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  1. Article ; Online: On the feasibility of dynamical analysis of network models of biochemical regulation.

    Rocha, Luis M

    Bioinformatics (Oxford, England)

    2022  Volume 38, Issue 14, Page(s) 3674–3675

    MeSH term(s) Feasibility Studies ; Models, Biological
    Language English
    Publishing date 2022-02-28
    Publishing country England
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural ; Comment
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btac360
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  2. Article ; Online: Dynamical Modularity in Automata Models of Biochemical Networks.

    Parmer, Thomas / Rocha, Luis M

    ArXiv

    2023  

    Abstract: Given the large size and complexity of most biochemical regulation and signaling networks, there is a non-trivial relationship between the micro-level logic of component interactions and the observed macro-dynamics. Here we address this issue by ... ...

    Abstract Given the large size and complexity of most biochemical regulation and signaling networks, there is a non-trivial relationship between the micro-level logic of component interactions and the observed macro-dynamics. Here we address this issue by formalizing the concept of pathway modules developed by
    Language English
    Publishing date 2023-04-17
    Publishing country United States
    Document type Preprint
    ISSN 2331-8422
    ISSN (online) 2331-8422
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  3. Article ; Online: Bursts of communication increase opinion diversity in the temporal Deffuant model.

    Zarei, Fatemeh / Gandica, Yerali / Rocha, Luis E C

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 2222

    Abstract: Human interactions create social networks forming the backbone of societies. Individuals adjust their opinions by exchanging information through social interactions. Two recurrent questions are whether social structures promote opinion polarisation or ... ...

    Abstract Human interactions create social networks forming the backbone of societies. Individuals adjust their opinions by exchanging information through social interactions. Two recurrent questions are whether social structures promote opinion polarisation or consensus and whether polarisation can be avoided, particularly on social media. In this paper, we hypothesise that not only network structure but also the timings of social interactions regulate the emergence of opinion clusters. We devise a temporal version of the Deffuant opinion model where pairwise social interactions follow temporal patterns. Individuals may self-organise into a multi-partisan society due to network clustering promoting the reinforcement of local opinions. Burstiness has a similar effect and is alone sufficient to refrain the population from consensus and polarisation by also promoting the reinforcement of local opinions. The diversity of opinions in socially clustered networks thus increases with burstiness, particularly, and counter-intuitively, when individuals have low tolerance and prefer to adjust to similar peers. The emergent opinion landscape is well-balanced regarding groups' size, with relatively short differences between groups, and a small fraction of extremists. We argue that polarisation is more likely to emerge in social media than offline social networks because of the relatively low social clustering observed online, despite the observed online burstiness being sufficient to promote more diversity than would be expected offline. Increasing the variance of burst activation times, e.g. by being less active on social media, could be a venue to reduce polarisation. Furthermore, strengthening online social networks by increasing social redundancy, i.e. triangles, may also promote diversity.
    MeSH term(s) Humans ; Attitude ; Social Networking ; Consensus ; Social Media
    Language English
    Publishing date 2024-01-26
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-52458-w
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  4. Book ; Online: On the feasibility of dynamical analysis of network models of biochemical regulation

    Rocha, Luis M.

    2021  

    Abstract: A recent article by Weidner et al. [2021] presents a method to extract graph properties that are predictive of the dynamical behavior of multivariate, discrete models of biochemical regulation. In other words, a method that uses only features from the ... ...

    Abstract A recent article by Weidner et al. [2021] presents a method to extract graph properties that are predictive of the dynamical behavior of multivariate, discrete models of biochemical regulation. In other words, a method that uses only features from the structure of network interactions to predict which nodes are most involved in automata network dynamics. However, the authors claim that dynamical analysis of large automata network models is "not even feasible." To make sure that others are not discouraged from working on this problem, it is important to clarify that effective dynamical analysis of automata network models, to the contrary, is feasible. Unlike what is suggested in the article, graph-based analysis of static features is not the only analytical avenue for large systems biology models of regulation and signaling dynamics because there are dynamical methods that are, indeed, scalable.
    Keywords Quantitative Biology - Quantitative Methods ; Nonlinear Sciences - Cellular Automata and Lattice Gases ; Quantitative Biology - Molecular Networks
    Subject code 000
    Publishing date 2021-10-20
    Publishing country us
    Document type Book ; Online
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  5. Article ; Online: Validation of the natural sedimentation technique in the diagnosis of chronic fasciolosis.

    Rojas-Moncada, Juan / Torrel-Pajares, Téofilo / Vargas-Rocha, Luis

    Parasitology international

    2024  Volume 101, Page(s) 102889

    Abstract: There are various diagnostic techniques available for chronic fasciolosis in ruminants. However, many of them exhibit low specificity and sensitivity, making them impractical for field use and in low-resource laboratories. The present study evaluates the ...

    Abstract There are various diagnostic techniques available for chronic fasciolosis in ruminants. However, many of them exhibit low specificity and sensitivity, making them impractical for field use and in low-resource laboratories. The present study evaluates the usefulness of the Natural Sedimentation technique in diagnosing chronic fasciolosis in three domestic species conducted at the Laboratorio de Parasitología y Enfermedades Parasitarias, Facultad de Ciencias Veterinas, Universidad Nacional de Cajamarca. Fecal samples were collected from n = 323 cattle, n = 362 sheep, and n = 231 swine for Fasciola hepatica fecal egg counts. The visualization of adult parasites in animal livers post-mortem was considered the gold standard. Additionally, the sensitivity of the technique was evaluated using five different amounts of feces. In cattle, a sensitivity of 0.93 ± 0.03, specificity of 0.91 ± 0.06, positive predictive value of 0.96 ± 0.03, and negative predictive value of 0.86 ± 0.07 were obtained. In sheep, a sensitivity of 0.79 ± 0.05, specificity of 0.83 ± 0.07, positive predictive value of 0.90 ± 0.04, and negative predictive value of 0.66 ± 0.08 were observed. In swine, a sensitivity of 0.92 ± 0.06, specificity of 1.00 ± 0.00, positive predictive value of 1.00 ± 0.00, and negative predictive value of 0.96 ± 0.03 were found. There was no statistical difference in egg counts when using 1, 2, 3, 4, and 5 g of feces (p = 0.907). Furthermore, 1 to 688 fecal eggs of F. hepatica were counted in 1 g of feces. The Natural Sedimentation technique has both qualitative and quantitative applications with satisfactory results when using 1 g of feces in the diagnosis of chronic fasciolosis in domestic animals. Due to its simplicity, it can be implemented in field conditions and low-resource laboratories.
    Language English
    Publishing date 2024-03-24
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1363151-2
    ISSN 1873-0329 ; 1383-5769
    ISSN (online) 1873-0329
    ISSN 1383-5769
    DOI 10.1016/j.parint.2024.102889
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    Zs.B 2322: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  6. Book ; Online: Dynamical Modularity in Automata Models of Biochemical Networks

    Parmer, Thomas / Rocha, Luis M.

    2023  

    Abstract: Given the large size and complexity of most biochemical regulation and signaling networks, there is a non-trivial relationship between the micro-level logic of component interactions and the observed macro-dynamics. Here we address this issue by ... ...

    Abstract Given the large size and complexity of most biochemical regulation and signaling networks, there is a non-trivial relationship between the micro-level logic of component interactions and the observed macro-dynamics. Here we address this issue by formalizing the existing concept of pathway modules, which are sequences of state updates that are guaranteed to occur (barring outside interference) in the dynamics of automata networks after the perturbation of a subset of driver nodes. We present a novel algorithm to automatically extract pathway modules from networks and we characterize the interactions that may take place between modules. This methodology uses only the causal logic of individual node variables (micro-dynamics) without the need to compute the dynamical landscape of the networks (macro-dynamics). Specifically, we identify complex modules, which maximize pathway length and require synergy between their components. This allows us to propose a new take on dynamical modularity that partitions complex networks into causal pathways of variables that are guaranteed to transition to specific states given a perturbation to a set of driver nodes. Thus, the same node variable can take part in distinct modules depending on the state it takes. Our measure of dynamical modularity of a network is then inversely proportional to the overlap among complex modules and maximal when complex modules are completely decouplable from one another in the network dynamics. We estimate dynamical modularity for several genetic regulatory networks, including the Drosophila melanogaster segment-polarity network. We discuss how identifying complex modules and the dynamical modularity portrait of networks explains the macro-dynamics of biological networks, such as uncovering the (more or less) decouplable building blocks of emergent computation (or collective behavior) in biochemical regulation and signaling.

    Comment: 42 pages, 7 figures; updated author information
    Keywords Quantitative Biology - Molecular Networks ; Computer Science - Computational Engineering ; Finance ; and Science
    Subject code 006
    Publishing date 2023-03-28
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: The distance backbone of directed networks.

    Costa, Felipe Xavier / Correia, Rion Brattig / Rocha, Luis M

    Complex networks and their applications XI : proceedings of the eleventh International Conference on Complex Networks and their Applications: Complex Networks 2022. Volume 2

    2023  Volume 1078, Page(s) 135–147

    Abstract: In weighted graphs the shortest path between two nodes is often reached through an indirect path, out of all possible connections, leading to structural redundancies which play key roles in the dynamics and evolution of complex networks. We have ... ...

    Abstract In weighted graphs the shortest path between two nodes is often reached through an indirect path, out of all possible connections, leading to structural redundancies which play key roles in the dynamics and evolution of complex networks. We have previously developed a parameter-free, algebraically-principled methodology to uncover such redundancy and reveal the distance backbone of weighted graphs, which has been shown to be important in transmission dynamics, inference of important paths, and quantifying the robustness of networks. However, the method was developed for undirected graphs. Here we expand this methodology to weighted directed graphs and study the redundancy and robustness found in nine networks ranging from social, biomedical, and technical systems. We found that similarly to undirected graphs, directed graphs in general also contain a large amount of redundancy, as measured by the size of their (directed) distance backbone. Our methodology adds an additional tool to the principled sparsification of complex networks and the measure of their robustness.
    Language English
    Publishing date 2023-01-26
    Publishing country Switzerland
    Document type Journal Article
    DOI 10.1007/978-3-031-21131-7_11
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  8. Article ; Online: Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs.

    Brattig Correia, Rion / Barrat, Alain / Rocha, Luis M

    PLoS computational biology

    2023  Volume 19, Issue 2, Page(s) e1010854

    Abstract: The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, ... ...

    Abstract The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, but a precise characterization of the redundancy present in social networks and its effect on the robustness of transmission is still lacking. This gap is addressed by the metric backbone, a weight- and connectivity-preserving subgraph that is sufficient to compute all shortest paths of weighted graphs. This subgraph is obtained via algebraically-principled axioms and does not require statistical sampling based on null-models. We show that the metric backbones of nine contact networks obtained from proximity sensors in a variety of social contexts are generally very small, 49% of the original graph for one and ranging from about 6% to 20% for the others. This reflects a surprising amount of redundancy and reveals that shortest paths on these networks are very robust to random attacks and failures. We also show that the metric backbone preserves the full distribution of shortest paths of the original contact networks-which must include the shortest inter- and intra-community distances that define any community structure-and is a primary subgraph for epidemic transmission based on pure diffusion processes. This suggests that the organization of social contact networks is based on large amounts of shortest-path redundancy which shapes epidemic spread in human populations. Thus, the metric backbone is an important subgraph with regard to epidemic spread, the robustness of social networks, and any communication dynamics that depend on complex network shortest paths.
    MeSH term(s) Humans ; Communicable Diseases/epidemiology ; Social Networking ; Epidemics ; Communication
    Language English
    Publishing date 2023-02-23
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1010854
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  9. Article ; Online: Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Automata Networks.

    Costa, Felipe Xavier / Rozum, Jordan C / Marcus, Austin M / Rocha, Luis M

    Entropy (Basel, Switzerland)

    2023  Volume 25, Issue 2

    Abstract: Biomolecular network dynamics are thought to operate near the critical boundary between ordered and disordered regimes, where large perturbations to a small set of elements neither die out nor spread on average. A biomolecular automaton (e.g., gene, ... ...

    Abstract Biomolecular network dynamics are thought to operate near the critical boundary between ordered and disordered regimes, where large perturbations to a small set of elements neither die out nor spread on average. A biomolecular automaton (e.g., gene, protein) typically has high regulatory redundancy, where small subsets of regulators determine activation via collective canalization. Previous work has shown that effective connectivity, a measure of collective canalization, leads to improved dynamical regime prediction for homogeneous automata networks. We expand this by (i) studying random Boolean networks (RBNs) with heterogeneous in-degree distributions, (ii) considering additional experimentally validated automata network models of biomolecular processes, and (iii) considering new measures of heterogeneity in automata network logic. We found that effective connectivity improves dynamical regime prediction in the models considered; in RBNs, combining effective connectivity with bias entropy further improves the prediction. Our work yields a new understanding of criticality in biomolecular networks that accounts for collective canalization, redundancy, and heterogeneity in the connectivity and logic of their automata models. The strong link we demonstrate between criticality and regulatory redundancy provides a means to modulate the dynamical regime of biochemical networks.
    Language English
    Publishing date 2023-02-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2014734-X
    ISSN 1099-4300 ; 1099-4300
    ISSN (online) 1099-4300
    ISSN 1099-4300
    DOI 10.3390/e25020374
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  10. Article: Exploring Suspected Diagnoses in Elderly Patients: A Case Study of Potential Necrotizing Otitis Externa.

    Rocha, Luís A / Costa, Tiago / Silva, Luciana / Veríssimo, Rafaela

    Cureus

    2023  Volume 15, Issue 12, Page(s) e49801

    Abstract: Necrotizing otitis externa (NOE) is a rare invasive infection affecting the EAC and the base of the skull. This condition is more prevalent in the elderly, diabetics, and immunocompromised individuals, often attributed to the ... ...

    Abstract Necrotizing otitis externa (NOE) is a rare invasive infection affecting the EAC and the base of the skull. This condition is more prevalent in the elderly, diabetics, and immunocompromised individuals, often attributed to the bacterium
    Language English
    Publishing date 2023-12-01
    Publishing country United States
    Document type Case Reports
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.49801
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