On the Artchitecture of Life

A conversation on the architecture of life has been recorded and released as an audio podcast at Syntalk.  The speakers are: Dr. Pushpa M. Bhargava (molecular biology, CCMB, Hyderabad), Prof. Nagarjuna G. (philosophy of science, HBCSE, Mumbai).  The following description is the text copied from the Syntalk link.

SynTalk thinks about the key conditions that characterize and create ‘biological’ life while constantly wondering whether life is a random accident, and if we are alone in the universe (because of a singularity?). What is the future of life? How aliens (if any) are also likely to be carbon and water based, but could be completely different morphologically and functionally. How was the first cell formed, and is this one of the biggest open questions today? The continuing journey after the big bang from the physical to astrophysical to chemical to biological to social evolution (across all species via, say, pollination) way into the distant future. The concepts are derived off / from Darwin, Crick, Watson, Hoyle, Prigogine, Manfred Eigen, Delbruck, Maturana, & Stuart Kauffman, among others. Is it possible to create synthetic life in a laboratory, and does the clue to this possibility lie in the (chemical?) nature of a virus? How does speciation happen? The core significance of the cell being a ‘phase separated structure’ with organizational closure. Is the cell the unity of life? How we do ‘not’ really know where biology ends and chemistry begins. Is life a physical state (just as liquid is a state of water)? The definition of life via replication (DNA, tRNA), metabolism (metabolic charts, glucose) and energy transduction. We discuss the role of glucose as a key molecule for all life, and wonder what it is like for glucose (& other bio molecules) to be ‘outside’ life. How does self organization arise in both physical and biological systems, and how (for example) phospholipids (with hydrophobic tails and hydrophilic heads) organize itself in water? How affinities can emerge between two DNA strands. How life is a dialogical state, and neither the physical equilibrium (oxidized state like carbon dioxide) nor the state of chemical death (‘petroleum state’). How virus ‘lives’ on the border of life and non-life. How all living stems can be characterized using unique chemistry, biochemistry, structure, & function. Why life originated from water? What is the role of weak bonds (in, say, the colloidal state of protoplasm)? How does ‘conscious cognition’ arise in living systems, & what are the links with ‘emancipated reflexive motor actions’, microtubules, dance, lizard, play, & consciousness (Mind from Matter). How does a living system talk to itself (why does a child suck its thumb)? How the feeling of ‘free will’ gives an (illusory) advantage. How life has multiple answers, and an inherent capability to change. How life is an expression of abundance. How a bio molecule is not like a sphere. The future with artificial life, cognitive robotics, & ‘languages in nature’ (of animals & languages). Why we can’t wear a full body armour anymore?

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Saturation in the scale-free dependency networks of free software

As reported in my previous post on Debian Dependency Maps we started to study the properties of dependency relation and the kind of networks the relation can generate.  One preliminary study we (me along with Arnab K. Ray and Rajiv Nair) posit a  nonlinear model for the global analysis of data pertaining to the semantic network of a complex operating system (free and open-source software). While the distribution of links in the dependency network of this system is scale-free for the intermediate nodes, we found that the richest nodes deviate from this trend, and exhibit a nonlinearity-induced saturation effect. This also distinguishes the two directed networks of incoming and outgoing links from each other. The initial condition for a dynamic model, evolving towards the steady dependency distribution, determines the saturation properties of the mature scale-free network.

Here I give some of the motivations on conducting this study and some conclusions.
The full paper with all the technical details is uploaded at arxiv.org.

Scale-free distributions in complex networks have been very well studied by now. The ubiquity of scale-free properties is quite noteworthy, and spans across vastly  diverse domains like (to name a few) the World Wide Web and the Internet, the social, ecological, biological and linguistic networks, income and wealth distributions, trade and business networks, and semantic networks.

It should occasion no surprise, therefore, that further developments have led to the discovery of scale-free features in the architecture of computer software as well. A recent
work  has shown that the structure of object-oriented software is a heterogeneous network characterised by a power-law distribution.  More in keeping with the purpose of this present paper, an earlier work on complex networks in software engineering had found evidence of power-law behaviour in the inter-package dependency networks in free and open-source software (FOSS).  It is a matter of common knowledge that when it comes to installing a software package from the  Debian GNU/Linux repository, many other packages — the “dependencies” — are also called for as prerequisites. This leads to a network of these dependencies, and every such package may be treated as a node in a network of dependency relationships. Each dependency relationship connecting any two packages (nodes) is treated as a link (an edge), and every link establishes a relation between a prior package and a posterior package, whereby the functions defined in the
prior package are called in the posterior package. This enables reuse (economy) of functions and eliminates duplicate development. As a result the whole operating system emerges as a coherent and stable semantic network. However, unlike other semantic networks, the network of nodes in the Debian repository is founded on a single relation spanning across all its nodes: Y depends on X; its inverse, X is required for Y .
So, given any particular node, its links (the relations with other nodes) can be of two types — incoming links and outgoing links — as a result of which, there will arise two distinct kinds of directed network.  For the network of incoming links, a newly-reported work  has empirically established the relevance of Zipf’s law and the conditions attendant on it in Debian GNU/Linux distribution. Carrying further along these very lines, the present study purports to analyse and model the finite-size effects in a FOSS network. There is a general appreciation that for any system with a finite size, the power-law trend is not manifested indefinitely, and in the context of the FOSS network, this is a matter that is recognised as one worthy of a more thorough investigation. Deviations from the power-law trend appear for both the heavily-linked and the sparsely-linked nodes. The former case corresponds to the distribution of a disproportionately high number of links connected to a very few special nodes — the so-called “top nodes” (or rich nodes).  The importance of these nodes is, therefore, a self-evident fact.

The data needed for the modelling pertain to the current stable Debian release, Etch (Debian GNU/Linux 4.0).  The respective networks of both the incoming links and the outgoing links span 18630 nodes (software packages).
The study argues for the significance of non-linearity and saturation, as regards a quantitative characterisation of the incoming and outgoing distribution in the Debian GNU/Linux network.  One might rightly expect to encounter similar features in other networks.  And indeed, given the possibility that the entire network of software packages in an operating system can be construed to be a semantic (albeit non-autonomous) system, its characteristics can furnish a model that can shed light on much more complex but realistic autonomous semantic and cognitive systems, such as the human society, or
even the human mind.

In the road ahead, the gnowledge lab will conduct a similar study for the dependencies between concepts and activities as and when we obtain sufficient number of nodes at gnowledge.org.  Currently we have only about 1000 dependency relations.  As more people get to know about the need of establishing dependency relation between concepts, and as and when the portal itself matures with features to attract more users we can study the properties of the resulting knowledge network.

The full paper with all the technical details is uploaded at arxiv.org.