I argued many times here that biology based biotechnology is the next information technology but in order to do so, biotech should harness good IT patterns and mimic its massive computing practices to handle the enormous amount of constantly accumulating data. Often this trend could be summarized in a simple way: keep your eye on Google and conduct thought experiments in advance in which science is done in a Googleplex like environment in terms of the computing & financial resources and algorithm heavy engineering culture. Use Python and learn cluster computing and MapReduce. With the expected launch of the massive scientific dataset hosting Google service - nicknamed Palimpsest - this year finally a direct interface between scientists and Googlers emerges and hopefully opens up possibilities for scientists to cooperate with Google. (Remember my joke on Google BioLabs back in 2006)? I get emails from biologists, bioinformaticians asking me how to be hired by Google ever since then. As I tweeted yesterday: I growingly have the impression that “being ambitious” today = ‘worked, is currently working, is going to work at/for Google’ Taking Google’s inter-industrial power into consideration I see a real chance that some day the “Google of Biotechnology” title goes not to a startup yet to be emerged, not to Genentech or to 23andMe but……to Google itself. No kidding here. Fortunately Google’s model is “to build a killer app then monetize it later” says Andy Rubin, the man behind Google’s Android mobile software in the July issue of Wired so scientists working for the big G probably won’t have to worry about turning their scientific killer app into an instant cash machine.
And now in the very issue of Wired magazine (not online yet ) there is an exciting cover story on the same pattern I talked about concerning the life sciences but in the broader context of every kind of science with the provocative, Fukuyama-like title The End of Science. There is a witty and short essay from editor-in-chief Chris Anderson entitled The End of Theory followed by examples of the ‘new science’ like the The Large Hadron Collider expected to generate 10 petabytes if data/second, The Sloan Digital Sky Survey heaven catalog maker accumulating 25 terrabytes of data so far, the skeleton scanning project of Sharmila Majumdar and the Many Eyes project “where users can share their own dynamic, interactive representations of big data”.
For many people around the globe, Chris Anderson is a freeconomist & the author of a popular airport book but fewer people are aware that he was actually trained as a (quantum) physicist and even worked at Los Alamos Read the rest of this entry »
When I had worked on my MSc thesis in biology on the relation of human mitochondrial mutations and aging the paper I used most frequently was Sequence and organization of the human mitochondrial genome by Anderson et al. published in Nature, 1981. The reason was simple: it is more of a database than a hypothesis driven article with the published 16.569 base pair sequence of the circular human mitochondrial genome (L-strand) containing 37 genes and a bigger non-coding, regulatory region. Throughout my work I had to use it as a basic reference. The sequence is a reconstruction of a single European individual’s mtDNA and contains several rare alleles. Nice figure isn’t it?
I’ve just realized with the help of genomics pioneer and warrior Craig Venter’s recent molecular autobiography Life decoded, that the brilliant two time Nobel laureate, sequencing urfather Frederick Sanger is also a coauthor of the paper. Here comes Venter: Read the rest of this entry »
Stem cell biology and regenerative medicine as an institutionally specified discipline is quite young, about a decade old. So it is no surprise that there is not a thing as a natural born stem cell researcher. All the famous researchers, the founding fathers and mothers came from other disciplines and studied something else as undergrads (just like in the case of molecular biology): they were veterinarians (like James Thomson, who received his doctorate in veterinary medicine), neurobiologists (Fred Gage), developmental biologists, biochemists, molecular biologists, classical medical doctors, bioengineers and so on.
All these people got immersed into stem cell research lately in their careers and so they carry their original motivations, disciplinary intuition and knowledge base when thinking about stem cells. This is the sign of an immature discipline but also good for creative ideas to enter. Historically stem cell biology and regenerative medicine will probably become a closed, paradigm ruled discipline with the necessary restrictions and less outsider innovations. The first generation of genuine stem cell researchers are years to come.
But today all stem cell researchers can become pioneers as they have the chance to form and invent radically new paradigms, not to live by them.
If there is any? Stem cell biology and regenerative medicine as an institutionally specified discipline is quite young, about a decade old. Bone marrow transplantation traces its roots back to the 1970-s, but many people don’t realize that it is the most useful although restricted form of stem cell therapy till this day. In my opinion the birth date of present day stem cell biology is Thomson et al.’s 1998 November paper in Science on EmbryonicStemCellLinesDerivedfromHumanBlastocysts.
Not because it was so original. It is known that much of the embryonic stem cell isolation protocol and the in vivo teratoma forming as pluripotency test came from two papers by Cambridge biologists, appeared in 1981 that reported the derivation of pluripotent stem cell lines from cultured mouse embryos. But the Thomson results were based on human cells and this is a crucial difference concerning potential regenerative therapies as it was discussed in the paper: “The standardized production of large,purified populations of euploid humancells such as cardiomyocytesand neurons will provide a potentially limitless source of cellsfor drug discovery and transplantation therapies. Many diseases,such as Parkinson’s disease and juvenile-onset diabetes mellitus,result from the death or dysfunction of just one or a few celltypes. The replacement of those cells could offer lifelong treatment.” Also the timing of the paper was good. The 2 Cambridge papers, which were also mentioned as references in the Thomson et al. paper.:
Evans, M. J. & Kaufman, M. H. Establishment in culture of pluripotential cells from mouse embryos. Nature 292, 154-6. (1981).
Martin, G. R. Isolation of a pluripotent cell line from early mouse embryos cultured in medium conditioned by teratocarcinoma stem cells. Proc. Natl. Acad. Sci. USA 78, 7634-7638 (1981).
In your opinion: What is the birth date of present day stem cell biology? Is there any discrete point? How would you locate the beginnings of stem cell science in time and space?
In David Scadden’s elegant review on The stem-cell niche as an entity of action I found the historically first article in which the concept of the stem cell niche was proposed: “The concept of a niche as a specialized microenvironment housing stem cells was first proposed by Schofield almost 30 years ago in reference to mammalian haematology, although experimental evidence was first provided by invertebrate models”. Now Schoefield is an active researcher since then and the paper was published in Blood Cells. Here is the abstract of the paper, notice the context (primary HSC candidate), the now familiar concepts like “immortality of stem cell population” and also the weird ones like “first generation colony-forming cells”.
“Several experimental findings that are inconsistent with the view that the spleen colony-forming cell (CFU-S) is the primary haemopoietic stem cell are reviewed. Recovery of CFU-S, both quantitatively and qualitatively, can proceed differently depending upon the cytotoxic agent or regime used to bring about the depletion. The virtual immortality of the stem cell population is at variance with evidence that the CFU-S population has an ‘age-structure’ which has been invoked by several workers to explain experimental and clinical observations. To account for these inconsistencies, a hypothesis is proposed in which the stem cell is seen in association with other cells which determine its behaviour. It becomes essentially a fixed tissue cell. Its maturation is prevented and, as a result, its continued proliferation as a stem cell is assured. Its progeny, unless they can occupy a similar stem cell ‘niche’, are first generation colony-forming cells, which proliferate and mature to acquire a high probability of differentiation, i.e., they have an age-structure. Some of the experimental situations reviewed are discussed in relation to the proposed hypothesis.”
Finally a journalist at Wired, Brandon Keim thought it’s time to check out some facts and formulate real arguments in the embryonic stem cell funding debate instead of boondoggling. He has collected good historical examples of long-term funding in drug research, which then saved many lives, like Taxol, and has enumerated fields of promising science, like proteomics, gene therapy and nanotechnology which are heavily donated with hundreds of millions of dollars by federal government, although as unproven yet as regenerative medicine based on embryonic stells. Thank you Brandon it is really wired. Link
“A favorite argument as to why the federal government should not fund embryonic stem cell research is that the science is unproven. It has not led to any cures or FDA-approved treatments. That happens to be true. But that doesn’t make it a good argument. In fact, most of the science funded by the federal government is not successful yet, since proven science doesn’t usually need funding.”
I tried to explain to my girlfriend the historical recipe of discovering the structure of DNA by Watson and Crick in 3 shots. Place: in front of the blue paque outside Eagle Pub near old Cavendish, Cambridge, UK. (For me, iMovie is not as intuitive without the Help, which explains the poor quality.)
From the annotated version of the Watson and Crick paper: “Their competitive spirit drove them to work quickly, and it undoubtedly helped them succeed in their quest. Watson and Crick’s rapport led them to speedy insights as well. They incessantly discussed the problem, bouncing ideas off one another. This was especially helpful because each one was inspired by different evidence. When the visually sensitive Watson, for example, saw a cross-shaped pattern of spots in an X-ray photograph of DNA, he knew DNA had to be a double helix. From data on the symmetry of DNA crystals, Crick, an expert in crystal structure, saw that DNA’s two chains run in opposite directions.”
I argued many times here that biology based biotechnology is the next information technology but in order to do so, biotech should harness good IT patterns and mimic its massive computing practices to handle the enormous amount of constantly accumulating data. Often this trend could be summarized in a simple way: keep your eye on Google and conduct thought experiments in advance in which science is done in a Googleplex like environment in terms of the computing & financial resources and algorithm heavy engineering culture. Use Python and learn cluster computing and MapReduce. With the expected launch of the massive scientific dataset hosting Google service - nicknamed Palimpsest - this year finally a direct interface between scientists and Googlers emerges and hopefully opens up possibilities for scientists to cooperate with Google. (Remember my joke on Google BioLabs back in 2006)? I get emails from biologists, bioinformaticians asking me how to be hired by Google ever since then. As I tweeted yesterday: I growingly have the impression that “being ambitious” today = ‘worked, is currently working, is going to work at/for Google’ Taking Google’s inter-industrial power into consideration I see a real chance that some day the “Google of Biotechnology” title goes not to a startup yet to be emerged, not to Genentech or to 23andMe but……to Google itself. No kidding here. Fortunately Google’s model is “to build a killer app then monetize it later” says Andy Rubin, the man behind Google’s Android mobile software in the July issue of Wired so scientists working for the big G probably won’t have to worry about turning their scientific killer app into an instant cash machine.
When I had worked on my MSc thesis in biology on the relation of human mitochondrial mutations and aging the paper I used most frequently was 
