Information Basics
"The heart of his theory is a simple but very general model of communication: A transmitter encodes information into a signal, which is corrupted by noise and then decoded by the receiver. Despite its simplicity, Shannon’s model incorporates two key insights: isolating the information and noise sources from the communication system to be designed, and modeling both of these sources probabilistically. He imagined the information source generating one of many possible messages to communicate, each of which had a certain probability. The probabilistic noise added further randomness for the receiver to disentangle." Full article @ Quanta Magazine.
Welcome to Life-Inspired, ISE483/SSIE583 Spring 2026 Class. On this blog you will see many types of posts related to the class, from links to multimedia materials used in class, to breaking research on related topics. The updated first chapter of the course's lecture notes is now available:
ISE483/SSIE583: What is Life?
You can also listen to the AI-produced podcast or video of this chapter via Google NoteBookLM. Note, the AIpodcast and video does not substitute the lecture notes at all! it brings up many connections not really in the argument, it is provided for fun only.
"we first discuss the micro-cascade proposed by Leibniz, which describes how the self-reproducing machine of the cell is built of smaller submachines down to the atomic scale. In the other direction, we propose that a macro-cascade builds from cells larger, organizational machines, up to the scale of the biosphere. The two cascades meet at the critical point of 103 s in time and 1 micron in length, the scales of a microbial cell. We speculate on how this double cascade evolved once a self-replicating machine emerged in the salty water of prebiotic earth". Full paper at PNAS.
Evolution of complexity through regulatory variation at a single gene
"Life history traits evolve to optimize an organism’s survival and reproductive output in response to natural selection (7). They are complex traits—e.g., size at birth, growth pattern, and age at maturity—that combine variation in physiology, development, and behavior to maximize fitness in a particular environment. Due to their complexity, variation in life history traits is expected to involve multiple genes (polygenic) (5), a genetic architecture that is particularly difficult to study given the statistical challenge of linking the effect of multiple low-effect genes to phenotypic variation. [...] The study of Verta et al. (6) revealed vgll3’s master control over multiple regulatory pathways, supporting the notion that it acts indeed as a hub gene." Full report at PNAS. Sell also the paper by Verta et al.
Related studies are reported by Rosvall, summarizing work identifying regulation of behavior and morphology driven by testosterone, which is formed via complex enzymatic pathways, but can be controlled by a single gene in birds, resulting in impressive morphological and behavioral diversity.
Evolution takes multiple paths to evolvability when facing environmental change
"we use digital evolution to show that changing environments facilitate the simultaneous evolution of high mutation rates and a distribution of mutational effects skewed toward beneficial phenotypes. The evolved mutational neighborhoods allow rapid adaptation to previously encountered environments, whereas higher mutation rates aid adaptation to completely new environmental conditions. By precisely tracking evolving lineages and the phenotypes of their mutants, we show that evolving populations localize on phenotypic boundaries between distinct regions of genotype space. Our results demonstrate how evolution shapes multiple determinants of evolvability concurrently, fine-tuning a population’s adaptive responses to unpredictable or recurrent environmental shifts".Full paper @ PNAS.
Optimal flock formation induced by agent heterogeneity
"The study of flocking in biological systems has identified conditions for self-organized collective behavior, inspiring the development of decentralized strategies to coordinate the dynamics of swarms of drones and other autonomous vehicles. Previous research has focused primarily on the role of the time-varying interaction network among agents while assuming that the agents themselves are identical or nearly identical. Here, we depart from this conventional assumption to investigate how inter-individual differences between agents affect the stability and convergence in flocking dynamics." Full article at the ArXiv.
Loved this piece by Melanie Mitchell: "I’d guess that it’s actually our human limitations [...] and complex environments that require us to form more abstract and generalizable internal models." Her thinking is very much in line with Pattee's and Rosen's concept of internal models, especially the former's notion of "selective loss of detail.
LLMs and World Models, Part 2 by Melanie Mitchell
Evidence For (and Against) Emergent World Models in LLMs
Mathematicians discover new class of shape seen throughout nature
‘Soft cells’ — shapes with rounded corners and pointed tips that fit together on a plane — feature in onions, molluscs and more. Full news article by Philip Glass at Nature.
Very cool use of machine learning to infer more precise rules of RNA transcription from DNA, including, strength, local and long-rage instructions: "The rules rely on three types of sequence patterns: motifs, initiators, and trinucleotides. The nine motifs are the main drivers of transcription initiation signals and can have short- or long-distance effects. The 11 initiators fine-tune transcription initiation signals but only have local effects. The 32 trinucleotides (representing all three-nucleotide combinations of A, C, G, and T) account for the remaining sequence dependencies not captured by motifs and initiators and have mostly local effects." Full news article and the original paper @ Science.
Complexity Thoughts is a wonderful digest of research in complex systems, theoretical bioology, and biomedical complexity, annotated by Manlio Dedomenico.
"What vindicates the complex-systems people, as I see it, is the recognition of “emergent behaviors,” unexpected phenomena that arise from seemingly simple interactions." James Gleick, Full interview by Daniel Drake at New York Review of Books.
Modeling and managing behavior change in groups: A Boolean network method
"Social influence processes can induce desired or undesired behavior change in individual members of a group. Empirical modeling of group processes and the design of network-based interventions meant to promote desired behavior change is somewhat limited be-cause the models often assume that the social influence is assimilative only and that the networks are not fully connected. We introduce a Boolean network method that addresses these two limitations. In line with dynamical systems principles, temporal changes in group members’ behavior are modeled as a Boolean network that also allows for application of control theory design of group management strategies that might direct the groups to-wards desired behavior". Full paper @ Advances.in/psychology.
Researchers have crafted synthetic genomes for several types of bacteria, and an 18-year-long project to do the same for brewer’s yeast is close to completion. Now, a group in China has tackled a multicellular organism, synthesizing part of the genome of a type of moss.Full news article at Science.
Diversity of information pathways drives sparsity in real-world networks
"What if the same physics that governs quantum particles could also explain the peculiar patterns observed in protein-protein interactions, in complex brains, in social relationships, in the Internet infrastructure or the intricate web of air traffic routes? This is not science fiction: it is a mathematical framework, based on thermodynamics and information theory, that has been used for decades to describe entanglement in quantum systems." See an explanation in the great Complexity Thoughts newsletter and the full paper at Nature Physics.
"As they collect and analyze massive amounts of genetic sequences from plants, animals, and microbes, biologists keep encountering surprises, including some that may challenge the very definition of life. The latest, reported this week in a preprint, is a new kind of viruslike entity that inhabits bacteria dwelling in the human mouth and gut. " Full News Report @ "Science"
The results remind me of computational experiments we did a long time ago with RNA Editing, where we experimented with drastic fitness changes (simulated cataclysms) and emergence of memory. RNA Editing, we started arguing long ago, also adds additional regulatory variety and proves advantageous in drastic fitness changes---though RNA editing works by adding more variants, not greater number of regulatory possibilities (network connectivity) as it is hypothesized for polyploidy. Maybe this explains why the latter is maladaptive in stable fitness landscapes, whereas RNA Editing often isn't?
Multilevel cultural evolution: From new theory to practical applications
Evolutionary science has led to many practical applications of genetic evolution but few practical uses of cultural evolution. This is because the entire study of evolution was gene centric for most of the 20th century, relegating the study and application of human cultural change to other disciplines. The formal study of human cultural evolution began in the 1970s and has matured to the point of deriving practical applications. We provide an overview of these developments and examples for the topic areas of complex systems science and engineering, economics and business, mental health and well-being, and global change efforts. Full article: Wilson, David Sloan, et al. "Multilevel cultural evolution: From new theory to practical applications." Proceedings of the National Academy of Sciences 120.16 (2023): e2218222120.
RNA editing is hypothesized to facilitate adaptive evolution via flexibly diversifying the proteome temporally or spatially. However, direct experimental evidence is lacking. This study unveils the functional importance of conserved missense adenosine-to-inosine (A-to-I) RNA editing (CME) sites in Fusarium graminearum and provides convincing experimental evidence for the adaptive advantages of two CME sites. The first CME site drives the CME5 gene gaining a new important function in ascus and ascospore formation during evolution. Having an editable A at this site is fitter than an uneditable A or a genomically encoded G. The second CME site in the CME11 gene confers a “heterozygote advantage” during ascosporogenesis, meaning that concurrently expressing both edited and unedited versions is more advantageous than either. Full article: Xin, Kaiyun, et al. "Experimental evidence for the functional importance and adaptive advantage of A-to-I RNA editing in fungi." Proceedings of the National Academy of Sciences120.12 (2023): e2219029120.
A new take on Ai, is "Wet" AI using organoids and other sythetic biology methods. "We anticipate OI-based biocomputing systems to allow faster decision-making, continuous learning during tasks, and greater energy and data efficiency. Furthermore, the development of “intelligence-in-a-dish” could help elucidate the pathophysiology of devastating developmental and degenerative diseases (such as dementia), potentially aiding the identification of novel therapeutic approaches to address major global unmet needs." Full article @ Frontiers in Science. Thank you Xuanchi Li for the article.
"Laning is a paradigmatic example of spontaneous organization in active two-component flows that has been observed in diverse contexts, including pedestrian traffic, driven colloids, complex plasmas, and molecular transport. We introduce a kinetic theory that elucidates the physical origins of laning and quantifies the propensity for lane nucleation in a given physical system. Our theory is valid in the low-density regime, and it makes different predictions about situations in which lanes may form that are not parallel with the direction of flow. We report on experiments with human crowds that verify two notable consequences of this phenomenon: tilting lanes under broken chiral symmetry and lane nucleation along elliptic, parabolic, and hyperbolic curves in the presence of sources or sinks." Full article @ Science.
We propose a biologically plausible model, based on a variant of the reinforced random walk on a graph, which explains this observation and suggests surprising algorithms for the shortest path problem and its variants. Full paper @ PNAS.
Scientists created DNA nanotube rails that branch in multiple directions, with each unique track made up of unique DNA patterns. Protein motors designed to recognize these patterns then carry their cargo down the desired tracks. Nanoswitchyards should help scientists better test and understand the real thing inside cells. They may also eventually help researchers steer different drug cargoes to different tissues or engineer novel DNA computers that respond to their environment. In the video, proteins called dyneins have been engineered to glide along DNA tracks. At a branch point, different DNA patterns of the tracks steer dyneins carrying orange fluorescent cargo to the left and dyneins carrying cyan fluorescent compounds to the right.
"Dynamical systems can be chaotic and impossible to predict, but mathematicians have discovered tools to help understand them". Full article by David S. Richeson at Quanta Magazine.
3D underwater collective behaviors in a fish-inspired robot swarm
"most underwater robot collectives rely on centralized, above-water, explicit communication and, as a result, exhibit limited coordination complexity. Here, we demonstrate 3D collective behaviors with a swarm of fish-inspired miniature underwater robots that use only implicit communication mediated through the production and sensing of blue light. We show that complex and dynamic 3D collective behaviors—synchrony, dispersion/aggregation, dynamic circle formation, and search-capture—can be achieved by sensing minimal, noisy impressions of neighbors, without any centralized intervention." Full paper @ Science Robotics.
Exciting work bridging biology and computing from josh Bongard and Michael Levin, who "present a method that designs completely biological machines from the ground up: computers automatically design new machines in simulation, and the best designs are then built by combining together different biological tissues." Full article @ PNAS.
"A yellow organism which looks like fungus but acts like an animal has gone on display at the Paris Zoological Park. The slime mould - Physarum polycephalum - has almost 720 sexes and has been described as one of "nature's mysteries" by scientists. It can heal itself in two minutes if cut in half, and detect and digest food despite not having eyes, a mouth or a stomach." From BBC News.
"A robotic system has been demonstrated in which the random motion of individual components leads to deterministic behaviour, much as occurs in living systems. Environmental and medical applications could follow." News article and full paper @ Nature.
"Novelty detection is a fundamental biological problem that organisms must solve to determine whether a given stimulus departs from those previously experienced. [The authors show] the algorithmic basis of an important neurobiological problem and offers strategies for novelty detection in computational systems." Full paper @ PNAS.
"A common theme in the self-organization of multicellular tissues is the use of cell-cell signaling networks to induce morphological changes. We used the modular synNotch juxtacrine signaling platform to engineer artificial genetic programs in which specific cell-cell contacts induced changes in cadherin cell adhesion. Despite their simplicity, these minimal intercellular programs were sufficient to yield assemblies with hallmarks of natural developmental systems: robust self-organization into multi-domain structures, well-choreographed sequential assembly, cell type divergence, symmetry breaking, and the capacity for regeneration upon injury. The ability of these networks to drive complex structure formation illustrates the power of interlinking cell signaling with cell sorting: signal-induced spatial reorganization alters the local signals received by each cell, resulting in iterative cycles of cell fate branching. These results provide insights into the evolution of multi-cellularity and demonstrate the potential to engineer customized self-organizing tissues or materials."