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In the age of Big Data, it turns out that the largest, fastest growing data source lies within your cells.
Quantitative biologists at the University of Illinois Urbana-Champaign and Cold Spring Harbor Laboratory, in New York, found that genomics reigns as champion over three of the biggest data domains around: astronomy, Twitter, and YouTube.
The scientists determined which would expand the fastest by evaluating acquisition, storage, distribution, and analysis of each set of data. Genomes are quantified by their chemical constructs, or base pairs. Genomics trumps other data generators because the genome sequencing rate doubles every seven months. If it maintains this rate, by 2020 more than one billion billion bases will be sequenced and stored per year, or 1 exabase. By 2025, researchers estimate the rate will be almost one zettabase, one trillion billion bases, per sequence per year.
Cripes, wouldn't you hate to be the guy paying the electricity bill to process that much data?
(Score: 1, Interesting) by Anonymous Coward on Friday July 10 2015, @01:13PM
Here is the research article: http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002195 [plos.org]
I predict that after decades of fishing the genomic data ocean and finding "significant" relationships, researcher's will finally realize genome sequence is relatively unimportant when it comes to health. Much more important is cyclical patterns of expression level. A mutated half functioning enzyme can be compensated by expressing twice as many. A knocked out gene can be compensated by different ones that performs similar functions. Living things consist of dynamic networks of feedbacks that seek equilibrium states.
(Score: 2) by ikanreed on Friday July 10 2015, @01:57PM
Then I don't think you know what they're fishing for.
Genomic(and epigenomic) research has already shown some of the most common differentiations of cancer cells. And many of the newest chemotherapies on the market specifically target proteins, enzymes, and processes that genetic research has revealed to be tied to specific kinds of cancer.
Genetic research has failed to support a lot of the more common genetic determinism arguments. People with high IQs don't seem to share any sort of genetic commonalities with each other that they don't also have in common with low IQ people. We always assumed they would because of years of twin studies hinting at it.
(Score: 1, Informative) by Anonymous Coward on Friday July 10 2015, @03:03PM
The somatic mutation rate is too low (10^-10 per nucleotide and 10-7 per gene each division)[1], to ever account for most cancers even assuming insane rates of dna replication (normal cells dividing once a day). If that theory was correct we wouldn't observe peaks in age-specific incidence as seen in fig 7 of ref [2]. It is something else, possibly aneuploidy, which messes up expression of many, many genes at once:
https://www.ncbi.nlm.nih.gov/pubmed/15549096 [nih.gov]
I don't know if it is aneuploidy, but it is something much more common than somatic mutations. That theory is wrong. Although they may contribute, the mutations are symptom of the problem. It was worth investigating, but now 50 years later it is a case of biased people spreading misinformation and wasting money. None of those drugs will cure cancer because tumor cells are genetically unstable. They will eventually select for resistant cells. They may slow tumor growth, but that it will come back. That is why these days you'll only hear about "effective cures", ie slowing tumor growth past the point you are likely to die of something else.
[1] http://www.ncbi.nlm.nih.gov/pubmed/11309271 [nih.gov]
[2] http://users.physics.harvard.edu/~wilson/publications/ppaper789.pdf [harvard.edu]
(Score: 2) by ikanreed on Friday July 10 2015, @03:05PM
Interesting. I'll have to rethink (and further research) my understanding of cancer.
(Score: 0) by Anonymous Coward on Friday July 10 2015, @03:39PM
You can see the error in this paper. The parameter p refers to probability of a tumor cell forming:
http://www.ncbi.nlm.nih.gov/pubmed/23396311 [nih.gov]
The models they use have simplifying assumptions built in that are incompatible with the peak in age specific incidence. Equation 5 in that paper will only increase with age. To get the peaks, the tumor cells must form much more often, but most do not generate tumors (either they go dormant or die off). It is also possible the multistage theory (cancer is caused by some kind of accumulation of errors) is totally wrong, but it makes a lot of sense.