Biosystems最新文献

{"title":"Measures of gene indispensability reveal the parallelism between phylogeny and ontogeny","authors":"Juraj Bergman ,&nbsp;Robert Bakarić ,&nbsp;Krunoslav Brčić-Kostić","doi":"10.1016/j.biosystems.2026.105710","DOIUrl":"10.1016/j.biosystems.2026.105710","url":null,"abstract":"<div><div>Haeckel's biogenetic law, or the recapitulation theory remains a controversial subject to this day since it is not based on quantitative regularities. Currently, the modern version of the biogenetic law is the hourglass model with its phylotypic period. Importantly, the hourglass model does not provide evidence that ontogeny recapitulates phylogeny, and it is often presented as the alternative model to recapitulation theory. However, the hourglass model and recapitulation are not mutually exclusive, and there are several examples of recapitulation-like processes observable after the phylotypic period of ontogeny. At the level of transcriptomics, all attempts to demonstrate recapitulation failed. Using a novel approach, combining transcriptomics with phylostratigraphy, we demonstrate that recapitulation exists as a quantitatively testable law. We show that the mean indispensability of genes decreases for phylogenetically younger genes, as well as genes expressed during later stages of ontogeny. We also define the ontotypic period of phylogeny, an analog to the phylotypic period of ontogeny. Since it starts from the beginning of phylogeny, it is reasonable to hypothesize that recapitulation starts from the phylotypic period. We conclude that parallelism, or recapitulation, is explainable by the fact that genes that emerged later in phylogeny have tendencies to be expressed during later stages of ontogeny. This is expected from the fundamental properties of Darwinian evolution which is based on conservation of existing gene functions by purifying selection and addition of new gene functions by positive selection. According to this, our result (the existence of parallelism or recapitulation) represents the empirical evidence for macroevolution.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"261 ","pages":"Article 105710"},"PeriodicalIF":1.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146020418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relaxation effects in cell microtubule under the influence of an external electric field: The mean field approximation","authors":"V.A. Saenko ,&nbsp;S.Eh. Shirmovsky ,&nbsp;D.V. Shulga","doi":"10.1016/j.biosystems.2026.105705","DOIUrl":"10.1016/j.biosystems.2026.105705","url":null,"abstract":"<div><div>The quantum relaxation processes in the microtubule dipole system under the action of an external electric field have been studied. The study is based on the Born–Markov equation. Tubulins dipole–dipole interaction and the internal dynamics of the dipole system that is determined by the quantum tunneling effect in the double potential well is taken into account. A system of differential equations defining the relaxation processes in a microtubule consisting of 676 tubulins is obtained. It was shown that the relaxation nature strongly depends on the magnitude of the dipole–dipole interaction, the internal dynamics of the dipole system, and the influence of the dissipative process. The decoherence time equal to 10⁻¹⁴ s – 10⁻⁹ s depending on the features of the relaxation process was determined. It has been proved that, the relaxation can have a twofold character, defining mixed or pure states.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"261 ","pages":"Article 105705"},"PeriodicalIF":1.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145991584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A precision-aware spike timing determination in Courbage–Nekorkin–Vdovin neuron map model: Statistical approaches and FPGA-based realization","authors":"Nimet Korkmaz","doi":"10.1016/j.biosystems.2026.105714","DOIUrl":"10.1016/j.biosystems.2026.105714","url":null,"abstract":"<div><div>This study focuses on five different neural dynamics related to spike timing determination in the Courbage–Nekorkin–Vdovin (CNV) neuron map model. These neural dynamics are simulated numerically through the double-precision arithmetic and fixed-point arithmetic, separately. Notable temporal shifts are observed between the spike timings generated by these simulations. Since the accurate determinations of the spike timings are the critical requirement for modeling the functional behavior of neurons, three different statistical methods are used to determine the spike timings of these neuron behaviors in these performed numerical simulations. The concordances between the spike timings of the systems, which are simulated through two separate arithmetic approaches, are compared by calculating the means and the standard deviations of their time differences. This process is repeated for three statistical methods, namely, “mean + K × Standard Deviation (Std)”, “median + K × Median Absolute Deviation (MAD)”, and “z-score normalization” methods. On the other hand, the requirement to fixed-point arithmetic usage arises due to the limited resources and energy consumption of the digital hardware. Accordingly, in addition to presenting a statistical analysis study that considers the spike timing conditions during the simulations of the CNV neuron map model, this neuron map model is constructed on the Field Programmable Gate Array (FPGA) device by using the fixed-point arithmetic. Therefore, this study aims additionally to verify the applicability of the process on hardware by performing its electronic implementation.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"261 ","pages":"Article 105714"},"PeriodicalIF":1.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining and finding lifelike entities with a lazy filter","authors":"Mario Martinez-Saito","doi":"10.1016/j.biosystems.2025.105672","DOIUrl":"10.1016/j.biosystems.2025.105672","url":null,"abstract":"<div><div>Our binary intuitive understanding of life and lifelikeness is good enough for daily life, but not for research in the natural sciences. Here we propose an operational definition of the lifeness of an entity, or object defined by its structure, as a scalar, namely the product of its defining information (algorithmic complexity) integrated over its lifetime. We provide a hierarchical Gaussian, yet parameter-free, dynamical filtering algorithm that can efficiently and on-the-fly fit configurations of entities constituted by moving particles to a tree structure that can model a wide range of hierarchical system entities, while extracting and calculating the complexity, lifespan, and lifeness of the entity and all of its constituting subtrees or subentities. We simulated 41 interacting particle worlds and found preliminary evidence suggesting that the lifeness of entities is associated with the distance to criticality, as roughly measured by the range of the pairwise interaction forces of the elemental particles of the worlds they inhabit. This study is a proof of concept that defining, measuring, and quantifying lifeness is (1) feasible, useful for (2) simplifying theoretical discussions, for (3) hierarchically assessing biotic properties such as number of hierarchical levels and predicted longevity and for (4) classifying both artificial and biological entities, respectively via computer simulations and a combination of evolutionary and molecular biology approaches.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"260 ","pages":"Article 105672"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145851353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Darwin to teleonomy: A categorical final-cause calculus for evolution","authors":"Andrei T. Patrascu","doi":"10.1016/j.biosystems.2025.105687","DOIUrl":"10.1016/j.biosystems.2025.105687","url":null,"abstract":"&lt;div&gt;&lt;div&gt;We propose a &lt;em&gt;teleonomical calculus&lt;/em&gt; for evolution that generalizes the classical Darwin–Fisher picture by making &lt;em&gt;final causes&lt;/em&gt; – what systems keep true about themselves – into mathematical objects with universal properties. In our framework, the state space is a category &lt;span&gt;&lt;math&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt; acted upon (laxly) by time &lt;span&gt;&lt;math&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;, and viability constraints live in a fibration &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;p&lt;/mi&gt;&lt;mo&gt;:&lt;/mo&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mo&gt;→&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. An &lt;em&gt;endogenous&lt;/em&gt; functor &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;G&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;:&lt;/mo&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mo&gt;→&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;E&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; extracts invariants from the system (e.g. topological features via persistent homology, sheaf gluing compatibilities, symmetry/conservation laws, or behavioral attractors). The present compatible with realizing these constraints at horizon &lt;span&gt;&lt;math&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt; is the right Kan extension &lt;span&gt;&lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;Tel&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mo&gt;Ran&lt;/mo&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;ι&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mi&gt;Φ&lt;/mi&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;X&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;0&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;equivalently a (possibly enriched) limit or a largest invariant subcoalgebra. Passing to concrete dynamics &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;x&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; yields an &lt;em&gt;endogenous bias&lt;/em&gt; that selects among feasible futures without introducing exogenous rewards: &lt;span&gt;&lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;d&lt;/mi&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;x&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mi&gt;f&lt;/mi&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;x&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;e&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;d&lt;/mi&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mi&gt;ɛ&lt;/mi&gt;&lt;msub&gt;&lt;mrow&gt;&lt;","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"260 ","pages":"Article 105687"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145919073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring potential size-dependent effects of Fibonacci-based acoustic binary strings on cells as measured by cell death and cell aggregation patterns","authors":"Edward Rietman ,&nbsp;Jack A. Tuszynski ,&nbsp;Geraldine A. Hamilton ,&nbsp;Gianni Martire","doi":"10.1016/j.biosystems.2025.105689","DOIUrl":"10.1016/j.biosystems.2025.105689","url":null,"abstract":"<div><div>This paper presents a preliminary investigation into potential size-dependent effects of Fibonacci-based acoustic signals on cells. Cellular responses to externally applied acoustic excitation were evaluated through measurements of reduced cell viability and changes in spatial aggregation patterns. To analyze these effects mathematically, binary Fibonacci sequences were converted into acoustic drive signals, and their spectral properties were examined. These signals distribute energy across multiple frequencies in a deterministic but non-periodic manner that exhibits fractal-like characteristics, with an estimated pointwise dimension of approximately 1.7. Experimental observations using three unicellular model systems (<em>Chlorella vulgaris</em>, <em>Saccharomyces cerevisiae</em>, and <em>Haematococcus pluvialis</em>) suggest that different cell sizes exhibit their strongest responses at different tested frequencies. An exploratory mathematical relationship between cell size and acoustic wavelength, size = (λ + 0.835)/0.8988 (R² = 0.8819), was observed and is presented as a hypothesis-generating trend that warrants further investigation. The range of statistical significance observed across experiments (p-values ranging from approximately 0.003 to 0.1) indicates that additional studies are required to assess reproducibility and elucidate underlying mechanisms. While these initial findings suggest possible directions for future research, substantial further investigation would be necessary to determine any potential relevance to therapeutic applications.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"260 ","pages":"Article 105689"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145901522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid DNN model using novel integrated interface features for predicting protein-protein complexes binding affinity","authors":"Lichao Zhang ,&nbsp;Zhengyan Bian ,&nbsp;Xue Wang ,&nbsp;Liang Kong","doi":"10.1016/j.biosystems.2025.105688","DOIUrl":"10.1016/j.biosystems.2025.105688","url":null,"abstract":"<div><div>Accurately predicting binding affinity of protein-protein complexes is significant for gaining deeper insights into complex biological mechanisms. Given that binding between proteins primarily occurs at the interface region, previous studies have demonstrated that the number of inter-residue contacts (ICs) and the buried surface area (BSA) are critical interface features. However, existing models generally used these two types of interface features separately, ignoring integrating them effectively to achieve high prediction accuracy. In this study, utilizing kernel density estimation-based mutual information and the Hadamard product, we proposed an effective approach that integrates BSA and ICs to construct the novel integrated interface features that embody dual structural information, and further derived our feature set. Subsequently, the proposed feature set was input Deep Neural Network (DNN), and a hybrid DNN model was further developed following our hybrid modeling strategy. To enhance its prediction performance, a combined activation function was customized for the output layers. Ultimately, using four-fold cross-validation, our hybrid DNN model achieved a Pearson correlation coefficient (R) of 0.88 and a root mean square error (RMSE) of 1.301 kcal/mol, and we verified its good generalization capability, achieving R = 0.82 and RMSE = 1.21 kcal/mol on the external test set derived from the SKEMPI 2.0 database. Compared with existing approaches, our method consistently exhibited superior predictive performance, validating the effectiveness of the proposed method for protein-protein binding affinity prediction. Moreover, the integration strategy for binding affinity representation and the hybrid modeling method may be helpful for related research.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"260 ","pages":"Article 105688"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145890426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligence as high-dimensional coherence: The observable dimensionality bound and computational tractability","authors":"Ian Todd","doi":"10.1016/j.biosystems.2026.105704","DOIUrl":"10.1016/j.biosystems.2026.105704","url":null,"abstract":"<div><div>Intelligence arises from the maintenance of high-dimensional coherent dynamics. High-dimensional systems are effectively nonergodic on relevant timescales—the curse of dimensionality confines trajectories to vanishingly small regions relative to the full space. This confinement is not a limitation but the foundation of biological computation: a system’s position in phase space functions as its memory, its constraints, its structured dynamics. Within these nonergodic regions, high entropy flow enables rich internal exploration; at the boundary, sparse outputs minimize free energy expenditure while defending the conditions for continued nonergodic existence. We formalize this through an Observable Dimensionality Bound: external observers cannot track systems whose effective dimensionality exceeds a critical threshold set by channel capacity and temporal resolution. This bound functions as protection—the opacity of high-dimensional dynamics shields internal structure from external disruption. Living systems exploit this by embodying the dynamics: the substrate is the high-dimensional field, information lives in geometric configuration, and irreversible commitments concentrate at sparse behavioral output events. The framework illuminates a thermodynamic pressure contributing to the efficiency gap between biological and artificial intelligence (brains concentrate irreversible commitments at behavioral boundaries rather than at every internal micro-update), provides a substrate-independent characterization of intelligence (capacity to maintain and defend coherent high-dimensional dynamics), and connects to the emergence of reusable codes through adaptive dynamics. Human cortex likely operates beyond this observable threshold, consistent with recent discussions of consciousness and dimensionality in the systems biology literature.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"260 ","pages":"Article 105704"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expert-guided multi-objective optimization: An efficient strategy for parameter estimation of biological systems with limited data","authors":"Léa Da Costa Fernandes ,&nbsp;David Bernard ,&nbsp;François Pérès ,&nbsp;Paul Monsarrat ,&nbsp;Béatrice Cousin ,&nbsp;Sylvain Cussat-Blanc","doi":"10.1016/j.biosystems.2025.105686","DOIUrl":"10.1016/j.biosystems.2025.105686","url":null,"abstract":"<div><div>Calibrating biological models is challenging due to high-dimensional parameter spaces and the limited availability of reliable experimental data. In this study, we propose a hybrid calibration framework that integrates expert knowledge into a multi-objective optimization process. We have evaluated three multi-objective optimization algorithm (NSGA-III, MOEA/D and MO-TPE) with our framework to combine hard constraints derived from biological measurements with soft constraints encoding qualitative domain expertise, such as expected curve shapes or event timing. This dual-constraint strategy guides the search toward biologically plausible parameter sets while preserving flexibility and interpretability. We demonstrate the effectiveness of our method on a benchmark model of skin wound healing, comparing it to standard and unconstrained optimization strategies. Results show that the framework reduces the risk of overfitting to sparse time-course data by favoring dynamically plausible trajectories that satisfy expert-guided soft constraints, increasing the proportion of biologically plausible solutions generated from 1.8% <span><math><mo>±</mo></math></span> 1.3 to 24.3% <span><math><mo>±</mo></math></span> 8.6 for NSGA-III without constraint to NSGA-III with 6 constraints, respectively (<span><math><mrow><mi>p</mi><mo>&lt;</mo><mn>0</mn><mo>.</mo><mn>0001</mn></mrow></math></span>). The framework is flexible, iterative, and generalizable, offering a principled way to leverage domain knowledge for model calibration in complex biological systems.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"260 ","pages":"Article 105686"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145901519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding life: A detailed examination of program collection","authors":"Jun Cao","doi":"10.1016/j.biosystems.2026.105693","DOIUrl":"10.1016/j.biosystems.2026.105693","url":null,"abstract":"<div><div>This article introduces the theory that “life is a collection of programs”. According to this theory, life constitutes a complex system composed of genetic information, metabolic regulation, developmental differentiation, and neurocognitive programs. These components operate in an orderly manner through initiation, execution, feedback, and repair mechanisms. Philosophically, ancient Greek atomism, the Yin-Yang Five Elements theory, and Hegelian dialectics provide support for the structural and dynamic properties of this theory. Scientifically, cell theory, genetics, and synthetic biology have validated its material basis. Specifically, genetic programs regulate traits through DNA, metabolic programs maintain homeostasis through enzymes and signaling pathways, developmental programs rely on gene networks to shape biological structures, and neural programs achieve cognition through neuronal signals. While this theory breaks through the traditional perspectives on life, it also faces challenges such as the “hard problem of consciousness” and ethical controversies. Looking ahead, integrating single-cell omics and artificial intelligence modeling is essential to deepen research and construct a robust ethical framework. This theory provides an interdisciplinary paradigm for life sciences and promotes the advancement of medicine and biotechnology.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"260 ","pages":"Article 105693"},"PeriodicalIF":1.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145919062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}