linkstream2 microblog

QT:{{”
In 1665, Christiaan Huygens [Huygens, 1673] noted “When we suspended two clocks so constructed from two hooks imbedded in the same wooden beam, the motions of each pendulum on opposite swings were so much in agreement that they never receded the least bit from each other and the sound of each was always heard simultaneously. Further, if this agreement was disturbed by some interference, it reestablished itself in a short time. For a long time I was amazed at this unexpected result, but after a careful examination finally found that the cause of this is due to the motion of the beam, even though this is hardly perceptible. The cause is that the oscillations of the pendula, in proportion to their weight, communicate some motion to the clocks. This motion, impressed onto the beam, necessarily has the effect of making the pendula come to a state of exactly contrary swings if it happened that they moved otherwise at first, and from this finally the motion of the beam completely ceases.” The study of coupled
oscillators has since become an active branch of mathematics, with applications in physics, biology, and chemistry. In physics, one encounters coupled oscillators in arrays of Josephson junctions [Chung et al., 1989, Blackburn et al., 1994], in modelling molecules [Sage, 1994], and in coupled lasers [Dente et al., 1990]. Coupled oscillators are also prevalent in biological systems. Most organisms appear to be coupled to various periodicities extant in our surroundings, such as the rotation of the earth about the sun, the alternation of night and day, or the tides. Not only do organisms exhibit periodicities due to their environment, but they also exhibit innate periodic behavior. Breathing, pumping blood, chewing, and galloping are examples of rhythmic patterns of motion…
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http://web.cse.ohio-state.edu/pnl/theses/campbell/Ch1.pdf

Disease-disease relationships through the incomplete interactome, by @barabasi http://www.sciencemag.org/content/347/6224/1257601.abstract #Network modules for 226 diseases

QT:{{”
Altogether, disease genes associated with 226 of the 299 diseases show a statistically significant tendency to form disease modules based on both Si andP(ds) (fig. S4).
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Distributed Info. Processing in Biological & Computational #Systems http://cacm.acm.org/magazines/2015/1/181614-distributed-information-processing-in-biological-and-computational-systems/fulltext Contrasts in strategies to handle node failures

QT:{{"
While both computational and biological systems need to address these similar types of failures, the methods they use to do so differs. In distributed computing, failures have primarily been handled by majority voting methods,37 by using dedicated failure detectors, or via cryptography. In contrast, most biological systems rely on various network topological features to handle failures. Consider for example the use of failure detectors. In distributed computing, these are either implemented in hardware or in dedicated additional software. In contrast, biology implements implicit failure detector mechanisms by relying on backup nodes or alternative pathways. Several proteins have paralogs, that is, structurally similar proteins that in most cases originated from the same ancestral protein (roughly 40% of yeast and human proteins have at least one paralog). In several cases, when one protein fails or is altered, its paralog can automatically take its place24 or protect the cell against the mutation.26 Thus, by preserving backup functionality in the protein interaction.

…
While we discussed some reoccurring algorithmic strategies used within both types of systems (for example, stochasticity and feedback), there is much more to learn in this regard. From the distributed computing side, new models are needed to address the dynamic aspects of communication (for example, nodes joining and leaving the network, and edges added and being subtracted), which are also relevant in mobile computing scenarios. Further, while the biological systems we discussed all operate without a single centralized controller, there is in fact a continuum in the term “distributed.” For example, hierarchical distributed models, where higher layers “control” lower layers with possible feedback, represent a more structured type of control system than traditional distributed systems without such a hierarchy. Gene regulatory networks and neuronal networks (layered columns) both share such a hierarchical structure, and this structure has been well-conserved across many different species, suggesting their importance to computation. Such models, however, have received less attention in the distributed computing literature.

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#Neuroscience, Ethics & National Security http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001289
Interrogations w/ oxytocin truth serum, No-lie fMRI & p300 waves. Scary!

QT:{{"
National security agencies are also mining neuroscience for ways to advance interrogation methods and the detection of deception. The increasing sophistication of brain-reading neurotechnologies has led many to investigate their potential applications for lie detection. Deception has long been associated with empirically measurable correlates, arguably originating nearly a century ago with research into blood pressure [24]. Yet blood pressure, among other modern bases for polygraphy like heart and breathing rates, indicates the presence of a proxy for deception: stress. Although the polygraph performs better than chance, it does not reliably and accurately indicate the presence of deception, and it is susceptible to counter measures. ….

“Brain fingerprinting” utilizes EEG to detect the P300 wave, an event-related potential (ERP) associated with the perception of a recognized, meaningful stimulus, and it is thought to hold potential for confirming the presence of “concealed information” [25]. The technology is marketed for a number of uses: “national security, medical diagnostics, advertising, insurance fraud and in the criminal justice system” [26]. Similarly, fMRI-based lie detection services are currently offered by several companies, including No Lie MRI [27] and Cephos [28]. DARPA funded the pioneering research that showed how deception involves a more complex array of neurological processes than truth-telling, and that fMRI arguably can detect the difference between the two [29]. No Lie MRI also has ties to national security: they market their services to the DoD, Department of Homeland Security, and the intelligence community, among other potential customers [30].

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In addition to questions of scientific validity, these technologies raise legal and ethical issues. Legally required brain scans arguably violate “the guarantee against self-incrimination” because they differ from acceptable forms of bodily evidence, such as fingerprints or blood samples, in an important way: they are not simply physical, hard evidence, but evidence that is intimately linked to the defendant’s mind [32]. Under US law, brain-scanning technologies might also raise implications for the Fourth Amendment, calling into question whether they constitute an unreasonable search and seizure [33].”

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Phylomemetics—Evolutionary Analysis beyond the Gene
http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001069 #Phylogenetics for texts, languages & artifacts (w/ recoding)

What Can Article-Level Metrics Do for You
http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001687 Wide distribution of #cites for @PLOSBiology papers; median 19 but 10% >50

[[DW: very large-scale models (vs. VLSI): markov logic network on customer networks, Innovation Award Talk by Pedro Domingos, KDD 2014 ]]

http://homes.cs.washington.edu/~pedrod/803

also, it has biological applications like:
Markov Logic Networks in the Analysis of Genetic Data
https://www.systemsbiology.org/markov-logic-networks-analysis-genetic-data

Where Do #Introns Come From? A suggestion: exons with premature stops; has implications for #pseudogene formation http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.0060283

QT:{{
We have proposed a novel hypothesis for the origin of spliceosomal
introns, invoking endogenous production within translatable sequences
(at least in the case of protein-coding genes), facilitated by the
activity of cellular surveillance mechanisms. Despite the mutational
hazard associated with intron presence and proliferation [136], we
argue that, at least initially, introns might represent a favorable
life line for an allele that has acquired an ORF-disrupting mutation.
In this sense, in-frame stop codons need not be dead ends, as often
believed, but rather sequences that occasionally facilitate the
evolution of eukaryotic gene structure, possibly favoring not only
intronization, but also processes such as exonization (following a PTC
loss [137]). Further experimental validation of our hypothesis would
not only support the idea that intron birth/death rates depend on both
the population-genetic [136] and the intracellular environment, but
also shed light on a surprising aspect of the evolution of eukaryotic
gene structure, i.e., the ongoing, stochastic process of mutual
conversion between exons and introns within genes.
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Is Sleep Essential?
http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.0060216 Amusing evidence from varied animals, eg 1-hemisphere dolphin #sleep & dying sleep-deprived rats

http://netbiopub.tumblr.com
associated w/ linkedin group