing vaccines in plants. 00:13:41.980 --> 00:13:44.380 align:middle line:84% Vaccines are one of the most cost effective ways 00:13:44.380 --> 00:13:49.930 align:middle line:84% of generating public health results 00:13:49.930 --> 00:13:54.970 align:middle line:84% but possibly even more effective would be to have your bananas 00:13:54.970 --> 00:13:56.735 align:middle line:84% and other crops contain vaccines. 00:13:56.735 --> 00:13:58.360 align:middle line:84% And these have actually been developed. 00:13:58.360 --> 00:14:01.810 align:middle line:84% But it's been hard getting them actually 00:14:01.810 --> 00:14:06.550 align:middle line:84% supplied due to concerns about release of genetically modified 00:14:06.550 --> 00:14:07.390 align:middle line:90% organisms. 00:14:07.390 --> 00:14:11.050 align:middle line:84% Possible allergic response and so forth. 00:14:11.050 --> 00:14:15.330 align:middle line:84% Salt and drought tolerance is extremely important. 00:14:15.330 --> 00:14:17.810 align:middle line:90% They often come together. 00:14:17.810 --> 00:14:21.820 align:middle line:84% And there are a huge number of drought and salt tolerant 00:14:21.820 --> 00:14:24.550 align:middle line:84% plants, so-called resurrection plants. 00:14:24.550 --> 00:14:28.390 align:middle line:84% About 100 different, completely different species 00:14:28.390 --> 00:14:30.670 align:middle line:84% which could provide new genes that 00:14:30.670 --> 00:14:33.400 align:middle line:84% can be introduced into non-drought tolerant plants 00:14:33.400 --> 00:14:36.550 align:middle line:84% and are being introduced by scientists in developing 00:14:36.550 --> 00:14:40.660 align:middle line:90% worlds, such as Africa. 00:14:40.660 --> 00:14:43.750 align:middle line:84% Terminators were originally, it's 00:14:43.750 --> 00:14:46.720 align:middle line:84% like this popular, unpopular, popular again. 00:14:46.720 --> 00:14:49.270 align:middle line:84% They were popular with the companies 00:14:49.270 --> 00:14:54.340 align:middle line:84% that developed them for reasons that we may not know. 00:14:54.340 --> 00:15:02.170 align:middle line:84% But there was the concern or the backlash 00:15:02.170 --> 00:15:05.560 align:middle line:84% was the companies are doing this to preventing 00:15:05.560 --> 00:15:07.090 align:middle line:90% the farmers from reseeding. 00:15:07.090 --> 00:15:12.310 align:middle line:84% By the terminator meant that the next generation seeds 00:15:12.310 --> 00:15:13.180 align:middle line:90% would be useless. 00:15:13.180 --> 00:15:17.980 align:middle line:84% And it had been the habit of a farmer to reseed. 00:15:17.980 --> 00:15:20.590 align:middle line:84% And so the terminators didn't sell for a while. 00:15:20.590 --> 00:15:23.560 align:middle line:84% But then because of the worry about dispersal 00:15:23.560 --> 00:15:25.550 align:middle line:84% of genetically modified organisms, 00:15:25.550 --> 00:15:29.970 align:middle line:84% now terminators are becoming more interesting again 00:15:29.970 --> 00:15:31.570 align:middle line:90% to a broad set of people. 00:15:31.570 --> 00:15:35.020 align:middle line:84% You talk about organic farming, there is controversy 00:15:35.020 --> 00:15:37.810 align:middle line:84% as to whether the tightest definition 00:15:37.810 --> 00:15:40.840 align:middle line:84% of this, which involves no inorganic fertilizers 00:15:40.840 --> 00:15:48.440 align:middle line:84% like nitrates and phosphates and so forth. 00:15:48.440 --> 00:15:50.952 align:middle line:84% But that means a very high animal load. 00:15:50.952 --> 00:15:52.660 align:middle line:84% High animal load means you need to use up 00:15:52.660 --> 00:15:54.460 align:middle line:84% a lot of your vegetable crops in order 00:15:54.460 --> 00:15:59.140 align:middle line:84% to produce the fertilizer for the other vegetables. 00:15:59.140 --> 00:16:01.540 align:middle line:84% And as you pointed out that natural is not 00:16:01.540 --> 00:16:04.360 align:middle line:90% necessarily harmless. 00:16:04.360 --> 00:16:07.360 align:middle line:84% A wide variety of naturally occurring 00:16:07.360 --> 00:16:10.930 align:middle line:84% compounds, natural pesticides, are also carcinogens. 00:16:10.930 --> 00:16:13.885 align:middle line:84% And here's the laundry list at the bottom of slide 43. 00:16:13.885 --> 00:16:19.870 align:middle line:90% 00:16:19.870 --> 00:16:21.010 align:middle line:90% Cloning of stem cells. 00:16:21.010 --> 00:16:23.650 align:middle line:90% 00:16:23.650 --> 00:16:30.190 align:middle line:84% We have problems with cloning definitely. 00:16:30.190 --> 00:16:32.950 align:middle line:84% In almost every species, even the successful ones, 00:16:32.950 --> 00:16:35.050 align:middle line:84% there are a variety of species which have 00:16:35.050 --> 00:16:36.580 align:middle line:90% been tried and not succeeded. 00:16:36.580 --> 00:16:38.380 align:middle line:84% There's some that have been tried. 00:16:38.380 --> 00:16:40.210 align:middle line:84% And if you look at the studies in detail 00:16:40.210 --> 00:16:42.910 align:middle line:84% they're examples of developmental defects 00:16:42.910 --> 00:16:47.920 align:middle line:84% higher than expected in that species ranging 00:16:47.920 --> 00:16:50.835 align:middle line:90% from a few percent on up. 00:16:50.835 --> 00:16:52.210 align:middle line:84% And, obviously, there's some kind 00:16:52.210 --> 00:16:54.610 align:middle line:84% of epigenetic reprogramming that's 00:16:54.610 --> 00:16:57.070 align:middle line:84% occurring here where you're not getting 00:16:57.070 --> 00:17:00.310 align:middle line:84% all the right contributions from the maternal and paternal 00:17:00.310 --> 00:17:01.390 align:middle line:90% genomes. 00:17:01.390 --> 00:17:05.980 align:middle line:84% And this can be possibly studied with expression profiles. 00:17:05.980 --> 00:17:10.900 align:middle line:84% We can start employing all of our automation 00:17:10.900 --> 00:17:18.609 align:middle line:84% to analyze how we can increase the fraction of stem cells 00:17:18.609 --> 00:17:28.700 align:middle line:84% that we could take adult cells and send them 00:17:28.700 --> 00:17:36.680 align:middle line:84% into different lineages, or we can 00:17:36.680 --> 00:17:40.430 align:middle line:84% formulate ways to either transform one adult stem 00:17:40.430 --> 00:17:42.140 align:middle line:84% cell into another or an adult stem cell 00:17:42.140 --> 00:17:46.190 align:middle line:84% into a slightly more primitive stem cell 00:17:46.190 --> 00:17:50.810 align:middle line:84% and still retain the advantages of so-called therapeutic 00:17:50.810 --> 00:17:58.370 align:middle line:84% cloning, which would be to maintain 00:17:58.370 --> 00:18:00.635 align:middle line:84% good histocompatibility, say, with the patients. 00:18:00.635 --> 00:18:03.240 align:middle line:90% 00:18:03.240 --> 00:18:05.750 align:middle line:90% So finally, education. 00:18:05.750 --> 00:18:07.820 align:middle line:84% Why should we bring up education in a course? 00:18:07.820 --> 00:18:11.540 align:middle line:90% 00:18:11.540 --> 00:18:13.700 align:middle line:84% We've talked about models of decision 00:18:13.700 --> 00:18:15.260 align:middle line:90% making in public health. 00:18:15.260 --> 00:18:19.220 align:middle line:90% 00:18:19.220 --> 00:18:24.830 align:middle line:84% But there's also a similar set for education. 00:18:24.830 --> 00:18:27.890 align:middle line:84% We want to be able to deal with uncertainty, complexity, 00:18:27.890 --> 00:18:28.670 align:middle line:90% quantification. 00:18:28.670 --> 00:18:32.510 align:middle line:84% I'm sure that I have introduced, or we, have introduced plenty 00:18:32.510 --> 00:18:35.677 align:middle line:84% of uncertainty and complexity in quantitation in your lives 00:18:35.677 --> 00:18:36.385 align:middle line:90% with this course. 00:18:36.385 --> 00:18:38.540 align:middle line:84% I apologize for the parts that are painful. 00:18:38.540 --> 00:18:45.200 align:middle line:84% I hope that no pain, no gain has some applicability here. 00:18:45.200 --> 00:18:47.750 align:middle line:84% We want to-- a theme in this course has been 00:18:47.750 --> 00:18:50.210 align:middle line:90% to cherish your exceptions. 00:18:50.210 --> 00:18:54.130 align:middle line:84% Collect them, and these can be discoveries. 00:18:54.130 --> 00:18:55.880 align:middle line:84% They are at least going to keep you honest 00:18:55.880 --> 00:18:59.465 align:middle line:84% and keep you from making big mistakes. 00:18:59.465 --> 00:19:03.710 align:middle line:90% 00:19:03.710 --> 00:19:07.640 align:middle line:84% We want to be able to translate from one data type 00:19:07.640 --> 00:19:10.430 align:middle line:84% to another, from one conceptual foundation to another, 00:19:10.430 --> 00:19:14.570 align:middle line:84% to integrate different either adjacent conceptual spheres 00:19:14.570 --> 00:19:15.680 align:middle line:90% or very distant ones. 00:19:15.680 --> 00:19:18.300 align:middle line:90% 00:19:18.300 --> 00:19:23.730 align:middle line:84% The way we do this, slide 47, we need 00:19:23.730 --> 00:19:26.460 align:middle line:84% to have measures of our progress, measures 00:19:26.460 --> 00:19:30.150 align:middle line:84% of the quality of the underlying data and the models. 00:19:30.150 --> 00:19:34.290 align:middle line:84% And we've already done this to some extent, 00:19:34.290 --> 00:19:37.620 align:middle line:84% basically, for three dimensional structures and sequence 00:19:37.620 --> 00:19:43.350 align:middle line:84% data, the primary and tertiary information. 00:19:43.350 --> 00:19:46.668 align:middle line:84% For X-ray diffraction-- this dates back into the '60s-- 00:19:46.668 --> 00:19:48.210 align:middle line:84% we have measures of data quality that 00:19:48.210 --> 00:19:51.670 align:middle line:84% include resolution, model quality, which is the R 00:19:51.670 --> 00:19:53.310 align:middle line:90% factor we talked about before. 00:19:53.310 --> 00:19:55.770 align:middle line:84% We have ways of doing similarity searches. 00:19:55.770 --> 00:19:59.310 align:middle line:84% For sequencing, a more recent enterprise 00:19:59.310 --> 00:20:02.250 align:middle line:84% in the '80s, late '80s, early '90s, 00:20:02.250 --> 00:20:04.590 align:middle line:84% we got the Genome Project launched 00:20:04.590 --> 00:20:08.070 align:middle line:84% with thoughts of measuring data quality in terms 00:20:08.070 --> 00:20:09.840 align:middle line:90% of discrepancy per base pair. 00:20:09.840 --> 00:20:15.120 align:middle line:84% That should be less than 1 part in 10 to the fourth. 00:20:15.120 --> 00:20:18.840 align:middle line:84% The models, typically, are models of protein conservation. 00:20:18.840 --> 00:20:22.080 align:middle line:84% And a similarity search is one of the greatest killer 00:20:22.080 --> 00:20:26.580 align:middle line:84% applications of all times, which is [? last. ?] 00:20:26.580 --> 00:20:31.890 align:middle line:84% And then for function we're less far along. 00:20:31.890 --> 00:20:35.410 align:middle line:84% We don't really have accession numbers, as I said. 00:20:35.410 --> 00:20:43.320 align:middle line:84% We don't really have great ways of doing similarity searches 00:20:43.320 --> 00:20:49.020 align:middle line:84% through say image databases or similarity searches other than 00:20:49.020 --> 00:20:51.168 align:middle line:90% say correlation coefficients. 00:20:51.168 --> 00:20:52.710 align:middle line:84% But I think this is rapidly changing. 00:20:52.710 --> 00:20:55.440 align:middle line:90% 00:20:55.440 --> 00:20:58.980 align:middle line:84% When we start applying these models, 00:20:58.980 --> 00:21:04.140 align:middle line:84% this is not only in the education sense, 00:21:04.140 --> 00:21:06.300 align:middle line:84% but in the probing these networks 00:21:06.300 --> 00:21:08.100 align:middle line:84% that we've been talking about, even further 00:21:08.100 --> 00:21:12.870 align:middle line:84% beyond consideration of neural networks 00:21:12.870 --> 00:21:16.470 align:middle line:84% and our interaction with other organisms, 00:21:16.470 --> 00:21:19.560 align:middle line:84% kind of combining those two, the neural networks 00:21:19.560 --> 00:21:22.200 align:middle line:84% and our interaction with other organisms, ecology, 00:21:22.200 --> 00:21:24.120 align:middle line:90% is this notion of biophilia. 00:21:24.120 --> 00:21:28.140 align:middle line:84% Which is that we, as human beings and other fairly 00:21:28.140 --> 00:21:32.910 align:middle line:84% intelligent animals, are connected subconsciously 00:21:32.910 --> 00:21:35.080 align:middle line:90% to other living beings. 00:21:35.080 --> 00:21:37.740 align:middle line:84% It is clear that no matter how urban or what culture 00:21:37.740 --> 00:21:39.180 align:middle line:84% you're talking about, snake dreams 00:21:39.180 --> 00:21:40.860 align:middle line:90% figure in very prominently. 00:21:40.860 --> 00:21:44.340 align:middle line:84% And this has to do with the need of primates 00:21:44.340 --> 00:21:46.830 align:middle line:84% to avoid and track snakes from their vicinity 00:21:46.830 --> 00:21:49.800 align:middle line:90% and the vicinity of the tribe. 00:21:49.800 --> 00:21:52.110 align:middle line:90% Little animals are cute. 00:21:52.110 --> 00:21:54.793 align:middle line:90% We just know that. 00:21:54.793 --> 00:21:56.460 align:middle line:84% And they are much cuter than the adults, 00:21:56.460 --> 00:21:58.835 align:middle line:84% no matter what the animal is, with the possible exception 00:21:58.835 --> 00:21:59.400 align:middle line:90% of snakes. 00:21:59.400 --> 00:22:01.690 align:middle line:90% [LAUGHTER] 00:22:01.690 --> 00:22:07.950 align:middle line:84% And there are anecdotal, at least, 00:22:07.950 --> 00:22:12.330 align:middle line:84% possibly well-characterized effects of the green fractals 00:22:12.330 --> 00:22:15.930 align:middle line:84% that we like to see in trees and plants. 00:22:15.930 --> 00:22:18.450 align:middle line:84% And taking this one step further from just this kind 00:22:18.450 --> 00:22:22.380 align:middle line:84% of very stimulating thought that we actually have co-evolved, 00:22:22.380 --> 00:22:24.450 align:middle line:84% our nervous system has co-evolved for so 00:22:24.450 --> 00:22:25.680 align:middle line:90% long with these other things. 00:22:25.680 --> 00:22:28.920 align:middle line:84% It would be natural for us to be very attuned to them 00:22:28.920 --> 00:22:32.130 align:middle line:84% because our survival would have depended upon our ability 00:22:32.130 --> 00:22:38.490 align:middle line:84% to avoid snakes and to deal with green versus brown shrubs. 00:22:38.490 --> 00:22:43.320 align:middle line:84% And if you take that one step further, 00:22:43.320 --> 00:22:48.660 align:middle line:84% much of what we do in the humanities say 00:22:48.660 --> 00:22:52.770 align:middle line:84% is affected our aesthetics and our approaches to it, 00:22:52.770 --> 00:22:56.620 align:middle line:84% our beliefs are affected by this heritage. 00:22:56.620 --> 00:22:58.920 align:middle line:84% And this is what E.O Wilson has championed. 00:22:58.920 --> 00:23:03.580 align:middle line:84% And I would say it's quite controversial as it should be. 00:23:03.580 --> 00:23:06.090 align:middle line:84% But in general, long separated fields come together-- 00:23:06.090 --> 00:23:08.190 align:middle line:84% it's this consilience definition-- 00:23:08.190 --> 00:23:09.480 align:middle line:90% and they create new insights. 00:23:09.480 --> 00:23:13.650 align:middle line:84% Like chemistry and genetics brings us molecular biology. 00:23:13.650 --> 00:23:15.960 align:middle line:84% And the question is, is all of human endeavor 00:23:15.960 --> 00:23:18.590 align:middle line:84% ready for such a thing, from religious feelings 00:23:18.590 --> 00:23:20.890 align:middle line:90% to financial markets and so on? 00:23:20.890 --> 00:23:23.700 align:middle line:84% And whether or not, how might genomics 00:23:23.700 --> 00:23:25.710 align:middle line:84% and computational biology contribute? 00:23:25.710 --> 00:23:30.690 align:middle line:84% It's surprising sometimes when these things do contribute. 00:23:30.690 --> 00:23:32.790 align:middle line:84% And here's some speculation on that. 00:23:32.790 --> 00:23:36.810 align:middle line:84% We have improving imaging methods. 00:23:36.810 --> 00:23:39.990 align:middle line:84% We talked about imaging in the context of in situs. 00:23:39.990 --> 00:23:42.840 align:middle line:84% Some very functional versions of this 00:23:42.840 --> 00:23:46.750 align:middle line:84% are positron emission tomography and magnetic resonance imaging, 00:23:46.750 --> 00:23:49.950 align:middle line:84% which allow you to monitor such things as blood 00:23:49.950 --> 00:24:00.060 align:middle line:84% flow or metabolic uptake in different parts of an actively 00:24:00.060 --> 00:24:01.990 align:middle line:90% metabolizing brain. 00:24:01.990 --> 00:24:08.142 align:middle line:84% And here you can inject some O-15 labeled compound. 00:24:08.142 --> 00:24:09.600 align:middle line:84% And you can get an image resolution 00:24:09.600 --> 00:24:11.310 align:middle line:84% on the order of nine millimeters. 00:24:11.310 --> 00:24:16.350 align:middle line:84% OK so the voxels here, volume elements, 00:24:16.350 --> 00:24:20.250 align:middle line:90% are limited in that range. 00:24:20.250 --> 00:24:23.940 align:middle line:84% And sort of in the 20 seconds is sort of the time frame 00:24:23.940 --> 00:24:25.740 align:middle line:90% that you're working in. 00:24:25.740 --> 00:24:28.200 align:middle line:84% And this has been applied to a whole variety 00:24:28.200 --> 00:24:32.250 align:middle line:90% of interesting behavioral tasks. 00:24:32.250 --> 00:24:36.120 align:middle line:84% Almost anything you can think of counting memory, 00:24:36.120 --> 00:24:37.740 align:middle line:90% so forth in humans. 00:24:37.740 --> 00:24:41.430 align:middle line:84% And you can map the parts of the brain that are differentially 00:24:41.430 --> 00:24:45.390 align:middle line:84% responsive to a control and an experimental time frame 00:24:45.390 --> 00:24:48.180 align:middle line:84% for the same patient in the same apparatus. 00:24:48.180 --> 00:24:49.770 align:middle line:84% And here, this is just to show you 00:24:49.770 --> 00:24:51.937 align:middle line:84% how far I can go and connect to what we were talking 00:24:51.937 --> 00:24:54.480 align:middle line:84% about in the previous slide, here 00:24:54.480 --> 00:25:02.130 align:middle line:84% religious subjects, patients, have been the differential 00:25:02.130 --> 00:25:05.010 align:middle line:84% parts of the brain monitored here 00:25:05.010 --> 00:25:07.860 align:middle line:84% are in a religious recitation process 00:25:07.860 --> 00:25:11.100 align:middle line:90% and in arresting control. 00:25:11.100 --> 00:25:14.140 align:middle line:84% And these are all the P less than P 00:25:14.140 --> 00:25:22.380 align:middle line:84% to the 0.001 significance by the very complicated statistics 00:25:22.380 --> 00:25:30.270 align:middle line:84% that are used in the analysis of these functional maps. 00:25:30.270 --> 00:25:34.260 align:middle line:84% Now not to leave us on that note but to connect it 00:25:34.260 --> 00:25:38.070 align:middle line:84% more to genomics and computational biology 00:25:38.070 --> 00:25:41.830 align:middle line:84% is more in the heart of this course. 00:25:41.830 --> 00:25:46.650 align:middle line:84% Here's an example how magnetic resonance imaging, which 00:25:46.650 --> 00:25:49.110 align:middle line:84% can be applied to gene expression, how 00:25:49.110 --> 00:25:51.210 align:middle line:84% we bring these two together, kind of imaging 00:25:51.210 --> 00:25:52.510 align:middle line:90% gene expression. 00:25:52.510 --> 00:25:57.260 align:middle line:84% And one of the powers of this in contrast the positron emission 00:25:57.260 --> 00:26:00.380 align:middle line:84% tomography had about a 9 millimeter resolution. 00:26:00.380 --> 00:26:02.420 align:middle line:84% This has a 10 micron resolution, sort 00:26:02.420 --> 00:26:04.820 align:middle line:84% of in the optical resolution range. 00:26:04.820 --> 00:26:07.970 align:middle line:84% But unlike optical methods, this will work 00:26:07.970 --> 00:26:11.420 align:middle line:90% for impact opaque organisms. 00:26:11.420 --> 00:26:15.380 align:middle line:84% And, finally, so MRI will do that in general. 00:26:15.380 --> 00:26:17.120 align:middle line:84% But to connect it to gene expression, 00:26:17.120 --> 00:26:19.970 align:middle line:84% you need to tag the gene expression such way, 00:26:19.970 --> 00:26:22.280 align:middle line:84% and we have green fluorescent protein, 00:26:22.280 --> 00:26:25.610 align:middle line:84% we have other colors fluorescent protein. 00:26:25.610 --> 00:26:28.503 align:middle line:84% We have luciferase, data glycosides, and so forth. 00:26:28.503 --> 00:26:30.170 align:middle line:84% One of those has to be turn on something 00:26:30.170 --> 00:26:33.710 align:middle line:84% that has sufficient contrast and magnetic resonance imaging. 00:26:33.710 --> 00:26:39.980 align:middle line:84% And an example of that is a way of caging a gadolinium ion such 00:26:39.980 --> 00:26:42.920 align:middle line:84% that you can see this little galactic tyrannous 00:26:42.920 --> 00:26:46.310 align:middle line:84% ring at the top right is covering it. 00:26:46.310 --> 00:26:49.760 align:middle line:84% And the little red bond there is cleaved by beta galactosidase, 00:26:49.760 --> 00:26:51.200 align:middle line:90% lacZ fusions. 00:26:51.200 --> 00:26:53.495 align:middle line:84% And so you can now make your same reporter constructs 00:26:53.495 --> 00:26:55.370 align:middle line:84% that have been used for making, say, 00:26:55.370 --> 00:26:58.430 align:middle line:84% blue cells with a core metric indicator 00:26:58.430 --> 00:27:00.260 align:middle line:90% with optical wavelengths. 00:27:00.260 --> 00:27:02.150 align:middle line:84% Well, now with magnetic resonance, 00:27:02.150 --> 00:27:04.145 align:middle line:84% imaging released that gadolinium. 00:27:04.145 --> 00:27:06.650 align:middle line:84% So it's now accessible to the solvent, 00:27:06.650 --> 00:27:08.450 align:middle line:84% has a different resonance, and you 00:27:08.450 --> 00:27:10.190 align:middle line:90% can get sharp contrast here. 00:27:10.190 --> 00:27:13.310 align:middle line:84% In a living organism on the top, with 10 micron resolution, 00:27:13.310 --> 00:27:15.230 align:middle line:84% as opposed to a fixed organism, which 00:27:15.230 --> 00:27:20.150 align:middle line:84% is required for getting the whole-mount in situ staining 00:27:20.150 --> 00:27:21.650 align:middle line:90% with lacZ. 00:27:21.650 --> 00:27:25.610 align:middle line:84% So I think, this is a very interesting combination 00:27:25.610 --> 00:27:30.020 align:middle line:84% of being able to use something alive in opaque tissue 00:27:30.020 --> 00:27:34.280 align:middle line:90% with a genomic tag of sorts. 00:27:34.280 --> 00:27:38.160 align:middle line:90% 00:27:38.160 --> 00:27:43.630 align:middle line:84% Well, on that religious note, we will sort of 00:27:43.630 --> 00:27:49.200 align:middle line:84% wrap up the course, my part of it, the lecture part. 00:27:49.200 --> 00:27:52.170 align:middle line:84% And in so doing, I want to especially give 00:27:52.170 --> 00:27:55.860 align:middle line:84% many, many thanks not just to this year's TFs, which 00:27:55.860 --> 00:27:58.890 align:middle line:84% we will get to in just a moment, but the ones that helped 00:27:58.890 --> 00:28:00.540 align:middle line:90% start this phase of the course. 00:28:00.540 --> 00:28:02.880 align:middle line:84% Actually, the course goes back to '88. 00:28:02.880 --> 00:28:06.120 align:middle line:84% But these are some of the Teaching 00:28:06.120 --> 00:28:11.970 align:middle line:90% Fellows in 1999 and 2000, 2001. 00:28:11.970 --> 00:28:16.050 align:middle line:84% One of these Teaching Fellows, [? Suzanne ?] [? Camille, ?] 00:28:16.050 --> 00:28:19.745 align:middle line:84% has stayed with us as a head Teaching Fellow this year. 00:28:19.745 --> 00:28:21.750 align:middle line:90% She was up to the top of-- 00:28:21.750 --> 00:28:25.260 align:middle line:84% and I'm very thankful to every one here, Woody, 00:28:25.260 --> 00:28:30.300 align:middle line:84% [? June, ?] [? Len, ?] Tom, [? John, ?] [? Juang ?] 00:28:30.300 --> 00:28:33.570 align:middle line:84% [? Hong, ?] Gary, and [? Lachmans. ?] If any of you 00:28:33.570 --> 00:28:37.080 align:middle line:84% are here, could you kind of stand up, wave, just wave. 00:28:37.080 --> 00:28:38.430 align:middle line:90% Thank you very much. 00:28:38.430 --> 00:28:40.890 align:middle line:90% Really, I love it. 00:28:40.890 --> 00:28:48.840 align:middle line:84% And if this course is to continue to survive, 00:28:48.840 --> 00:28:52.390 align:middle line:90% we need TFs for next year. 00:28:52.390 --> 00:28:55.710 align:middle line:84% So if any of you feel that you have the right stuff 00:28:55.710 --> 00:29:00.330 align:middle line:84% and feel that this course should survive, please contact us. 00:29:00.330 --> 00:29:04.260 align:middle line:90% 00:29:04.260 --> 00:29:09.780 align:middle line:84% Hopefully, it'll be some finite positive number. 00:29:09.780 --> 00:29:12.420 align:middle line:84% We really love the projects, and we'd love-- 00:29:12.420 --> 00:29:15.090 align:middle line:84% and in the past, many students have 00:29:15.090 --> 00:29:18.360 align:middle line:84% been reluctant to stop working on the project 00:29:18.360 --> 00:29:21.190 align:middle line:84% after the course is over and their grade has been assigned 00:29:21.190 --> 00:29:23.370 align:middle line:90% and so forth. 00:29:23.370 --> 00:29:27.360 align:middle line:84% And that nothing could make me happier than to have do that. 00:29:27.360 --> 00:29:30.880 align:middle line:84% There's a limit to just how much I can help you do that. 00:29:30.880 --> 00:29:33.420 align:middle line:84% But if anything I can do to help, 00:29:33.420 --> 00:29:35.880 align:middle line:84% providing additional mentoring and so forth, 00:29:35.880 --> 00:29:37.680 align:middle line:90% I'd love to do that. 00:29:37.680 --> 00:29:42.940 align:middle line:84% Some of these have even resulted in publications later on. 00:29:42.940 --> 00:29:47.790 align:middle line:84% We started this course, slide four of the first lecture, 00:29:47.790 --> 00:29:50.190 align:middle line:84% actually the first real slide or the first lecture, 00:29:50.190 --> 00:29:52.575 align:middle line:84% was on the origins of zeros and ones. 00:29:52.575 --> 00:29:55.110 align:middle line:90% 00:29:55.110 --> 00:29:59.790 align:middle line:84% Kind of a play on the 101 course number, 00:29:59.790 --> 00:30:02.070 align:middle line:84% where did the binary code come from? 00:30:02.070 --> 00:30:05.190 align:middle line:84% And you could ascribe it to Leibniz 00:30:05.190 --> 00:30:13.170 align:middle line:84% or one of the modern 18th century mathematicians. 00:30:13.170 --> 00:30:18.600 align:middle line:84% But Leibniz himself found that it had already 00:30:18.600 --> 00:30:24.870 align:middle line:84% been invented about 5,000 years ago or so 00:30:24.870 --> 00:30:27.150 align:middle line:90% by China's first emperor. 00:30:27.150 --> 00:30:31.380 align:middle line:84% And since then, some people have gone so far as 00:30:31.380 --> 00:30:39.300 align:middle line:84% to take this binary coding, the etching, which has 64 hexagons 00:30:39.300 --> 00:30:41.370 align:middle line:84% and has arranged it in such a way 00:30:41.370 --> 00:30:44.670 align:middle line:84% that it has decoded it so that it actually 00:30:44.670 --> 00:30:48.880 align:middle line:84% fits in with the geniculate code which has 64 codons. 00:30:48.880 --> 00:30:51.750 align:middle line:84% So for those of you who are students of the etching, 00:30:51.750 --> 00:30:56.200 align:middle line:84% hopefully, it now has new meaning for you. 00:30:56.200 --> 00:31:01.440 align:middle line:84% And to emphasize this yin and yang symbol here, 00:31:01.440 --> 00:31:03.960 align:middle line:84% remember that the purpose of having 00:31:03.960 --> 00:31:08.040 align:middle line:84% the black dot in the white zone and the reciprocal white dot 00:31:08.040 --> 00:31:10.980 align:middle line:84% in the black zone is to remind you that things are not just 00:31:10.980 --> 00:31:11.860 align:middle line:90% black and white. 00:31:11.860 --> 00:31:14.400 align:middle line:90% They're not just zeros and ones. 00:31:14.400 --> 00:31:20.160 align:middle line:84% They have more complexity, and they are constantly in change. 00:31:20.160 --> 00:31:24.450 align:middle line:84% This is the book of changes, and this course is about change. 00:31:24.450 --> 00:31:27.540 align:middle line:84% And you should-- you do computational biology. 00:31:27.540 --> 00:31:30.467 align:middle line:90% 00:31:30.467 --> 00:31:31.800 align:middle line:90% It's not just about computation. 00:31:31.800 --> 00:31:34.410 align:middle line:84% It's not by keeping yourself busy at the computer, 00:31:34.410 --> 00:31:36.120 align:middle line:84% keeping your computers busy all the time. 00:31:36.120 --> 00:31:40.630 align:middle line:84% It's about thinking, thinking as broadly as you can. 00:31:40.630 --> 00:31:42.600 align:middle line:90% So thank you very much. 00:31:42.600 --> 00:31:45.950 align:middle line:90% [APPLAUSE] 00:31:45.950 --> 00:31:47.000 align:middle line:90%