Uncommon Descent Serving The Intelligent Design Community

Controlling the waves of dynamic, far from equilibrium states: the NF-kB system of transcription regulation.

I have recently commented on another thread: about a paper that (very correctly) describes cells as dynamic, far from equilibrium systems, rather than as “traditional” machines. That is true. But, of course, the cell implements the same functions as complex machines do, and much more. My simple point is that, to do that, you need much greater functional complexity than you need to realize a conventional machine. IOWs, dynamic, far from equilibrium systems that can be as successful as a conventional machine, or more, must certainly be incredibly complex and amazing systems, systems that defy everything else that we already know and that we can conceive. They must not only implement their functional purposes, but they must do that by Read More ›

Mechanosensing and Mechanotransduction: how cells touch their world.

Fig. 1: Cnidaria are probably one of the most ancient phyla of known Metazoa.   Metazoa, or multicellular organisms, are one of the amazing “novelties” in natural history. At some point, single eukaryotic cells begin to be organized in a new, incredibly complex plan: a multicellular organism. It is well known and understood that one of the main tools to realize that innovation, that new expression of life, is cell differentiation. Cells, while sharing the same genome, become different, incredibly different one from the other. Stem cells differentiate and acquire, through amazing and still poorly understood epigenetic trajectories, completely different cellular phenotypes and functions. The miracle of transcription regulation, as we have seen in another recent OP, is at the Read More ›

Transcription regulation: a miracle of engineering

Transcription is certainly the essential node in the complex network of procedures and regulations that control the many activities of living cells. Understanding how it works is a fascinating adventure in the world of design and engineering. The issue is huge and complex, but I will try to give here a simple (but probably not too brief) outline of its main features, always from a design perspective.   Fig. 1 A simple and effective summary of a gene regulatory network   Introduction: where is the information? One of the greatest mysteries in cell life is how the information stored in the cell itself can dynamically control the many changes that continuosly take place in living cells and in living beings. Read More ›

Isolated complex functional islands in the ocean of sequences: a model from English language, again.

      A few days ago, Denyse published the following, very interesting, OP: Laszlo Bencze offers an analogy to current claims about evolution: Correcting an F grade paper Considering that an example is often better than many long discussions, I have decided to use part of the analogy presented there by philopsopher and photographer Laszlo Bencze to show some important aspects of the concept of isolated islands of complex functional information, recently discussed at this OP of mine: Defending Intelligent Design theory: Why targets are real targets, probabilities real probabilities, and the Texas Sharp Shooter fallacy does not apply at all. and in the following discussion. So, I will quote here the relevant part of Bencze’s argument, the part that Read More ›

Defending Intelligent Design theory: Why targets are real targets, probabilities real probabilities, and the Texas Sharp Shooter fallacy does not apply at all.

      The aim of this OP is to discuss in some order and with some completeness a few related objections to ID theory which are in a way connected to the argument that goes under the name of Texas Sharp Shooter Fallacy, sometimes used as a criticism of ID. The argument that the TSS fallacy is a valid objection against ID has been many times presented by DNA_Jock, a very good discussant from the other side. So, I will refer in some detail to his arguments, as I understand them and remember them. Of course, if DNA_Jock thinks that I am misrepresenting his ideas, I am ready to ackowledge any correction about that. He can post here, if he Read More ›

The Ubiquitin System: Functional Complexity and Semiosis joined together.

This is a very complex subject, so as usual I will try to stick to the essentials to make things as clear as possible, while details can be dealt with in the discussion. It is difficult to define exactly the role of the Ubiquitin System. It is usually considered mainly a pathway which regulates protein degradation, but in reality its functions are much wider than that. In essence, the US is a complex biological system which targets many different types of proteins for different final fates. The most common “fate” is degradation of the protein. In that sense, the Ubiquitin System works together with another extremely complex cellular system, the proteasome. In brief, the Ubiquitin System “marks” proteins for degradation, Read More ›

The spliceosome: a molecular machine that defies any non-design explanation.

OK, let’s start with a very simple fact: eukaryotic genes have introns. IOWs, they are not continuous. They are made of exons and introns: exon – intron – exon – intron – exon and so on. Exons code for the protein. Introns don’t. So, when the content of the gene is copied to the mRNA, introns must be cut away, and only exons are retained, in order to be translated, so that the mature mRNA can be transferred to the cytoplasm and translated by the ribosome. This process of removing introns is called splicing. Now, a few clarifications: a) Introns exist in prokaryotes too, but they are rather rare. For our purposes, we will only discuss introns in eukaryotes. b) Read More ›

Bioinformatics tools used in my OPs: some basic information.

EugeneS made this simple request in the thread about Random Variation: I also have a couple of very concrete and probably very simple questions regarding the bioinformatics algorithms and software you are using. Could you write a post on the bioinformatics basics, the metrics and a little more detail about how you produced those graphs, for the benefit of the general audience? That’s a very reasonable request, and so I am trying here to address it. So, this OP is mainly intended as a reference, and not necessarily for discussion. However, I will be happy, of course, to answer any further requests for clarifications or details, or any criticism or debate. My first clarification is that I work on proteins Read More ›

What are the limits of Random Variation? A simple evaluation of the probabilistic resources of our biological world

Coming from a long and detailed discussion about the limits of Natural Selection, here: https://uncommondesc.wpengine.com/intelligent-design/what-are-the-limits-of-natural-selection-an-interesting-open-discussion-with-gordon-davisson/#comment-642154 I realized that some attention could be given to the other great protagonist of the neo-darwinian algorithm: Random Variation (RV). For the sake of clarity, as usual, I will try to give explicit definitions in advance. Let’s call RV event any random event that, in the course of Natural History, acts on an existing organism at the genetic level, so that the genome of that individual organism changes in its descendants. That’s more or less the same as the neo-darwinian concept of descent with modifications. A few important clarifications: a) I use the term variation instead of mutation because I want to include in the definition all possible kinds Read More ›

What are the limits of Natural Selection? An interesting open discussion with Gordon Davisson

An interesting discussion, still absolutely open, has taken place in the last few days between Gordon Davisson and me on the thread: https://uncommondesc.wpengine.com/intelligent-design/what-only-an-extremely-occasional-mutation-is-beneficial-but-darwinism/ Some very good friends, like Dionisio, Mung and Origenes, seem to have appreciated the discussion, which indeed has touched important issues. Origenes has also suggested that it could be transformed into an OP. Well, I tought that it was probably a good idea, and luckily it did not require much work. 🙂   So, here it is. Gordon Davisson’s posts are in italics. It’s a bit long, and I am sorry for that! I thank in advance Gordon Davisson for the extremely good contribution he has already given, and for any other contribution he will give. He Read More ›

Interesting proteins: DNA-binding proteins SATB1 and SATB2

With this OP, I am starting a series (I hope) of articles whose purpose is to present interesting proteins which can be of specific relevance to ID theory, for their functional context and evolutionary history. DNA-binding protein SATB1 SATB1 (accession number Q01826) is a very intriguing molecule. Let’s start with some information we can find at Uniprot, a fundamental protein database, about what is known of its function (in the human form): Crucial silencing factor contributing to the initiation of X inactivation mediated by Xist RNA that occurs during embryogenesis and in lymphoma And: Transcriptional repressor controlling nuclear and viral gene expression in a phosphorylated and acetylated status-dependent manner, by binding to matrix attachment regions (MARs) of DNA and inducing a Read More ›

The amazing level of engineering in the transition to the vertebrate proteome: a global analysis

As a follow-up to my previous post: https://uncommondesc.wpengine.com/intelligent-design/the-highly-engineered-transition-to-vertebrates-an-example-of-functional-information-analysis/ I am presenting here some results obtained by a general application, expanded to the whole human proteome, of the procedure already introduced in that post. Main assumptions. The aim of the procedure is to measure a well defined equivalent of functional information in proteins: the information that is conserved throughout long evolutionary times, in a well specified evolutionary line. The simple assumption is that  such information, which is not modified by neutral variation in a time span of hundreds of million years, is certainly highly functionally constrained, and is therefore a very good empirical approximation of the value of functional information in a protein. In particular, I will use the proteins in the human proteome Read More ›

The highly engineered transition to vertebrates: an example of functional information analysis

In the recent thread “That’s gotta hurt” Bill Cole states: I think over the next few years 3 other origins (my note: together with OOL), will start to be recognized as equally hard to explain: The origin of eukaryotic cell: difficult to explain the origin of the spliceosome, the nuclear pore complex and chromosome structure. The origin of multicellular life: difficult to explain the origin of the ability to build complex body plans. The origin of man: difficult to explain the origin of language and complex thought. That thought is perfectly correct. There are, in natural history, a few fundamental transitions which scream design more that anything else. I want to be clear: I stick to my often expressed opinion Read More ›

Information jumps again: some more facts, and thoughts, about Prickle 1 and taxonomically restricted genes.

  My previous post about information jumps, based on the example of the Prickle 1 protein, has generated a very interesting discussion, still ongoing. I add here some more thoughts about an aspect which has not been really analyzed in the first post, and which can probably contribute to the discussion. I will give here only a very quick summary of the basic issue, inviting all those interested to check my first post: Homologies, differences and information jumps and the following discussion, amounting at present at more than 500 posts. So: Prickle 1 is an interesting protein, with rich functional properties, in general still not well understood. With reference to the human form, I have identified two different parts in the protein. Read More ›

Homologies, differences and information jumps

In recent posts, I have been discussing some important points about the reasonable meaning of homologies and differences in the proteome in the course of natural history. For the following discussion, just to be clear, I will accept a scenario of Common Descent (as explained in many recent posts) in the context of an ID approach. I will also accept the very reasonable concept that neutral or quasi-neutral random variation happens in time, and that negative (purifying) selection is the main principle which limits random variation in functional sequences. My main points are the following: Given those premises, homologies through natural history are certainly an indicator of functional constraints, because they mean that some sequence cannot be significantly transformed by random variation. Another way Read More ›