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Biotech Open Source Science

Open Source Software Meets Do-It-Yourself Biology 113

Posted by Soulskill
from the releasing-your-genome-under-the-gpl dept.
destinyland writes "This article profiles a growing movement — DIY biology — that's made possible in part by open source tools. Using programs like BioPerl and BioPython, DIY biologists write their own code (computer and genetic), designing their own biological systems and altering the genome. A protein-folding simulator, Folding@home, is now the most powerful distributed computing cluster in the world, and as the movement evolves, cooperatives are also springing up where hobbyists pool resources and create 'hacker spaces' to reduce costs and share knowledge. 'As the shift to open source software continues, computational biology will become even more accessible, and even more powerful,' this article argues — while intellectual property and other bureaucracies continue to hobble traditional forms of research."
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Open Source Software Meets Do-It-Yourself Biology

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  • by Grond (15515) on Tuesday January 26, 2010 @02:13PM (#30907406) Homepage

    The article makes some vague statements that IP limits traditional biotech research. In fact, empirical studies do not back up such claims. John Walsh, Charlene Cho, Wesley Cohen, View from the Bench: Patents and Material Transfers [umd.edu] , 309 Science 2002-2003 (2005). Some highlights:

    "Thus, of 381 academic scientists, even including the 10% who claimed to be doing drug development or related downstream work, none were stopped by the existence of third-party patents, and even modifications or delays were rare, each affecting around 1% of our sample."

    "In addition, 22 of the 23 respondents to our question about costs reported that there was no fee for the patented technology, and the 23rd respondent said the fee was in the range of $1 to $100."

    19% of the respondents reported that other scientists had not complied with material transfer requests (i.e. requests for data or samples), but analysis found that "The patent status of the requested material had no significant effect on noncompliance."

    An additional, more focused case study of a highly-commercialized area of research with a lot of patent activity found that "only 3% of respondents reported stopping a project in the past 2 years because of a patent."

  • by Anonymous Coward on Tuesday January 26, 2010 @03:40PM (#30908706)

    http://en.wikipedia.org/wiki/The_White_Plague [wikipedia.org]

    Scared me way more than any "grey goo" idea.

  • by bzdyelnik (1600135) on Tuesday January 26, 2010 @04:00PM (#30908970)
    Don't forget R/Bioconductor! Not only is R free/free, but there are thousands of available Bioconductor packages ready for out-of-the-box use. Also consider Cytoscape and or EGAN for graph visualization of established and experimental bio-knowledge. http://www.bioconductor.org/ [bioconductor.org] http://www.cytoscape.org/ [cytoscape.org] http://akt.ucsf.edu/EGAN/ [ucsf.edu] (full disclosure - I work on EGAN)
  • by bzdyelnik (1600135) on Tuesday January 26, 2010 @04:11PM (#30909114)
  • by Grond (15515) on Tuesday January 26, 2010 @05:38PM (#30910326) Homepage

    I doubt that the harm happens at the level of actualised research, but rather research choices are effected by intellectual property. Thus, it slips by this study relatively unnoticed.

    Actually the study authors looked at that, too. "[F]ew academic bench scientists currently pay much attention to others' patents. Only 5% (18 out of 379) regularly check for patents on knowledge inputs related to their research...Five percent had been made aware of intellectual property (IP) relevant to their research through a notification letter sent either to them or their institution." If they don't even know if something is patented or not, it can't affect whether they decide to research it.

    Furthermore, "[E]ven for the few who were aware of others' patents, those third-party patents did not have a large impact on their research. Of the 32 respondents who were aware of relevant IP, four reported changing their research approach and five delayed completion of an experiment by more than 1 month. No one reported abandoning a line of research."

  • Re:Depends (Score:3, Informative)

    by interkin3tic (1469267) on Tuesday January 26, 2010 @06:24PM (#30910960)

    Many of these biology experiments require very expensive machines, such as microarray machines, as mentioned by the article. I don't know if purchasing refurbished machines is a wise choice since we don't want data quality to be compromised.

    A microarray is pretty expensive yes, but a lot of DIY biology could be done with just a computer and or a secondhand PCR machine. Used PCR machines apperantly can be had for under a grand [ebay.com]. Even less if you can service a broken one yourself, which many of these DIYers seem capable of. Probably won't have all the fancy options of a higher priced one either, but our academic lab has an expensive cycler with many options that we never use.

    Data quality with many of these things is less tempermental than a microarray too. The secondhand PCR machine in this case might not be good for sequencing, but it would be a great tool if you were, say, making a plasmid to make glowing bacteria, using it to identify species of plants, making in-situ hybridization primers. There are a lot of things you can do with a basic cheap PCR machine.

    As far as microarray data goes, an affymetrix premade microarray chip goes for about a thousand dollars. Obviously it's not feasible for most people to do many of these out of their own pocket, but not everyone does. Say you want to find out what genes are expressed more in dog breed A than dog breed B. If you were wanting to publish that data in a peer-reviewed journal, you'd probably need 6 chips, it seems like most people I know who do microarray do triplicates. If you were just wanting to find out for yourself, like to find canidates for which genes produced trait X that was in breed A, you could do just two, one for each, and hope it wasn't wildly innacurate. You could then focus your search based on that, taking it with a grain of salt until you confirmed it through other, less expensive means.

    If you were going to be doing many microarrays, this website [stanford.edu] appears to be a guide for making your own microarrayer. The price tag for building it exactly as that lab says to would be about $24k [stanford.edu]. Again though, many DIYers are mechanically inclined and could cut corners for their own purposes.

    Another issue is gathering the samples. If you're collecting yeast, that would be simple. Arabidopsis, other small plants, mice, or other small animals, you probably need quite some space.

    I don't see that. Our lab studies chicken embryos. An egg incubator is pretty small. C elegans can be grown wherever you've got space. Arabidopsis can grow in the yard, you don't need acres. A research-grade mouse colony would be expensive yes (maintaining a genetically pure mouse colony in a sterile environment free of variation is harder just obtaining mice from the street). If you need other model organisms, there are farms. It can be a limiting factor, yes, but when is that not true? You can't exactly use elephants as a model organism in really any lab in the world.

    Humans? That won't be simple at all. You have to clear privacy issues, getting the research review board to sign papers, etc.

    Which research review board? If I'm comparing gene expression in human blood samples in my garage, without using public grant money, the "review board" is whatever poor saps I sucker into giving me their blood.

    You can always resort to publicly available data. But chances are that you won't be able to impress scientists much for going that route. Also, most of the important discoveries are already done on this data.

    I reject both of those claims. Real scientists recognize valid results independant of the professional nature of the researcher or his lab. Hell, most of us "p

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