Latest recommendations
Id | Title * | Authors * | Abstract * ▼ | Picture * | Thematic fields * | Recommender | Reviewers | Submission date | |
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08 Nov 2024
Bayesian joint-regression analysis of unbalanced series of on-farm trialsMichel Turbet Delof , Pierre Rivière , Julie C Dawson, Arnaud Gauffreteau , Isabelle Goldringer , Gaëlle van Frank , Olivier David https://hal.science/hal-04380787Handling Data Imbalance and G×E Interactions in On-Farm Trials Using Bayesian Hierarchical ModelsRecommended by Sophie Donnet based on reviews by Pierre Druilhet and David MakowskiThe article, "Bayesian Joint-Regression Analysis of Unbalanced Series of On-Farm Trials," presents a Bayesian statistical framework tailored for analyzing highly unbalanced datasets from participatory plant breeding (PPB) trials, specifically wheat trials. The key goal of this research is to address the challenges of genotype-environment (G×E) interactions in on-farm trials, which often have limited replication and varied testing conditions across farms. The study applies a hierarchical Bayesian model with Finlay-Wilkinson regression, which improves the estimation of G×E effects despite substantial data imbalance. By incorporating a Student’s t-distribution for residuals, the model is more robust to extreme values, which are common in on-farm trials due to variable environments. Note that the model allows a detailed breakdown of variance, identifying environment effects as the most significant contributors, thus highlighting areas for future breeding focus. Using Hamiltonian Monte Carlo methods, the study achieves reasonable computation times, even for large datasets. Obviously, the limitation of the methods comes from the level of data balance and replication. The method requires a minimum level of data balance and replication, which can be a challenge in very decentralized breeding networks Moreover, the Bayesian framework, though computationally feasible, may still be complex for widespread adoption without computational resources or statistical expertise. The paper presents a sophisticated Bayesian framework specifically designed to tackle the challenges of unbalanced data in participatory plant breeding (PPB). It showcases a novel way to manage the variability in on-farm trials, a common issue in decentralized breeding programs. This study's methods accommodate the inconsistencies inherent in on-farm trials, such as extreme values and minimal replication. By using a hierarchical Bayesian approach with a Student’s t-distribution for robustness, it provides a model that maintains precision despite these real-world challenges. This makes it especially relevant for those working in unpredictable agricultural settings or decentralized trials. From a more general perspective, this paper’s findings support breeding methods that prioritize specific adaptation to local conditions. It is particularly useful for researchers and practitioners interested in breeding for agroecological or organic farming systems, where G×E interactions are critical but hard to capture in traditional trial setups. Beyond agriculture, the paper serves as an excellent example of advanced statistical modeling in highly variable datasets. Its applications extend to any field where data is incomplete or irregular, offering a clear case for hierarchical Bayesian methods to achieve reliable results. Finally, although begin quite methodological, the paper provides practical insights into how breeders and researchers can work with farmers to achieve meaningful varietal evaluations. References Michel Turbet Delof , Pierre Rivière , Julie C Dawson, Arnaud Gauffreteau , Isabelle Goldringer , Gaëlle van Frank , Olivier David (2024) Bayesian joint-regression analysis of unbalanced series of on-farm trials. HAL, ver.2 peer-reviewed and recommended by PCI Math Comp Biol https://hal.science/hal-04380787 | Bayesian joint-regression analysis of unbalanced series of on-farm trials | Michel Turbet Delof , Pierre Rivière , Julie C Dawson, Arnaud Gauffreteau , Isabelle Goldringer , Gaëlle van Frank , Olivier David | <p>Participatory plant breeding (PPB) is aimed at developing varieties adapted to agroecologically-based systems. In PPB, selection is decentralized in the target environments, and relies on collaboration between farmers, farmers' organisations an... | Agricultural Science, Genetics and population Genetics, Probability and statistics | Sophie Donnet | Pierre Druilhet, David Makowski | 2024-01-11 14:17:41 | View | |
24 Dec 2020
A linear time solution to the Labeled Robinson-Foulds Distance problemSamuel Briand, Christophe Dessimoz, Nadia El-Mabrouk and Yannis Nevers https://doi.org/10.1101/2020.09.14.293522Comparing reconciled gene trees in linear timeRecommended by Céline Scornavacca based on reviews by Barbara Holland, Gabriel Cardona, Jean-Baka Domelevo Entfellner and 1 anonymous reviewerUnlike a species tree, a gene tree results not only from speciation events, but also from events acting at the gene level, such as duplications and losses of gene copies, and gene transfer events [1]. The reconciliation of phylogenetic trees consists in embedding a given gene tree into a known species tree and, doing so, determining the location of these gene-level events on the gene tree [2]. Reconciled gene trees can be seen as phylogenetic trees where internal node labels are used to discriminate between different gene-level events. Comparing them is of foremost importance in order to assess the performance of various reconciliation methods (e.g. [3]). References [1] Maddison, W. P. (1997). Gene trees in species trees. Systematic biology, 46(3), 523-536. doi: https://doi.org/10.1093/sysbio/46.3.523 | A linear time solution to the Labeled Robinson-Foulds Distance problem | Samuel Briand, Christophe Dessimoz, Nadia El-Mabrouk and Yannis Nevers | <p>Motivation Comparing trees is a basic task for many purposes, and especially in phylogeny where different tree reconstruction tools may lead to different trees, likely representing contradictory evolutionary information. While a large variety o... | Combinatorics, Design and analysis of algorithms, Evolutionary Biology | Céline Scornavacca | 2020-08-20 21:06:23 | View | ||
02 Oct 2024
HairSplitter: haplotype assembly from long, noisy readsRoland Faure, Dominique Lavenier, Jean-François Flot https://doi.org/10.1101/2024.02.13.580067Accurate Haplotype Reconstruction from Long, Error-Prone, Reads with HairSplitterRecommended by Giulio Ermanno Pibiri based on reviews by Dmitry Antipov and 1 anonymous reviewerA prominent challenge in computational biology is to distinguish microbial haplotypes -- closely related organisms with highly similar genomes -- due to small genomic differences that can cause significant phenotypic variations. Current genome assembly tools struggle with distinguishing these haplotypes, especially for long-read sequencing data with high error rates, such as PacBio or Oxford Nanopore Technology (ONT) reads. While existing methods work well for either viral or bacterial haplotypes, they often fail with low-abundance haplotypes and are computationally intensive. This work by Faure, Lavenier, and Flot [1] introduces a new tool -- HairSplitter -- that offers a solution for both viral and bacterial haplotype separation, even with error-prone long reads. It does this by efficiently calling variants, clustering reads into haplotypes, creating new separated contigs, and resolving the assembly graph. A key advantage of HairSplitter is that it is entirely parameter-free and does not require prior knowledge of the organism's ploidy. HairSplitter is designed to handle both metaviromes and bacterial metagenomes, offering a more versatile and efficient solution than existing tools, like stRainy [2], Strainberry [3], and hifiasm-meta [4]. References [1] Roland Faure, Dominique Lavenier, Jean-François Flot (2024) HairSplitter: haplotype assembly from long, noisy reads. bioRxiv, ver.3 peer-reviewed and recommended by PCI Math Comp Biol https://doi.org/10.1101/2024.02.13.580067 [2] Kazantseva E, A Donmez, M Pop, and M Kolmogorov (2023). stRainy: assembly-based metagenomic strain phasing using long reads. Bioinformatics. https://doi.org/10.1101/2023.01.31.526521 [3] Vicedomini R, C Quince, AE Darling, and R Chikhi (2021). Strainberry: automated strain separation in low complexity metagenomes using long reads. Nature Communications, 12, 4485. ISSN: 2041-1723. https://doi.org/10.1038/s41467-021-24515-9 [4] Feng X, H Cheng, D Portik, and H Li (2022). Metagenome assembly of high-fidelity long reads with hifiasm-meta. Nature Methods, 19, 1–4. https://doi.org/10.1038/s41592-022-01478-3 | HairSplitter: haplotype assembly from long, noisy reads | Roland Faure, Dominique Lavenier, Jean-François Flot | <p>Long-read assemblers face challenges in discerning closely related viral or<br>bacterial strains, often collapsing similar strains in a single sequence. This limitation has<br>been hampering metagenome analysis, where diverse strains may harbor... | Design and analysis of algorithms, Development, Genomics and Transcriptomics, Probability and statistics | Giulio Ermanno Pibiri | 2024-02-15 10:17:04 | View | ||
10 Jan 2024
An approximate likelihood method reveals ancient gene flow between human, chimpanzee and gorillaNicolas Galtier https://doi.org/10.1101/2023.07.06.547897Aphid: A Novel Statistical Method for Dissecting Gene Flow and Lineage Sorting in Phylogenetic ConflictRecommended by Alan Rogers based on reviews by Richard Durbin and 2 anonymous reviewersGaltier [1] introduces “Aphid,” a new statistical method that estimates the contributions of gene flow (GF) and incomplete lineage sorting (ILS) to phylogenetic conflict. Aphid is based on the observation that GF tends to make gene genealogies shorter, whereas ILS makes them longer. Rather than fitting the full likelihood, it models the distribution of gene genealogies as a mixture of several canonical gene genealogies in which coalescence times are set equal to their expectations under different models. This simplification makes Aphid far faster than competing methods. In addition, it deals gracefully with bidirectional gene flow—an impossibility under competing models. Because of these advantages, Aphid represents an important addition to the toolkit of evolutionary genetics. In the interest of speed, Aphid makes several simplifying assumptions. Yet even when these were violated, Aphid did well at estimating parameters from simulated data. It seems to be reasonably robust. Aphid studies phylogenetic conflict, which occurs when some loci imply one phylogenetic tree and other loci imply another. This happens when the interval between successive speciation events is fairly short. If this interval is too short, however, Aphid’s approximations break down, and its estimates are biased. Galtier suggests caution when the fraction of discordant phylogenetic trees exceeds 50–55%. Thus, Aphids will be most useful when the interval between speciation events is short, but not too short. Galtier applies the new method to three sets of primate data. In two of these data sets (baboons and African apes), Aphid detects gene flow that would likely be missed by competing methods. These competing methods are primarily sensitive to gene flow that is asymmetric in two senses: (1) greater flow in one direction than the other, and (2) unequal gene flow connecting an outgroup to two sister species. Aphid finds evidence of symmetric gene flow in the ancestry of baboons and also in that of African apes. The data suggest that ancestral humans and chimpanzees both interbred with ancestral gorillas, and at about the same rate. Aphid’s ability to detect this signature sets it apart from competing methods. References [1] Nicolas Galtier (2023) “An approximate likelihood method reveals ancient gene flow between human, chimpanzee and gorilla”. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Mathematical and Computational Biology. https://doi.org/10.1101/2023.07.06.547897 | An approximate likelihood method reveals ancient gene flow between human, chimpanzee and gorilla | Nicolas Galtier | <p>Gene flow and incomplete lineage sorting are two distinct sources of phylogenetic conflict, i.e., gene trees that differ in topology from each other and from the species tree. Distinguishing between the two processes is a key objective of curre... | Evolutionary Biology, Genetics and population Genetics, Genomics and Transcriptomics | Alan Rogers | 2023-07-06 18:41:16 | View | ||
26 Feb 2024
A workflow for processing global datasets: application to intercroppingRémi Mahmoud, Pierre Casadebaig, Nadine Hilgert, Noémie Gaudio https://hal.science/hal-04145269Collecting, assembling and sharing data in crop sciencesRecommended by Eric Tannier based on reviews by Christine Dillmann and 2 anonymous reviewersIt is often the case that scientific knowledge exists but is scattered across numerous experimental studies. Because of this dispersion in different formats, it remains difficult to access, extract, reproduce, confirm or generalise. This is the case in crop science, where Mahmoud et al [1] propose to collect and assemble data from numerous field experiments on intercropping. It happens that the construction of the global dataset requires a lot of time, attention and a well thought-out method, inspired by the literature on data science [2] and adapted to the specificities of crop science. This activity also leads to new possibilities that were not available in individual datasets, such as the detection of full factorial designs using graph theory tools developed on top of the global dataset. The study by Mahmoud et al [1] has thus multiple dimensions:
I was particularly interested in the promotion of the FAIR principles, perhaps used a little too uncritically in my view, as an obvious solution to data sharing. On the one hand, I am admiring and grateful for the availability of these data, some of which have never been published, nor associated with published results. This approach is likely to unearth buried treasures. On the other hand, I can understand the reluctance of some data producers to commit to total, definitive sharing, facilitating automatic reading, without having thought about a certain reciprocity on the part of users and use by artificial intelligence. Reciprocity in terms of recognition, as is discussed by Mahmoud et al [1], but also in terms of contribution to the commons [5] or reading conditions for machine learning. References [1] Mahmoud R., Casadebaig P., Hilgert N., Gaudio N. A workflow for processing global datasets: application to intercropping. 2024. ⟨hal-04145269v2⟩ ver. 2 peer-reviewed and recommended by Peer Community in Mathematical and Computational Biology. https://hal.science/hal-04145269 [2] Wickham, H. 2014. Tidy data. Journal of Statistical Software 59(10) https://doi.org/10.18637/jss.v059.i10 [3] Gaudio, N., R. Mahmoud, L. Bedoussac, E. Justes, E.-P. Journet, et al. 2023. A global dataset gathering 37 field experiments involving cereal-legume intercrops and their corresponding sole crops. https://doi.org/10.5281/zenodo.8081577 [4] Mahmoud, R., Casadebaig, P., Hilgert, N. et al. Species choice and N fertilization influence yield gains through complementarity and selection effects in cereal-legume intercrops. Agron. Sustain. Dev. 42, 12 (2022). https://doi.org/10.1007/s13593-022-00754-y [5] Bernault, C. « Licences réciproques » et droit d'auteur : l'économie collaborative au service des biens communs ?. Mélanges en l'honneur de François Collart Dutilleul, Dalloz, pp.91-102, 2017, 978-2-247-17057-9. https://shs.hal.science/halshs-01562241 | A workflow for processing global datasets: application to intercropping | Rémi Mahmoud, Pierre Casadebaig, Nadine Hilgert, Noémie Gaudio | <p>Field experiments are a key source of data and knowledge in agricultural research. An emerging practice is to compile the measurements and results of these experiments (rather than the results of publications, as in meta-analysis) into global d... | Agricultural Science | Eric Tannier | 2023-06-29 15:38:28 | View | ||
28 Jun 2024
Emergence of Supercoiling-Mediated Regulatory Networks through the Evolution of Bacterial Chromosome OrganizationThéotime Grohens, Sam Meyer, Guillaume Beslon https://doi.org/10.1101/2022.09.23.509185Understanding the impact of the transcription-supercoiling coupling on bacterial genome evolutionRecommended by Nelle Varoquaux based on reviews by Ivan Junier and 1 anonymous reviewerDNA supercoiling, the under or overwinding of DNA, is known to strongly impact gene expression, as changes in levels of supercoiling directly influence transcription rates. In turn, gene transcription generates DNA supercoiling on each side of an advancing RNA polymerase. This coupling between DNA supercoiling and transcription may result in different outcomes, depending on neighboring gene orientations: divergent genes tend to increase transcription levels, convergent genes tend to inhibit each other, while tandem genes may exhibit more intricate relationships. While several works have investigated the relationship between transcription and supercoiling, Grohens et al [1] address a different question: how does transcription-supercoiling coupling drive genome evolution? To this end, they consider a simple model of gene expression regulation where transcription level only depends on the local DNA supercoiling and where the transcription of one gene generates a linear profile of positive and negative DNA supercoiling on each side of it. They then make genomes evolve through genomic inversions only considering a fitness that reflects the ability of a genome to cope with two distinct environments for which different genes have to be activated or repressed. Using this simple model, the authors illustrate how evolutionary adaptation via genomic inversions can adjust expression levels for enhanced fitness within specific environments, particularly with the emergence of relaxation-activated genes. Investigating the genomic organization of individual genomes revealed that genes are locally organized to leverage the transcription-supercoiling coupling for activation or inhibition, but larger-scale networks of genes are required to strongly inhibit genes (sometimes up to networks of 20 genes). Thus, supercoiling-mediated interactions between genes can implicate more than just local genes. Finally, they construct an "effective interaction graph" between genes by successively simulating gene knock-outs for all of the genes of an individual and observing the effect on the expression level of other genes. They observe a densely connected interaction network, implying that supercoiling-based regulation could evolve concurrently with genome organization in bacterial genomes. References [1] Théotime Grohens, Sam Meyer, Guillaume Beslon (2024) Emergence of Supercoiling-Mediated Regulatory Networks through the Evolution of Bacterial Chromosome Organization. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Mathematical and Computational Biology https://doi.org/10.1101/2022.09.23.509185 | Emergence of Supercoiling-Mediated Regulatory Networks through the Evolution of Bacterial Chromosome Organization | Théotime Grohens, Sam Meyer, Guillaume Beslon | <p>DNA supercoiling -- the level of twisting and writhing of the DNA molecule around itself -- plays a major role in the regulation of gene expression in bacteria by modulating promoter activity. The level of DNA supercoiling is a dynamic property... | Biophysics, Evolutionary Biology, Systems biology | Nelle Varoquaux | 2023-06-30 10:34:28 | View | ||
27 Sep 2024
In silico identification of switching nodes in metabolic networksFrancis Mairet https://doi.org/10.1101/2023.05.17.541195A computational method to identify key players in metabolic rewiringRecommended by Claudine Chaouiya based on reviews by 2 anonymous reviewersSignificant progress has been made in developing computational methods to tackle the analysis of the numerous (genome-wide scale) metabolic networks that have been documented for a wide range of species. Understanding the behaviours of these complex reaction networks is crucial in various domains such as biotechnology and medicine. Metabolic rewiring is essential as it enables cells to adapt their metabolism to changing environmental conditions. Identifying the metabolites around which metabolic rewiring occurs is certainly useful in the case of metabolic engineering, which relies on metabolic rewiring to transform micro-organisms into cellular factories [1], as well as in other contexts. This paper by F. Mairet [2] introduces a method to disclose these metabolites, named switch nodes, relying on the analysis of the flux distributions for different input conditions. Basically, considering fluxes for different inputs, which can be computed using e.g. Parsimonious Flux Balance Analysis (pFBA), the proposed method consists in identifying metabolites involved in reactions whose different flux vectors are not collinear. The approach is supported by four case studies, considering core and genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae and the diatom Phaeodactylum tricornutum. Whilst identified switch nodes may be biased because computed flux vectors satisfying given objectives are not necessarily unique, the proposed method has still a relevant predictive potential, complementing the current array of computational methods to study metabolism. References [1] Tao Yu, Yasaman Dabirian, Quanli Liu, Verena Siewers, Jens Nielsen (2019) Strategies and challenges for metabolic rewiring. Current Opinion in Systems Biology, Vol 15, pp 30-38. https://doi.org/10.1016/j.coisb.2019.03.004. [2] Francis Mairet (2024) In silico identification of switching nodes in metabolic networks. bioRxiv, ver.3 peer-reviewed and recommended by PCI Math Comp Biol https://doi.org/10.1101/2023.05.17.541195 | In silico identification of switching nodes in metabolic networks | Francis Mairet | <p>Cells modulate their metabolism according to environmental conditions. A major challenge to better understand metabolic regulation is to identify, from the hundreds or thousands of molecules, the key metabolites where the re-orientation of flux... | Graph theory, Physiology, Systems biology | Claudine Chaouiya | Anonymous | 2023-05-26 17:24:26 | View | |
07 Sep 2021
The origin of the allometric scaling of lung ventilation in mammalsFrédérique Noël, Cyril Karamaoun, Jerome A. Dempsey, Benjamin Mauroy https://doi.org/10.48550/arXiv.2005.12362How mammals adapt their breath to body activity – and how this depends on body sizeRecommended by Wolfram Liebermeister based on reviews by Elad Noor, Oliver Ebenhöh, Stefan Schuster and Megumi InoueHow fast and how deep do animals breathe, and how does this depend on how active they are? To answer this question, one needs to dig deeply into how breathing works and what biophysical processes it involves. And one needs to think about body size. It is impressive how nature adapts the same body plan – e.g. the skeletal structure of mammals – to various shapes and sizes. From mice to whales, also the functioning of most organs remains the same; they are just differently scaled. Scaling does not just mean “making bigger or smaller”. As already noted by Galilei, body shapes change as they are adapted to body dimensions, and the same holds for physiological variables. Many such variables, for instance, heartbeat rates, follow scaling laws of the form y~x^a, where x denotes body mass and the exponent a is typically a multiple of ¼ [1]. These unusual exponents – instead of multiples of ⅓, which would be expected from simple geometrical scaling – are why these laws are called “allometric”. Kleiber’s law for metabolic rates, with a scaling exponent of ¾, is a classic example [2]. As shown by G. West, allometric laws can be explained through a few simple steps [1]. In his models, he focused on network-like organs such as the vascular system and assumed that these systems show a self-similar structure, with a fixed minimal unit (for instance, capillaries) but varying numbers of hierarchy levels depending on body size. To determine the flow through such networks, he employed biophysical models and optimality principles (for instance, assuming that oxygen must be transported at a minimal mechanical effort), and showed that the solutions – and the physiological variables – respect the known scaling relations. The paper “The origin of the allometric scaling of lung ventilation in mammals“ by Noël et al. [3], applies this thinking to the depth and rate of breathing in mammals. Scaling laws describing breathing in resting animals have been known since the 1950s [4], with exponents of 1 (for tidal volume) and -¼ (for breathing frequency). Equipped with a detailed biophysical model, Noël et al. revisit this question, extending these laws to other metabolic regimes. Their starting point is a model of the human lung, developed previously by two of the authors [5], which assumes that we meet our oxygen demand with minimal lung movements. To state this as an optimization problem, the model combines two submodels: a mechanical model describing the energetic effort of ventilation and a highly detailed model of convection and diffusion in self-similar lung geometries. Breathing depths and rates are computed by numerical optimization, and to obtain results for mammals of any size many of the model parameters are described by known scaling laws. As expected, the depth of breathing (measured by tidal volume) scales almost proportionally with body mass and increases with metabolic demand, while the breathing rate decreases with body mass, with an exponent of about -¼. However, the laws for the breathing rate hold only for basal activity; at higher metabolic rates, which are modeled here for the first time, the exponent deviates strongly from this value, in line with empirical data. Why is this paper important? The authors present a highly complex model of lung physiology that integrates a wide range of biophysical details and passes a difficult test: the successful prediction of unexplained scaling exponents. These scaling relations may help us transfer insights from animal models to humans and in reverse: data for breathing during exercise, which are easy to measure in humans, can be extrapolated to other species. Aside from the scaling laws, the model also reveals physiological mechanisms. In the larger lung branches, oxygen is transported mainly by air movement (convection), while in smaller branches air flow is slow and oxygen moves by diffusion. The transition between these regimes can occur at different depths in the lung: as the authors state, “the localization of this transition determines how ventilation should be controlled to minimize its energetic cost at any metabolic regime”. In the model, the optimal location for the transition depends on oxygen demand [5, 6]: the transition occurs deeper in the lung in exercise regimes than at rest, allowing for more oxygen to be taken up. However, the effects of this shift depend on body size: while small mammals generally use the entire exchange surface of their lungs, large mammals keep a reserve for higher activities, which becomes accessible as their transition zone moves at high metabolic rates. Hence, scaling can entail qualitative differences between species! Altogether, the paper shows how the dynamics of ventilation depend on lung morphology. But this may also play out in the other direction: if energy-efficient ventilation depends on body activity, and therefore on ecological niches, a niche may put evolutionary pressures on lung geometry. Hence, by understanding how deep and fast animals breathe, we may also learn about how behavior, physiology, and anatomy co-evolve. References [1] West GB, Brown JH, Enquist BJ (1997) A General Model for the Origin of Allometric Scaling Laws in Biology. Science 276 (5309), 122–126. https://doi.org/10.1126/science.276.5309.122 [2] Kleiber M (1947) Body size and metabolic rate. Physiological Reviews, 27, 511–541. https://doi.org/10.1152/physrev.1947.27.4.511 [3] Noël F., Karamaoun C., Dempsey J. A. and Mauroy B. (2021) The origin of the allometric scaling of lung's ventilation in mammals. arXiv, 2005.12362, ver. 6 peer-reviewed and recommended by Peer community in Mathematical and Computational Biology. https://arxiv.org/abs/2005.12362 [4] Otis AB, Fenn WO, Rahn H (1950) Mechanics of Breathing in Man. Journal of Applied Physiology, 2, 592–607. https://doi.org/10.1152/jappl.1950.2.11.592 [5] Noël F, Mauroy B (2019) Interplay Between Optimal Ventilation and Gas Transport in a Model of the Human Lung. Frontiers in Physiology, 10, 488. https://doi.org/10.3389/fphys.2019.00488 [6] Sapoval B, Filoche M, Weibel ER (2002) Smaller is better—but not too small: A physical scale for the design of the mammalian pulmonary acinus. Proceedings of the National Academy of Sciences, 99, 10411–10416. https://doi.org/10.1073/pnas.122352499 | The origin of the allometric scaling of lung ventilation in mammals | Frédérique Noël, Cyril Karamaoun, Jerome A. Dempsey, Benjamin Mauroy | <p>A model of optimal control of ventilation has recently been developed for humans. This model highlights the importance of the localization of the transition between a convective and a diffusive transport of respiratory gas. This localization de... | Biophysics, Evolutionary Biology, Physiology | Wolfram Liebermeister | 2020-08-28 15:18:03 | View |
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