Barry Leiba (a fellow Indy Science Blogger) has an interesting discussion on whether it matters where you go to college. If you are a good student, does the success of your future career really depend on where you go?
Barry makes some good points about this issue from the persepctive of someone working as a computer scientist for a tech company. I think much of what he says applies to academia as well - if you browse through the faculty pages of top university science departments, you'll see most people in those departments got their PhDs in top schools. I think a good student from just about any serious 4-year college could get into a good graduate science program, but where you do your graduate work has a big impact on your career prosepcts.
For another take on this issue, looking at law schools, check out Balkanization.
One thing I hate is top ten lists. Barry links to one he takes issue with. I take issue with the idea that ten is some magical number - that ten schools are somehow in a different league from the rest. I think a better number would be twenty - there are so many very good universities in the US and Canada, and a prosepctive student should take a broader look at what's out there.
Monday, February 26, 2007
A Genome-wide Association Study to Find Genes Linked to Diabetes
I meant to get this post about an important new paper up 10 days ago, but illness intervened. The paper I discuss has now been published in the latest print issue of Nature.
Genome-wide association studies are hot right now, and Nature has recently published a large study that identifies new genes possibly linked to type II diabetes.
For those of you not familiar with such studies, here is a very brief, oversimplified account - for more in depth commentary on such studies, check out Nature's News and Views accompanying the article (subscription required).
The goal of genome-wide association studies is to find genes linked with a disease, in this case, diabetes. For diseases such as cystic fibrosis, which result from a catastrophic defect in a single gene, which have clear inheritance patterns, and few environmental factors involved, it's relatively straightforward to identify the gene and even understand how the defective gene results in the disease. But most common diseases that afflict industrialized societies, especially the US, such as heart disease and diabetes, are extremely complex. They result from the interplay of multiple environmental and genetic factors. A major goal of biomedical research is to identify these factors and to understand how they contribute to the development of the disease.
So how do you find the genes involved in something like diabetes? Ideally, you would get a study population of thousands of people, and compare the genomes of those who have diabetes with the genomes of those who don't have it. Variants of genes that tend to be found among diabetics, but not healthy subjects, would then be candidate diabetes genes. Unfortunately, we cannot (yet) sequence the complete genomes of thousands of people with the limited time and money available. And in fact, I'm exaggerating when I say that sequencing entire genomes would be ideal - the vast majority of our genome does not vary among individuals, so we really only want to look at those sequences where we vary. Major efforts have gone into looking at where human DNA varies among individuals (check this out), so we have some idea of where to check our genomes for differences.
We also have new technologies that make it feasible to compare the genomes of thousands of people without completely sequencing each genome. We can use microarrays to probe hundreds of thousands of places in the genome where there are known differences among people (see here; also look at this PDF for an into to a non-array technology). In most genome-wide association studies, the differences that researchers look for are SNPs (single nucleotide polymorphisms) - single 'letters' or bases of DNA that vary among people. At each SNP it is possible to find up to four different variants (either an A, T, C, or G, although at many of these points, only one or two of these variants will actually exist in among humans). In the study published in Nature, the researchers looked for SNPs that tend to show up among diabetics.
The authors of this paper, working in Canada, France, and the UK, used blood samples from 1,363 people about evenly divided between type II diabetics and non-diabetics. They determined the identity of the DNA base for 400,000 SNPs in each subject - in more technical terms, they genotyped 400,000 SNPs in their subjects. To give you an idea of how much of the genome this covers, that's about 1 SNP for every 7,500 bases in the 3 billion base genome, which is reasonably good coverage. These SNPs however are not evenly spaced over the whole genome, so you don't literally have a SNP every 7,500 bases - it is thus important to select the right set of SNPs, a complicated issue which we won't get into here.
This first screen identified about 60 SNPs possibly associated with diabetes, but to rigorously test that association the authors looked at the SNPs in a much larger study population. Since in this second stage they were now only checking a small number of SNPs, it was feasible to genotype a much larger group of people. As opposed to 1,363 people, they genotyped 5,511, divided about evenly between diabetics and non-diabetics. Ultimately they were able to check 57 SNPs, and found eight SNPs that fell within five regions, or loci, of the genome. One of these five loci contains a gene previously found to be linked with diabetes; this gene, TCF7L2, codes for a transcription factor. The other four loci also contained plausible candidate genes.
The most amazing gene found was one for a zinc transporter protein that is expressed only in the beta cells that secrete insulin, a process which requires zinc. One of the SNPs in this locus is non-synonymous, that is, it produces in an amino acid change in the zinc transporter protein, and such a change could easily, but not necessarily, impact the protein's function. This remarkable find immediately suggests treatment possibilities, such as drugs or diet supplements that could compensate for the change in this zinc transporter, though much more research will be needed to understand just what role this protein plays in the development of diabetes.
One of the most surprising conclusions in this paper is that most of the genetic variants associated with diabetes are the variants possessed by most of the human population, at least in the ethnic groups covered. In the case of the zinc transporter, those with a 'C' at that position in their DNA are more susceptible to diabetes - and most of us do have a 'C' at that position. The authors reported eight SNPs linked with diabetes, and in six of these cases the diabetes-associated variant is the major variant in the human populations studied. This suggests that most of us are genetically predisposed to diabetes, while a few of us are resistant, and thus for most of us environmental factors will play a large role in determining whether we develop diabetes. There is also an evolutionary story here - the major variants of these eight SNPs may have been beneficial in the environment in which our earliest human ancestors lived, but under our current diets these variants have become a liability. This is not the first time such an idea has been proposed, but the results of this study strengthen the evidence for this scenario.
This paper presents some of the earliest results using a genome-wide association approach with the promising new technologies described at the sites I linked to above. Whether such studies will substantially impact our understanding and ability to treat major diseases is still an open question, but these first results appear promising. The authors of this study report that they found other promising genes, which they will report later after further analysis. The hope is that such studies will enable us to confidently identify people who are at risk, and develop new treatments for these diseases that are major killers in our society.
Genome-wide association studies are hot right now, and Nature has recently published a large study that identifies new genes possibly linked to type II diabetes.
For those of you not familiar with such studies, here is a very brief, oversimplified account - for more in depth commentary on such studies, check out Nature's News and Views accompanying the article (subscription required).
The goal of genome-wide association studies is to find genes linked with a disease, in this case, diabetes. For diseases such as cystic fibrosis, which result from a catastrophic defect in a single gene, which have clear inheritance patterns, and few environmental factors involved, it's relatively straightforward to identify the gene and even understand how the defective gene results in the disease. But most common diseases that afflict industrialized societies, especially the US, such as heart disease and diabetes, are extremely complex. They result from the interplay of multiple environmental and genetic factors. A major goal of biomedical research is to identify these factors and to understand how they contribute to the development of the disease.
So how do you find the genes involved in something like diabetes? Ideally, you would get a study population of thousands of people, and compare the genomes of those who have diabetes with the genomes of those who don't have it. Variants of genes that tend to be found among diabetics, but not healthy subjects, would then be candidate diabetes genes. Unfortunately, we cannot (yet) sequence the complete genomes of thousands of people with the limited time and money available. And in fact, I'm exaggerating when I say that sequencing entire genomes would be ideal - the vast majority of our genome does not vary among individuals, so we really only want to look at those sequences where we vary. Major efforts have gone into looking at where human DNA varies among individuals (check this out), so we have some idea of where to check our genomes for differences.
We also have new technologies that make it feasible to compare the genomes of thousands of people without completely sequencing each genome. We can use microarrays to probe hundreds of thousands of places in the genome where there are known differences among people (see here; also look at this PDF for an into to a non-array technology). In most genome-wide association studies, the differences that researchers look for are SNPs (single nucleotide polymorphisms) - single 'letters' or bases of DNA that vary among people. At each SNP it is possible to find up to four different variants (either an A, T, C, or G, although at many of these points, only one or two of these variants will actually exist in among humans). In the study published in Nature, the researchers looked for SNPs that tend to show up among diabetics.
The authors of this paper, working in Canada, France, and the UK, used blood samples from 1,363 people about evenly divided between type II diabetics and non-diabetics. They determined the identity of the DNA base for 400,000 SNPs in each subject - in more technical terms, they genotyped 400,000 SNPs in their subjects. To give you an idea of how much of the genome this covers, that's about 1 SNP for every 7,500 bases in the 3 billion base genome, which is reasonably good coverage. These SNPs however are not evenly spaced over the whole genome, so you don't literally have a SNP every 7,500 bases - it is thus important to select the right set of SNPs, a complicated issue which we won't get into here.
This first screen identified about 60 SNPs possibly associated with diabetes, but to rigorously test that association the authors looked at the SNPs in a much larger study population. Since in this second stage they were now only checking a small number of SNPs, it was feasible to genotype a much larger group of people. As opposed to 1,363 people, they genotyped 5,511, divided about evenly between diabetics and non-diabetics. Ultimately they were able to check 57 SNPs, and found eight SNPs that fell within five regions, or loci, of the genome. One of these five loci contains a gene previously found to be linked with diabetes; this gene, TCF7L2, codes for a transcription factor. The other four loci also contained plausible candidate genes.
The most amazing gene found was one for a zinc transporter protein that is expressed only in the beta cells that secrete insulin, a process which requires zinc. One of the SNPs in this locus is non-synonymous, that is, it produces in an amino acid change in the zinc transporter protein, and such a change could easily, but not necessarily, impact the protein's function. This remarkable find immediately suggests treatment possibilities, such as drugs or diet supplements that could compensate for the change in this zinc transporter, though much more research will be needed to understand just what role this protein plays in the development of diabetes.
One of the most surprising conclusions in this paper is that most of the genetic variants associated with diabetes are the variants possessed by most of the human population, at least in the ethnic groups covered. In the case of the zinc transporter, those with a 'C' at that position in their DNA are more susceptible to diabetes - and most of us do have a 'C' at that position. The authors reported eight SNPs linked with diabetes, and in six of these cases the diabetes-associated variant is the major variant in the human populations studied. This suggests that most of us are genetically predisposed to diabetes, while a few of us are resistant, and thus for most of us environmental factors will play a large role in determining whether we develop diabetes. There is also an evolutionary story here - the major variants of these eight SNPs may have been beneficial in the environment in which our earliest human ancestors lived, but under our current diets these variants have become a liability. This is not the first time such an idea has been proposed, but the results of this study strengthen the evidence for this scenario.
This paper presents some of the earliest results using a genome-wide association approach with the promising new technologies described at the sites I linked to above. Whether such studies will substantially impact our understanding and ability to treat major diseases is still an open question, but these first results appear promising. The authors of this study report that they found other promising genes, which they will report later after further analysis. The hope is that such studies will enable us to confidently identify people who are at risk, and develop new treatments for these diseases that are major killers in our society.
Monday, February 19, 2007
President's Day Miscellany
Extended, rampant illness at home has adversely affected lab work and blog posting, including a forthcoming post on a recent genome-wide association study identifying some new genes possibly linked to diabetes.
However, here are a few links to a couple of stories about about our culture's baffling, hyper-squeamish approach to sex:
Cosmic Variance's take on a children's book that for an absurd reason is controversial, and
a substitute-teacher facing jail time because of pornographic popups that she wasn't able to stop. Why are we wasting time and money on trials like this, instead of spending it on more current and safer classroom software?
However, here are a few links to a couple of stories about about our culture's baffling, hyper-squeamish approach to sex:
Cosmic Variance's take on a children's book that for an absurd reason is controversial, and
a substitute-teacher facing jail time because of pornographic popups that she wasn't able to stop. Why are we wasting time and money on trials like this, instead of spending it on more current and safer classroom software?
Monday, February 12, 2007
Should a mainstream university grant a doctorate to a Young Earth Creationist?
That is the question people are asking in this NY Times piece about a recent geosciences PhD graduate from the University of Rhode Island - a well-regarded school in this field. Marcus Ross is a Young Earth Creationist who submitted his dissertation in paleontology in December and is now teaching at Jerry Falwell's Liberty University. So is it bad thing that the U of RI granted this guy a doctorate? Should they have not let him graduate?
To treat this guy differently would have been wrong. I would be scared by the prospect of universities screening their graduates based on personal beliefs - that would be one more nasty development in the ongoing the balkanization of our culture. We're divided enough already. It would just give ammunition to anti-evolutionists, who would argue that we are using unfair, suppressive tactics because our arguments can't stand on their own.
I'm not worried about Creationists with PhDs because:
1. They're rare, and they will never amass enough numbers to seriously change the balance of the evolution vs creationism fight.
2. They won't have any impact on mainstream science - after grad school, they'll never publish anything that will change the way most professional scientists think about their field. They're not about to get tenure in a science department at Harvard.
3. They're really not more likely to get teaching jobs at public schools than Creationists without PhDs. A YEC with a PhD will probably raise more immediate red flags in the local science community than a less high-profile Creationist. I don't see how the PhD itself would sway anyone except those are are already determined to push Creationism, and for every one YEC PhD there are hundreds of PhDs supporting evolution.
People like this are already out there, but I don't see how they are much worse than Creationists with academic credentials in non-science fields. Has Jonathan Wells, with a PhD in developmental biology, been more of a threat than law professor Phillip Johnson? Articulate, educated leaders of the Creationist movement are going to keep popping up, generation after generation, whether we let them get reputable science doctorates or not. By banning them from graduate programs for their religious beliefs, we would be sacrificing our moral integrity for very little practical benefit.
If people like Marcus Ross do a good job and meet the requirements for a doctorate - that is, if they don't try rig their thesis committee to get away with substandard work, they should be cheerfully given their degrees. Who knows, some of these people may have their faith changed by their work - Ronald Numbers details several such cases, in his book The Creationists (this is highly recommended reading). Not many people can really live with that much cognitive dissonance for very long. And those who can should be allowed to take their degrees and go have a nice fulfilling career at academic holes like Liberty University.
To treat this guy differently would have been wrong. I would be scared by the prospect of universities screening their graduates based on personal beliefs - that would be one more nasty development in the ongoing the balkanization of our culture. We're divided enough already. It would just give ammunition to anti-evolutionists, who would argue that we are using unfair, suppressive tactics because our arguments can't stand on their own.
I'm not worried about Creationists with PhDs because:
1. They're rare, and they will never amass enough numbers to seriously change the balance of the evolution vs creationism fight.
2. They won't have any impact on mainstream science - after grad school, they'll never publish anything that will change the way most professional scientists think about their field. They're not about to get tenure in a science department at Harvard.
3. They're really not more likely to get teaching jobs at public schools than Creationists without PhDs. A YEC with a PhD will probably raise more immediate red flags in the local science community than a less high-profile Creationist. I don't see how the PhD itself would sway anyone except those are are already determined to push Creationism, and for every one YEC PhD there are hundreds of PhDs supporting evolution.
People like this are already out there, but I don't see how they are much worse than Creationists with academic credentials in non-science fields. Has Jonathan Wells, with a PhD in developmental biology, been more of a threat than law professor Phillip Johnson? Articulate, educated leaders of the Creationist movement are going to keep popping up, generation after generation, whether we let them get reputable science doctorates or not. By banning them from graduate programs for their religious beliefs, we would be sacrificing our moral integrity for very little practical benefit.
If people like Marcus Ross do a good job and meet the requirements for a doctorate - that is, if they don't try rig their thesis committee to get away with substandard work, they should be cheerfully given their degrees. Who knows, some of these people may have their faith changed by their work - Ronald Numbers details several such cases, in his book The Creationists (this is highly recommended reading). Not many people can really live with that much cognitive dissonance for very long. And those who can should be allowed to take their degrees and go have a nice fulfilling career at academic holes like Liberty University.
A New Book by David Lindley on Quantum Mechanics
The NY Times has a review of a new book, Uncertainty by David Lindley, author of Boltzmann's Atom, a superb book on the late 19th century debate over atoms and the development of statistical mechanics. This latest book is about one of the most fascinating periods in the history of science - the development of quantum mechanics and its aftermath, especially the debates among Einstein, Bohr, and Heisenberg. Thinking about this period in science makes you wonder where such giants are today, ones in the same league as Einstein, Heisenberg, Bohr, Dirac, Bethe, Feynman...
Maybe this is just like the disappearance of the 0.400 hitter in baseball. Or maybe it has to do with the massive increase in the number of scientists since WWII and hence increasing competition, which produces pressure to pursue science that generates more immediate rewards - lots of quick, high profile papers, with a concomitant emphasis on multitasking as opposed to finding large, uninterrupted blocks of time to concentrate on a single deep problem. Maybe it's the length of time it takes now before a young scientist can truly work independently and the push for big interdisciplinary teams, sometimes at the expense of the interdisciplinary individual.
I'll get off my soapbox now. Lindley's book looks like it's worth checking out.
Maybe this is just like the disappearance of the 0.400 hitter in baseball. Or maybe it has to do with the massive increase in the number of scientists since WWII and hence increasing competition, which produces pressure to pursue science that generates more immediate rewards - lots of quick, high profile papers, with a concomitant emphasis on multitasking as opposed to finding large, uninterrupted blocks of time to concentrate on a single deep problem. Maybe it's the length of time it takes now before a young scientist can truly work independently and the push for big interdisciplinary teams, sometimes at the expense of the interdisciplinary individual.
I'll get off my soapbox now. Lindley's book looks like it's worth checking out.
Wednesday, February 07, 2007
The Latest IPCC Report on Climate Change
The Intergovernmental Panel on Climate Change has released its latest report, which of course has been all over the headlines. This report, already obsolete since it couldn't include the most recently published research, states more strongly than ever that humans have clearly contributed to global warming. We're reaching the point where professional scientists who continue to deny this are at risk of crossing the border into crank territory. As an inducement to make that border crossing, the American Enterprise Institute has offered $10,000 to several scientists to write critical essays of the IPCC's latest work.
I'm not suggesting anything negative about the recipients of this letter - yet. I have no idea how they responded. You can find the full text of the letter here on a site defending the AEI. No, the AEI is not asking these scientists change their mind for a bribe - they would be writing what they already believe. But read the letter and see how the AEI knocks the intergrity of the IPCC while telling the letter's recipient that "From our earlier discussions of climate modeling..., I developed considerable respect for the integrity with which your lab approaches the characterization of climate modeling data." Make of the letter what you will, but I certainly wouldn't go whoring away my scientific credibility by taking a $10,000 honorarium for an oil company-funded attack on climate change. It smells a lot like earlier tobacco-funded attacks on the link between smoking and cancer. Check out Cosmic Variance for some more commentary.
The well-funded and widely echoed opposition to climate change science in the US can make it hard to find scientifically reliable news sources amid the media coverage that tends gives equal time to unequally substantiated viewpoints. One place to look is the climate change feature on Nature's News site (some articles are free, some require a subscription). For a running commentary by people who are actually doing some of the relevant research, check out the Real Climate blog.
I'm not suggesting anything negative about the recipients of this letter - yet. I have no idea how they responded. You can find the full text of the letter here on a site defending the AEI. No, the AEI is not asking these scientists change their mind for a bribe - they would be writing what they already believe. But read the letter and see how the AEI knocks the intergrity of the IPCC while telling the letter's recipient that "From our earlier discussions of climate modeling..., I developed considerable respect for the integrity with which your lab approaches the characterization of climate modeling data." Make of the letter what you will, but I certainly wouldn't go whoring away my scientific credibility by taking a $10,000 honorarium for an oil company-funded attack on climate change. It smells a lot like earlier tobacco-funded attacks on the link between smoking and cancer. Check out Cosmic Variance for some more commentary.
The well-funded and widely echoed opposition to climate change science in the US can make it hard to find scientifically reliable news sources amid the media coverage that tends gives equal time to unequally substantiated viewpoints. One place to look is the climate change feature on Nature's News site (some articles are free, some require a subscription). For a running commentary by people who are actually doing some of the relevant research, check out the Real Climate blog.
Monday, February 05, 2007
Making Simple Model Systems to Study the Design Principles of Biological Networks
The speaker at our departmental seminar last week, Wenying Shou, discussed a system of cooperating yeast strains she has constructed, forthcoming in PNAS (link to abstract, full article requires subscription). She created two yeast strains which absolutely depend on each other for survival. Yeast are normally free-living single celled organisms. But Shou knocked out a gene required to make lysine (an amino acid, critical in many proteins) in one yeast strain, and a gene required to make adenine (needed to make DNA and RNA) in the other yeast strain. These yeast strains are perfectly fine on their own, as long as you supplement their broth or culture medium with adenine or lysine - if they can't make it, the yeast cells can pull it in from their environment. However, if you put these yeast strains alone in a culture medium without adenine or lysine, they die out.
Shou showed that you can put these two engineered strains together so that they each supply the missing nutrient required by the other strain (with a little bit of tweaking, described in the paper). The strain that cannot produce its own adenine does produce the lysine that's required by the other strain and visa versa. So what happens is this: you start out with a culture containing both strains, in medium missing lysine and adenine. The lysine-defective strain starts to die off because there is no lysine available. As the cells die, they release adenine (which they can synthesize) into the medium, which is quickly taken up and used by the other adenine-defective strain, which doesn't produce adenine. Soon enough, the adenine-defective strain sucks up all the adenine released by the first strain, and now the adenine-defective strain is dying. As it dies, it releases lysine, which the first strain, now near complete extinction, can take up, enabling it to start growing robustly again. And so this whole system goes back and forth, each strain supplying a missing nutrient to the other.
The beauty of this system is that all of the relevant parameters can be measured, such as how much adenine a cell releases when it dies, how fast a strain grows at a certain concentration of nutrient, etc. Shou was able to write a set of equations describing this relatively simple system, and create a phase diagram based on two variables - the number of cells from each strain used to start the cooperative culture:
So we now have a prediction - the two strains will cooperate and survive if you start them on one side of the phase diagram, but they will die out if you start them on the other side. If you start your culture with a number of cells that lies right on the dividing line, sometimes your culture will survive and sometimes it won't. That's exactly what Shou found when she started her cultures with varying numbers of cells from each strain.
I think this is a nice model system to play with, but the problem is that I'm not sure yet what key questions it can answer for us. The ostensible rationale for this system is to study cooperation in nature, but frankly I think this is too disconnected from real cooperating species found in nature to gain much insight. Furthermore, since cooperation is already established in this system, you're not really studying how cooperating systems evolve in the first place. In the paper itself, Shou and her co-authors barely make reference to the decades of field and theoretical studies that have analyzed natural cooperation, and I don't think they've identified any questions that field biologists would love to see answered with this model system.
But this is beside the point. Our inability to engineer any but the simplest cellular networks from scratch suggests that we are missing an important part of the picture of how cells work. We can't build a cell from scratch. One way forward is to build simple systems like Shou's, with measurable parameters and study the dynamics to learn more about the principles that underlie simple biological networks. The dynamics that Shou has produced so far are maybe a little too simple (if you read the paper, you'll notice that the system merely converges to a point attractor), but I don't doubt this system has potential. As more simple systems like this one become available, we will need to define the specific important questions we want to answer. We probably have most of the mathematical and physical tools we need, yet we are lacking the useful concepts that will enable us to seriously study how a cellular system works on a quantitative level.
Shou showed that you can put these two engineered strains together so that they each supply the missing nutrient required by the other strain (with a little bit of tweaking, described in the paper). The strain that cannot produce its own adenine does produce the lysine that's required by the other strain and visa versa. So what happens is this: you start out with a culture containing both strains, in medium missing lysine and adenine. The lysine-defective strain starts to die off because there is no lysine available. As the cells die, they release adenine (which they can synthesize) into the medium, which is quickly taken up and used by the other adenine-defective strain, which doesn't produce adenine. Soon enough, the adenine-defective strain sucks up all the adenine released by the first strain, and now the adenine-defective strain is dying. As it dies, it releases lysine, which the first strain, now near complete extinction, can take up, enabling it to start growing robustly again. And so this whole system goes back and forth, each strain supplying a missing nutrient to the other.
The beauty of this system is that all of the relevant parameters can be measured, such as how much adenine a cell releases when it dies, how fast a strain grows at a certain concentration of nutrient, etc. Shou was able to write a set of equations describing this relatively simple system, and create a phase diagram based on two variables - the number of cells from each strain used to start the cooperative culture:
So we now have a prediction - the two strains will cooperate and survive if you start them on one side of the phase diagram, but they will die out if you start them on the other side. If you start your culture with a number of cells that lies right on the dividing line, sometimes your culture will survive and sometimes it won't. That's exactly what Shou found when she started her cultures with varying numbers of cells from each strain.
I think this is a nice model system to play with, but the problem is that I'm not sure yet what key questions it can answer for us. The ostensible rationale for this system is to study cooperation in nature, but frankly I think this is too disconnected from real cooperating species found in nature to gain much insight. Furthermore, since cooperation is already established in this system, you're not really studying how cooperating systems evolve in the first place. In the paper itself, Shou and her co-authors barely make reference to the decades of field and theoretical studies that have analyzed natural cooperation, and I don't think they've identified any questions that field biologists would love to see answered with this model system.
But this is beside the point. Our inability to engineer any but the simplest cellular networks from scratch suggests that we are missing an important part of the picture of how cells work. We can't build a cell from scratch. One way forward is to build simple systems like Shou's, with measurable parameters and study the dynamics to learn more about the principles that underlie simple biological networks. The dynamics that Shou has produced so far are maybe a little too simple (if you read the paper, you'll notice that the system merely converges to a point attractor), but I don't doubt this system has potential. As more simple systems like this one become available, we will need to define the specific important questions we want to answer. We probably have most of the mathematical and physical tools we need, yet we are lacking the useful concepts that will enable us to seriously study how a cellular system works on a quantitative level.
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