Knockout gene study shows “beautiful hierarchical structure” underlying cell’s biology

As to “beautiful hierarchical structure underlying cell’s biology", the following study is of interest. The regulatory network of a e-coli is found to be much more elegant than the operating system of Linux:

The Multi-dimensional Genome–impossible for Darwinism to account for– by Dr Robert Carter – video (15:52 minute mark: Comparing the Computer Operating Systems of Linux to the much more sophisticated operating systems of Regulatory Networks in e-coli) https://youtu.be/K3faN5fU6_Y?t=952 Comparing genomes to computer operating systems – Van – May 2010 Excerpt: we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology,,, http://www.ncbi.nlm.nih.gov/pubmed/20439753 regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) – Picture of comparison http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2889091/figure/F1/

Along that line, it is also found that bacteria ‘solve optimization problems for collective decision making that are beyond what we, human beings, can solve with our most powerful computers’

Learning from Bacteria about Social Networking (Information Processing) – video Excerpt: I will show illuminating movies of swarming intelligence of live bacteria in which they solve optimization problems for collective decision making that are beyond what we, human beings, can solve with our most powerful computers. http://www.youtube.com/watch?v=yJpi8SnFXHs

And also along that line, here is, according to a Darwinist, a ‘horrendously complex’ metabolic pathway chart of a ‘simple’ cell:

ExPASy – Biochemical Pathways – interactive schematic http://biochemical-pathways.com/#/map/1

As to trying to tag the number of 'essential genes' for biological life, i.e. for self replication, these following studies are of interest: Even the most stripped down bacteria imaginable, gives us every indication that life was Intelligently Designed

“No man-made program comes close to the technical brilliance of even Mycoplasmal genetic algorithms. Mycoplasmas are the simplest known organism with the smallest known genome, to date. How was its genome and other living organisms’ genomes programmed?” David L. Abel and Jack T. Trevors - Three Subsets of Sequence Complexity and Their Relevance to Biopolymeric Information – Theoretical Biology & Medical Modelling, Vol. 2, 11 August 2005, page 8 To Model the Simplest Microbe in the World, You Need 128 Computers – July 2012 Excerpt: Mycoplasma genitalium has one of the smallest genomes of any free-living organism in the world, clocking in at a mere 525 genes. That’s a fraction of the size of even another bacterium like E. coli, which has 4,288 genes.,,, The bioengineers, led by Stanford’s Markus Covert, succeeded in modeling the bacterium, and published their work last week in the journal Cell. What’s fascinating is how much horsepower they needed to partially simulate this simple organism. It took a cluster of 128 computers running for 9 to 10 hours to actually generate the data on the 25 categories of molecules that are involved in the cell’s lifecycle processes.,,, ,,the depth and breadth of cellular complexity has turned out to be nearly unbelievable, and difficult to manage, even given Moore’s Law. The M. genitalium model required 28 subsystems to be individually modeled and integrated, and many critics of the work have been complaining on Twitter that’s only a fraction of what will eventually be required to consider the simulation realistic.,,, http://www.theatlantic.com/technology/archive/2012/07/to-model-the-simplest-microbe-in-the-world-you-need-128-computers/260198/ Microbe with stripped-down DNA may hint at secrets of life – Mar 24, 2016 Excerpt: The newly created bacterium has a smaller genetic code than does any natural free-living counterpart, with 531,000 DNA building blocks containing 473 genes. (Humans have more than 3 billion building blocks and more than 20,000 genes). But even this stripped-down organism is full of mystery. Scientists say they have little to no idea what a third of its genes actually do. “We’re showing how complex life is, even in the simplest of organisms,” researcher J. Craig Venter told reporters. “These findings are very humbling.”,,, The genome is not some one-and-only minimal set of genes needed for life itself. For one thing, if the researchers had pared DNA from a different bacterium they would probably have ended up with a different set of genes.,,, The genome is “as small as we can get it and still have an organism that is … useful,” Hutchison said.,,, http://hosted.ap.org/dynamic/stories/U/US_SCI_SKINNY_GENES

As to their claim "if the researchers had pared DNA from a different bacterium they would probably have ended up with a different set of genes", I hold that there is virtually no doubt that they would have ended up with a different set of genes if they had started with a different bacteria.

,,,”Typical bacterial species. The smallest part of the pie are the genes that all bacteria share. 8% roughly. This second and largest slice (of the pie, 64%) are the genes that are specialized to some particular environment. They call them character genes. By far the biggest number of genes are the ones that are unique. This big green ball here (on the right of the illustration). These are genes found only in one species or its near relatives. Those are the ORFans (i.e. Genes with no ancestry). They said, on the basis of our analysis the genetic diversity of bacteria is of infinite size.” Paul Nelson – quoted from 103:48 minute mark of the following video Whatever Happened To Darwin's Tree Of Life? – Paul Nelson – video https://youtu.be/9UTrZX47e00?t=3820 "When biologists began sequencing genomes they discovered up to a third of genes in each species seemed to have no parents or family of any kind. Nevertheless, some of these "orphan genes" are high achievers (are just as essential as 'old' genes),,," - Helen Pilcher - Genes from nowhere: Orphans with a surprising story - 16 January 2013

Of related interest, here is a paper that calculates total number of possible distinct patterns of interactions of yeast to find the 'the interactome search space'. Needless to say, the paper finds that Darwinists are on the wrong side of the science once again.

The Humpty-Dumpty Effect: A Revolutionary Paper with Far-Reaching Implications - Paul Nelson - October 23, 2012 Excerpt: Tompa and Rose calculate the "total number of possible distinct patterns of interactions," using yeast, a unicellular eukaryote, as their model system; this "total number" is the size of the space that must be searched. With approximately 4,500 proteins in yeast, the interactome search space "is on the order of 10^7200, an unimaginably large number," they write -- but "more realistic" estimates, they continue, are "yet more complicated." Proteins present many possible surfaces for chemical interaction. "In all," argue Tompa and Rose, "an average protein would have approximately 3540 distinguishable interfaces," and if one uses this number for the interactome space calculation, the result is 10 followed by the exponent 7.9 x 10^10.,,, the numbers preclude formation of a functional interactome (of 'simple' life) by trial and error,, within any meaningful span of time. This numerical exercise...is tantamount to a proof that the cell does not organize by random collisions of its interacting constituents. (i.e. that life did not arise, nor operate, by chance!) http://www.evolutionnews.org/2012/10/a_revolutionary065521.html

bornagain77

from a friend: Not sure I've got the maths right from the Quanta article. The author says that the team were testing pairwise knockouts among 4800 inessential genes and generated 550,000 deleterious tests among 23 million unique pairs of genes (I assume they performed 23 million unique pairwise tests, which is pretty impressive). On the face of it this suggests that in any 100 randomly selected pairs of inessential genes, knockout is likely to be deleterious in roughly two cases. Seems pretty low to me - though if the genes are "inessential", then a low number is presumably to be expected. Also, 23 million variants is surely a tiny fraction of the total possible number of gene pairings among 4800 loci. Isn't that 2 to the power of 4800? Which is a number too big for my calculator to handle. The article is extremely interesting in all respects. O'Leary's specious misrepresentation of the science is not." AhmedKiaan

gpuccio @1:

Of course, in the complex network of gene interactions, many functions are redundant. Redundancy is a function itself, and a very important feature of good programming and of safety and efficiency of the design, especially in very complex structures.

Excellent point. Right on target, as usual. Here's a common example of redundancy as an important component of good design:

How Redundancy Improves the Safety of Your Flight http://www.jetairgroup.com/2012/03/03/how-redundancy-improves-the-safety-of-your-flight/ On audits and airplanes: Redundancy and reliability-assessment in high technologies http://www.sciencedirect.com/science/article/pii/S0361368211000456 By integrating dual global positioning system receivers with triple-redundant flight management systems, providing enhanced, simplified flight crew approach capability using the integrated approach navigation concept introduced on the Next-Generation 737, and including this information on the dual head-up displays (HUDs), the 787 offers the capability to reliably perform required navigation performance (RNP) procedures far into the future, improving operational efficiency. Two identical integrated surveillance systems provide reliable weather radar, transponder, traffic collision avoidance system, and ground proximity functionality. This redundancy improves dispatch safety and reliability and also provides a platform for growth to support future air traffic initiatives, such as Automatic Dependent Surveillance-Broadcast (ADS-B).

BTW, biological systems have been around a little longer than airplanes, right? :) Dionisio

Here is another study on yeast that falsified Darwinian claims from another angle:

Here Are Those Incongruent Trees From the Yeast Genome - Case Study - Cornelius Hunter - June 2013 Excerpt: We recently reported on a study of 1,070 genes and how they contradicted each other in a couple dozen yeast species. Specifically, evolutionists computed the evolutionary tree, using all 1,070 genes, showing how the different yeast species are related. This tree that uses all 1,070 genes is called the concatenation tree. They then repeated the computation 1,070 times, for each gene taken individually. Not only did none of the 1,070 trees match the concatenation tree, they also failed to show even a single match between themselves. In other words, out of the 1,071 trees, there were zero matches. Yet one of the fundamental predictions of evolution is that different features should generally agree. It was “a bit shocking” for evolutionists, as one explained: “We are trying to figure out the phylogenetic relationships of 1.8 million species and can’t even sort out 20 yeast.” In fact, as the figure above shows, the individual gene trees did not converge toward the concatenation tree. Evolutionary theory does not expect all the trees to be identical, but it does expect them to be consistently similar. They should mostly be identical or close to the concatenation tree, with a few at farther distances from the concatenation tree. Evolutionists have clearly and consistently claimed this consilience as an essential prediction. But instead, on a normalized scale from zero to one (where zero means the trees are identical), the gene trees were mostly around 0.4 from the concatenation tree with a huge gap in between. There were no trees anywhere close to the concatenation tree. This figure is a statistically significant, stark falsification of a highly acclaimed evolutionary prediction. http://darwins-god.blogspot.com/2013/06/here-are-those-incongruent-trees-from.html That Yeast Study is a Good Example of How Evolutionary Theory Works – Cornelius Hunter – June 2013 Excerpt:,,, The evolutionists tried to fix the problem with all kinds of strategies. They removed parts of genes from the analysis, they removed a few genes that might have been outliers, they removed a few of the yeast species, they restricted the analysis to certain genes that agreed on parts of the evolutionary tree, they restricted the analysis to only those genes thought to be slowly evolving, and they tried restricting the gene comparisons to only certain parts of the gene. These various strategies each have their own rationale. That rationale may be dubious, but at least there is some underlying reasoning. Yet none of these strategies worked. In fact they sometimes exacerbated the incongruence problem. What the evolutionists finally had to do, simply put, was to select the subset of the genes or of the problem that gave the right evolutionary answer. They described those genes as having “strong phylogenetic signal.” And how do we know that these genes have strong phylogenetic signal. Because they give the right (preferred) answer. This is an example of a classic tendency in science known as confirmation bias.,,, http://darwins-god.blogspot.com/2013/06/that-yeast-study-is-good-example-of-how.html

bornagain77

Very interesting. That's exactly the reason why single gene knockout experiments cannot be considered a final test to assess function, and sometimes seem to contradict data from sequence conservation. Of course, in the complex network of gene interactions, many functions are redundant. Redundancy is a function itself, and a very important feature of good programming and of safety and efficiency of the design, especially in very complex structures. Sequence conservation remains the best positive indicator of function, because sequences that are preserved by negative selection for hundreds of millions of years must necessarily be highly functional and constrained. Knockout experiments can only reveal the tip of the iceberg of functional complexity in biology. gpuccio