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Journal articles on the topic 'Coevolutionary domains'

Author: Grafiati

Published: 14 March 2023

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1

Krepel, Dana, Ryan R. Cheng, Michele Di Pierro, and José N. Onuchic. "Deciphering the structure of the condensin protein complex." Proceedings of the National Academy of Sciences 115, no. 47 (2018): 11911–16. http://dx.doi.org/10.1073/pnas.1812770115.

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Protein assemblies consisting of structural maintenance of chromosomes (SMC) and kleisin subunits are essential for the process of chromosome segregation across all domains of life. Prokaryotic condensin belonging to this class of protein complexes is composed of a homodimer of SMC that associates with a kleisin protein subunit called ScpA. While limited structural data exist for the proteins that comprise the (SMC)–kleisin complex, the complete structure of the entire complex remains unknown. Using an integrative approach combining both crystallographic data and coevolutionary information, we

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Croce, Giancarlo, Thomas Gueudré, Maria Virginia Ruiz Cuevas, et al. "A multi-scale coevolutionary approach to predict interactions between protein domains." PLOS Computational Biology 15, no. 10 (2019): e1006891. http://dx.doi.org/10.1371/journal.pcbi.1006891.

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Cartlidge, John, and Seth Bullock. "Combating Coevolutionary Disengagement by Reducing Parasite Virulence." Evolutionary Computation 12, no. 2 (2004): 193–222. http://dx.doi.org/10.1162/106365604773955148.

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While standard evolutionary algorithms employ a static, absolute fitness metric, co-evolutionary algorithms assess individuals by their performance relative to populations of opponents that are themselves evolving. Although this arrangement offers the possibility of avoiding long-standing difficulties such as premature convergence, it suffers from its own unique problems, cycling, over-focusing and disengagement. Here, we introduce a novel technique for dealing with the third and least explored of these problems. Inspired by studies of natural host-parasite systems, we show that disengagement

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Zheng, Wei, Xiaogen Zhou, Qiqige Wuyun, Robin Pearce, Yang Li, and Yang Zhang. "FUpred: detecting protein domains through deep-learning-based contact map prediction." Bioinformatics 36, no. 12 (2020): 3749–57. http://dx.doi.org/10.1093/bioinformatics/btaa217.

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Abstract Motivation Protein domains are subunits that can fold and function independently. Correct domain boundary assignment is thus a critical step toward accurate protein structure and function analyses. There is, however, no efficient algorithm available for accurate domain prediction from sequence. The problem is particularly challenging for proteins with discontinuous domains, which consist of domain segments that are separated along the sequence. Results We developed a new algorithm, FUpred, which predicts protein domain boundaries utilizing contact maps created by deep residual neural

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Xue, Xingsi, Jie Chen, Junfeng Chen, and Dongxu Chen. "Using Compact Coevolutionary Algorithm for Matching Biomedical Ontologies." Computational Intelligence and Neuroscience 2018 (October 8, 2018): 1–8. http://dx.doi.org/10.1155/2018/2309587.

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Over the recent years, ontologies are widely used in various domains such as medical records annotation, medical knowledge representation and sharing, clinical guideline management, and medical decision-making. To implement the cooperation between intelligent applications based on biomedical ontologies, it is crucial to establish correspondences between the heterogeneous biomedical concepts in different ontologies, which is so-called biomedical ontology matching. Although Evolutionary algorithms (EAs) are one of the state-of-the-art methodologies to match the heterogeneous ontologies, huge mem

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Solan, Ron, Joana Pereira, Andrei N. Lupas, Rachel Kolodny та Nir Ben-Tal. "Gram-negative outer-membrane proteins with multiple β-barrel domains". Proceedings of the National Academy of Sciences 118, № 31 (2021): e2104059118. http://dx.doi.org/10.1073/pnas.2104059118.

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Outer-membrane beta barrels (OMBBs) are found in the outer membrane of gram-negative bacteria and eukaryotic organelles. OMBBs fold as antiparallel β-sheets that close onto themselves, forming pores that traverse the membrane. Currently known structures include only one barrel, of 8 to 36 strands, per chain. The lack of multi-OMBB chains is surprising, as most OMBBs form oligomers, and some function only in this state. Using a combination of sensitive sequence comparison methods and coevolutionary analysis tools, we identify many proteins combining multiple beta barrels within a single chain;

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Donges, Jonathan F., Wolfgang Lucht, Finn Müller-Hansen, and Will Steffen. "The technosphere in Earth System analysis: A coevolutionary perspective." Anthropocene Review 4, no. 1 (2017): 23–33. http://dx.doi.org/10.1177/2053019616676608.

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Earth System analysis is the study of the joint dynamics of biogeophysical, social and technological processes on our planet. To advance our understanding of possible future development pathways and identify management options for navigating to safe operating spaces while avoiding undesirable domains, computer models of the Earth System are developed and applied. These models hardly represent dynamical properties of technological processes despite their great planetary-scale influence on the biogeophysical components of the Earth System and the associated risks for human societies posed, e.g.

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Granata, Daniele, Luca Ponzoni, Cristian Micheletti, and Vincenzo Carnevale. "Patterns of coevolving amino acids unveil structural and dynamical domains." Proceedings of the National Academy of Sciences 114, no. 50 (2017): E10612—E10621. http://dx.doi.org/10.1073/pnas.1712021114.

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Patterns of interacting amino acids are so preserved within protein families that the sole analysis of evolutionary comutations can identify pairs of contacting residues. It is also known that evolution conserves functional dynamics, i.e., the concerted motion or displacement of large protein regions or domains. Is it, therefore, possible to use a pure sequence-based analysis to identify these dynamical domains? To address this question, we introduce here a general coevolutionary coupling analysis strategy and apply it to a curated sequence database of hundreds of protein families. For most fa

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García, Enol, José R. Villar, Qing Tan, Javier Sedano, and Camelia Chira. "An efficient multi-robot path planning solution using A* and coevolutionary algorithms." Integrated Computer-Aided Engineering 30, no. 1 (2022): 41–52. http://dx.doi.org/10.3233/ica-220695.

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Multi-robot path planning has evolved from research to real applications in warehouses and other domains; the knowledge on this topic is reflected in the large amount of related research published in recent years on international journals. The main focus of existing research relates to the generation of efficient routes, relying the collision detection to the local sensory system and creating a solution based on local search methods. This approach implies the robots having a good sensory system and also the computation capabilities to take decisions on the fly. In some controlled environments,

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Dharna, Aaron, Julian Togelius, and L. B. Soros. "Co-Generation of Game Levels and Game-Playing Agents." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 16, no. 1 (2020): 203–9. http://dx.doi.org/10.1609/aiide.v16i1.7431.

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Open-endedness, a longstanding cornerstone of artificial life research, is the ability of systems to generate potentially unbounded ontologies of increasing novelty and complexity. Engineering generative systems displaying at least some degree of this ability is a goal with clear applications to procedural content generation in games. The Paired Open-Ended Trailblazer (POET) algorithm, heretofore explored only in a biped walking domain, is a coevolutionary system that simultaneously generates environments and agents that can solve them. This paper introduces a POET-Inspired Neuroevolutionary S

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Gopnik, Alison, Shaun O’Grady, Christopher G. Lucas, et al. "Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood." Proceedings of the National Academy of Sciences 114, no. 30 (2017): 7892–99. http://dx.doi.org/10.1073/pnas.1700811114.

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How was the evolution of our unique biological life history related to distinctive human developments in cognition and culture? We suggest that the extended human childhood and adolescence allows a balance between exploration and exploitation, between wider and narrower hypothesis search, and between innovation and imitation in cultural learning. In particular, different developmental periods may be associated with different learning strategies. This relation between biology and culture was probably coevolutionary and bidirectional: life-history changes allowed changes in learning, which in tu

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Jaśkowski, Wojciech, Paweł Liskowski, Marcin Szubert, and Krzysztof Krawiec. "The performance profile: A multi–criteria performance evaluation method for test–based problems." International Journal of Applied Mathematics and Computer Science 26, no. 1 (2016): 215–29. http://dx.doi.org/10.1515/amcs-2016-0015.

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Abstract In test-based problems, solutions produced by search algorithms are typically assessed using average outcomes of interactions with multiple tests. This aggregation leads to information loss, which can render different solutions apparently indifferent and hinder comparison of search algorithms. In this paper we introduce the performance profile, a generic, domain-independent, multi-criteria performance evaluation method that mitigates this problem by characterizing the performance of a solution by a vector of outcomes of interactions with tests of various difficulty. To demonstrate the

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Verkhivker, Gennady. "Coevolution, Dynamics and Allostery Conspire in Shaping Cooperative Binding and Signal Transmission of the SARS-CoV-2 Spike Protein with Human Angiotensin-Converting Enzyme 2." International Journal of Molecular Sciences 21, no. 21 (2020): 8268. http://dx.doi.org/10.3390/ijms21218268.

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Binding to the host receptor is a critical initial step for the coronavirus SARS-CoV-2 spike protein to enter into target cells and trigger virus transmission. A detailed dynamic and energetic view of the binding mechanisms underlying virus entry is not fully understood and the consensus around the molecular origins behind binding preferences of SARS-CoV-2 for binding with the angiotensin-converting enzyme 2 (ACE2) host receptor is yet to be established. In this work, we performed a comprehensive computational investigation in which sequence analysis and modeling of coevolutionary networks are

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Henrich, Joseph, and Michael Muthukrishna. "The Origins and Psychology of Human Cooperation." Annual Review of Psychology 72, no. 1 (2021): 207–40. http://dx.doi.org/10.1146/annurev-psych-081920-042106.

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Humans are an ultrasocial species. This sociality, however, cannot be fully explained by the canonical approaches found in evolutionary biology, psychology, or economics. Understanding our unique social psychology requires accounting not only for the breadth and intensity of human cooperation but also for the variation found across societies, over history, and among behavioral domains. Here, we introduce an expanded evolutionary approach that considers how genetic and cultural evolution, and their interaction, may have shaped both the reliably developing features of our minds and the well-docu

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Xiao, Qingjie, Mengxue Xu, Weiwei Wang, et al. "Utilization of AlphaFold2 to Predict MFS Protein Conformations after Selective Mutation." International Journal of Molecular Sciences 23, no. 13 (2022): 7235. http://dx.doi.org/10.3390/ijms23137235.

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The major facilitator superfamily (MFS) is the largest secondary transporter family and is responsible for transporting a broad range of substrates across the biomembrane. These proteins are involved in a series of conformational changes during substrate transport. To decipher the transport mechanism, it is necessary to obtain structures of these different conformations. At present, great progress has been made in predicting protein structure based on coevolutionary information. In this study, AlphaFold2 was used to predict different conformational structures for 69 MFS transporters of E. coli

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Meng, Lingyan, Xiaomeng Li, Yue Hou, Yaxuan Li, and Yingkao Hu. "Functional conservation and divergence in plant-specific GRF gene family revealed by sequences and expression analysis." Open Life Sciences 17, no. 1 (2022): 155–71. http://dx.doi.org/10.1515/biol-2022-0018.

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Abstract Unique to plants, growth regulatory factors (GRFs) play important roles in plant growth and reproduction. This study investigated the evolutionary and functional characteristics associated with plant growth. Using genome-wide analysis of 15 plant species, 173 members of the GRF family were identified and phylogenetically categorized into six groups. All members contained WRC and QLQ conserved domains, and the family’s expansion largely depended on segmental duplication. The promoter region of the GRF gene family mainly contained four types of cis-acting elements (light-responsive elem

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Krepel, Dana, Aram Davtyan, Nicholas P. Schafer, Peter G. Wolynes, and José N. Onuchic. "Braiding topology and the energy landscape of chromosome organization proteins." Proceedings of the National Academy of Sciences 117, no. 3 (2019): 1468–77. http://dx.doi.org/10.1073/pnas.1917750117.

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Assemblies of structural maintenance of chromosomes (SMC) proteins and kleisin subunits are essential to chromosome organization and segregation across all kingdoms of life. While structural data exist for parts of the SMC−kleisin complexes, complete structures of the entire complexes have yet to be determined, making mechanistic studies difficult. Using an integrative approach that combines crystallographic structural information about the globular subdomains, along with coevolutionary information and an energy landscape optimized force field (AWSEM), we predict atomic-scale structures for se

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Sutto, Ludovico, Simone Marsili, Alfonso Valencia, and Francesco Luigi Gervasio. "From residue coevolution to protein conformational ensembles and functional dynamics." Proceedings of the National Academy of Sciences 112, no. 44 (2015): 13567–72. http://dx.doi.org/10.1073/pnas.1508584112.

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The analysis of evolutionary amino acid correlations has recently attracted a surge of renewed interest, also due to their successful use in de novo protein native structure prediction. However, many aspects of protein function, such as substrate binding and product release in enzymatic activity, can be fully understood only in terms of an equilibrium ensemble of alternative structures, rather than a single static structure. In this paper we combine coevolutionary data and molecular dynamics simulations to study protein conformational heterogeneity. To that end, we adapt the Boltzmann-learning

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Liu, Guangshuai, Huanxin Zhang, Chao Zhao, and Honghai Zhang. "Evolutionary History of the Toll-Like Receptor Gene Family across Vertebrates." Genome Biology and Evolution 12, no. 1 (2019): 3615–34. http://dx.doi.org/10.1093/gbe/evz266.

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Abstract Adaptation to a wide range of pathogenic environments is a major aspect of the ecological adaptations of vertebrates during evolution. Toll-like receptors (TLRs) are ancient membrane-bound sensors in animals and are best known for their roles in detecting and defense against invading pathogenic microorganisms. To understand the evolutionary history of the vertebrate TLR gene family, we first traced the origin of single-cysteine cluster TLRs that share the same protein architecture with vertebrate TLRs in early-branching animals and then analyzed all members of the TLR family in over 2

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Hong, Seung Hwan, Keehyoung Joo, and Jooyoung Lee. "ConDo: protein domain boundary prediction using coevolutionary information." Bioinformatics 35, no. 14 (2018): 2411–17. http://dx.doi.org/10.1093/bioinformatics/bty973.

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AbstractMotivationDomain boundary prediction is one of the most important problems in the study of protein structure and function. Many sequence-based domain boundary prediction methods are either template-based or machine learning (ML) based. ML-based methods often perform poorly due to their use of only local (i.e. short-range) features. These conventional features such as sequence profiles, secondary structures and solvent accessibilities are typically restricted to be within 20 residues of the domain boundary candidate.ResultsTo address the performance of ML-based methods, we developed a n

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Panait, Liviu. "Theoretical Convergence Guarantees for Cooperative Coevolutionary Algorithms." Evolutionary Computation 18, no. 4 (2010): 581–615. http://dx.doi.org/10.1162/evco_a_00004.

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Cooperative coevolutionary algorithms have the potential to significantly speed up the search process by dividing the space into parts that can each be conquered separately. However, recent research presented theoretical and empirical arguments that these algorithms tend to converge to suboptimal solutions in the search space, and are thus not fit for optimization tasks. This paper details an extended formal model for cooperative coevolutionary algorithms, and uses it to explore possible reasons these algorithms converge to optimal or suboptimal solutions. We demonstrate that, under specific c

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Tian, Jin, Minqiang Li, and Fuzan Chen. "A hybrid classification algorithm based on coevolutionary EBFNN and domain covering method." Neural Computing and Applications 18, no. 3 (2008): 293–308. http://dx.doi.org/10.1007/s00521-008-0182-6.

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Hofmeyer, Hèrm, and Juan Manuel Davila Delgado. "Coevolutionary and genetic algorithm based building spatial and structural design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 29, no. 4 (2015): 351–70. http://dx.doi.org/10.1017/s0890060415000384.

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AbstractIn this article, two methods to develop and optimize accompanying building spatial and structural designs are compared. The first, a coevolutionary method, applies deterministic procedures, inspired by realistic design processes, to cyclically add a suitable structural design to the input of a spatial design, evaluate and improve the structural design via the finite element method and topology optimization, adjust the spatial design according to the improved structural design, and modify the spatial design such that the initial spatial requirements are fulfilled. The second method uses

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ROSENMAN, MIKE, and ROB SAUNDERS. "Self-regulatory hierarchical coevolution." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 17, no. 4 (2003): 273–85. http://dx.doi.org/10.1017/s089006040317401x.

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An evolutionary model for nonroutine design is presented, which is called hierarchical coevolution. The requirements for an evolutionary model of nonroutine design are provided, and some of the problems with existing approaches are discussed. Some of the ways in which these problems have been addressed are examined in terms of the design knowledge required by evolutionary processes. Then, a synthesis of these approaches as a hierarchical coevolutionary model of nonroutine design is presented and the manner in which this model addresses the requirements of an evolutionary design model is discus

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Rodriguez-Rivas, Juan, Simone Marsili, David Juan, and Alfonso Valencia. "Conservation of coevolving protein interfaces bridges prokaryote–eukaryote homologies in the twilight zone." Proceedings of the National Academy of Sciences 113, no. 52 (2016): 15018–23. http://dx.doi.org/10.1073/pnas.1611861114.

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Protein–protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein

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Stanley, K. O., and R. Miikkulainen. "Competitive Coevolution through Evolutionary Complexification." Journal of Artificial Intelligence Research 21 (February 1, 2004): 63–100. http://dx.doi.org/10.1613/jair.1338.

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Two major goals in machine learning are the discovery and improvement of solutions to complex problems. In this paper, we argue that complexification, i.e. the incremental elaboration of solutions through adding new structure, achieves both these goals. We demonstrate the power of complexification through the NeuroEvolution of Augmenting Topologies (NEAT) method, which evolves increasingly complex neural network architectures. NEAT is applied to an open-ended coevolutionary robot duel domain where robot controllers compete head to head. Because the robot duel domain supports a wide range of st

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Xue, Xingsi, and Wenbin Tan. "Matching Cybersecurity Ontologies on Internet of Everything through Coevolutionary Multiobjective Evolutionary Algorithm." Security and Communication Networks 2022 (August 10, 2022): 1–13. http://dx.doi.org/10.1155/2022/3572404.

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Since Internet of Everything (IoE) makes all the connections that come online more relevant and valuable, they are subject to numerous security and privacy concerns. Cybersecurity ontology is a shared knowledge model for tackling the security information heterogeneity issue on IoE, which has been widely used in the IoE domain. However, the existing CSOs are developed and maintained independently, yielding the CSO heterogeneity problem. To address this issue, we need to use the similarity measure (SM) to calculate two entities’ similarity value in two CSOs and, on this basis, determine the enti

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Campbell, Matthew A., Shannon Loncar, Robert M. Kotin, and Robert J. Gifford. "Comparative analysis reveals the long-term coevolutionary history of parvoviruses and vertebrates." PLOS Biology 20, no. 11 (2022): e3001867. http://dx.doi.org/10.1371/journal.pbio.3001867.

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Parvoviruses (family Parvoviridae) are small DNA viruses that cause numerous diseases of medical, veterinary, and agricultural significance and have important applications in gene and anticancer therapy. DNA sequences derived from ancient parvoviruses are common in animal genomes and analysis of these endogenous parvoviral elements (EPVs) has demonstrated that the family, which includes twelve vertebrate-specific genera, arose in the distant evolutionary past. So far, however, such “paleovirological” analysis has only provided glimpses into the biology of ancient parvoviruses and their long-te

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Wever, Marcel, Lorijn van Rooijen, and Heiko Hamann. "Multioracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets." Evolutionary Computation 28, no. 2 (2020): 165–93. http://dx.doi.org/10.1162/evco_a_00266.

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In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of

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Puppala, Narendra, and Sandip Sen. "Evolving Cooperative Groups Using Shared Memory." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 6 (1999): 457–61. http://dx.doi.org/10.20965/jaciii.1999.p0457.

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We present a coevolutionary approach to generating behavioral strategies for cooperating agent groups. We coevolve agent behavior with genetic algorithms (GAs), where one GA population is evolved per individual in the cooperative group. Groups are evaluated by pairing strategies from each population and the best strategy pairs are stored together in shared memory. To evaluate a strategy from one population, it is paired sequentially with strategies from the other population stored in shared memory. The maximum evaluation from all such pairings is used to evaluate the strategy. A pair is stored

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Chen, Zhen, Weiqian Meyer, Sugima Rappert, Jibin Sun, and An-Ping Zeng. "Coevolutionary Analysis Enabled Rational Deregulation of Allosteric Enzyme Inhibition in Corynebacterium glutamicum for Lysine Production." Applied and Environmental Microbiology 77, no. 13 (2011): 4352–60. http://dx.doi.org/10.1128/aem.02912-10.

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ABSTRACTProduct feedback inhibition of allosteric enzymes is an essential issue for the development of highly efficient microbial strains for bioproduction. Here we used aspartokinase fromCorynebacterium glutamicum(CgAK), a key enzyme controlling the biosynthesis of industrially important aspartate family amino acids, as a model to demonstrate a fast and efficient approach to the deregulation of allostery. In the last 50 years many researchers and companies have made considerable efforts to deregulate this enzyme from allosteric inhibition by lysine and threonine. However, only a limited numbe

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Deliyska, Boryana, Vladislav Todorov, and Adelina Ivanova. "Common Ontology of Sustainable Development." International Journal of Information Systems and Social Change 11, no. 4 (2020): 55–69. http://dx.doi.org/10.4018/ijissc.2020100104.

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Sustainable development in its various aspects is a multifaceted and contradictory concept, interpreted by multiple sources. This study exposes the need to explore and develop a productive coevolutionary approach to build modular ontological metamodel of sustainable development including a set of interconnected ontologies and instance databases. Based on a review and on an analysis of existing ontologies in this area, a methodology for building common ontology of sustainable development is proposed as a top level of the metamodel. Using terminology from well-established and authoritative sourc

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MORFFE, JANS, NAYLA GARCÍA, LAURA VÉLIZ, KOICHI HASEGAWA, and RAMON A. CARRENO. "Morphological and molecular characterization of two species of nematodes (Oxyuridomorpha: Thelastomatoidea: Protrelloididae, Thelastomatidae) parasitic in the cockroach Blaberus discoidalis Serville (Blattaria: Blaberidae) from Cuba." Zootaxa 5194, no. 1 (2022): 92–108. http://dx.doi.org/10.11646/zootaxa.5194.1.5.

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Protrelleta floridana Chitwood, 1932 and Cranifera cranifera (Chitwood, 1932) (Oxyuridomorpha: Thelastomatoidea: Protrelloididae, Thelastomatidae) are recorded for the first time in Cuba. These nematodes were found to parasitize the cockroach Blaberus discoidalis Serville (Blattaria: Blaberidae), constituting a new host record for them. Both species are redescribed with the aid of scanning electron microscopy and the arrangement of the copulatory papillae of the males of P. floridana is amended. The present specimens coincide in their morphology and most of the measurements with the type popul

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Cavalier-Smith, Thomas, and Ema E.-Yung Chao. "Multidomain ribosomal protein trees and the planctobacterial origin of neomura (eukaryotes, archaebacteria)." Protoplasma 257, no. 3 (2020): 621–753. http://dx.doi.org/10.1007/s00709-019-01442-7.

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AbstractPalaeontologically, eubacteria are > 3× older than neomura (eukaryotes, archaebacteria). Cell biology contrasts ancestral eubacterial murein peptidoglycan walls and derived neomuran N-linked glycoprotein coats/walls. Misinterpreting long stems connecting clade neomura to eubacteria on ribosomal sequence trees (plus misinterpreted protein paralogue trees) obscured this historical pattern. Universal multiprotein ribosomal protein (RP) trees, more accurate than rRNA trees, are taxonomically undersampled. To reduce contradictions with genically richer eukaryote trees and improve eubacte

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Zhang, Xuan, Xueting Wang, Kai Xu та ін. "The serine/threonine/tyrosine kinase STY46 defends against hordeivirus infection by phosphorylating γb protein". Plant Physiology 186, № 1 (2021): 715–30. http://dx.doi.org/10.1093/plphys/kiab056.

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Abstract Protein phosphorylation is a common post-translational modification that frequently occurs during plant–virus interaction. Host protein kinases often regulate virus infectivity and pathogenicity by phosphorylating viral proteins. The Barley stripe mosaic virus (BSMV) γb protein plays versatile roles in virus infection and the coevolutionary arms race between plant defense and viral counter-defense. Here, we identified that the autophosphorylated cytosolic serine/threonine/tyrosine (STY) protein kinase 46 of Nicotiana benthamiana (NbSTY46) phosphorylates and directly interacts with the

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McIntyre, Andrew R., and Malcolm I. Heywood. "Classification as Clustering: A Pareto Cooperative-Competitive GP Approach." Evolutionary Computation 19, no. 1 (2011): 137–66. http://dx.doi.org/10.1162/evco_a_00016.

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Intuitively population based algorithms such as genetic programming provide a natural environment for supporting solutions that learn to decompose the overall task between multiple individuals, or a team. This work presents a framework for evolving teams without recourse to prespecifying the number of cooperating individuals. To do so, each individual evolves a mapping to a distribution of outcomes that, following clustering, establishes the parameterization of a (Gaussian) local membership function. This gives individuals the opportunity to represent subsets of tasks, where the overall task i

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Ji, Meijun, Kangtai Sun, Hui Fang, et al. "Genome-wide identification and characterization of the CLASP_N gene family in upland cotton (Gossypium hirsutum L.)." PeerJ 10 (January 3, 2022): e12733. http://dx.doi.org/10.7717/peerj.12733.

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Background Cytoplasmic linker–associated proteins (CLASPs) are tubule proteins that can bind to microtubules and participate in regulating the structure and function of microtubules, which significantly affects the development and growth of plants. These proteins have been identified in Arabidopsis; however, little research has been performed in upland cotton. Methods In this study, the whole genome of the CLASP_N family was analyzed to provide theoretical support for the function of this gene family in the development of upland cotton fiber. Bioinformatics was used to analyze the family chara

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Goubard, Armelle, François Clavel, Fabrizio Mammano, and Béatrice Labrosse. "In vivo selection by enfuvirtide of HIV type-1 env quasispecies with optimal potential for phenotypic expression of HR1 mutations." Antiviral Therapy 14, no. 4 (2008): 597–602. http://dx.doi.org/10.1177/135965350901400409.

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Background HIV type-1 (HIV-1) resistance to enfuvirtide (ENF) is mediated by mutations in the HR1 domain of gp41. We have previously shown that some of these mutations are selected in the context of env backgrounds that are not dominant before exposure to ENF, suggesting that particular env environments could facilitate phenotypic expression of HR1-mediated ENF resistance. Methods Envelope clones, representing the viral quasispecies present in the longitudinal follow-up of a patient who failed ENF-based salvage therapy, were tested for ENF susceptibility and Env-related replicative capacity. E

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Balbuena, Juan Antonio, Óscar Alejandro Pérez-Escobar, Cristina Llopis-Belenguer, and Isabel Blasco-Costa. "Random Tanglegram Partitions (Random TaPas): An Alexandrian Approach to the Cophylogenetic Gordian Knot." Systematic Biology 69, no. 6 (2020): 1212–30. http://dx.doi.org/10.1093/sysbio/syaa033.

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Abstract Symbiosis is a key driver of evolutionary novelty and ecological diversity, but our understanding of how macroevolutionary processes originate extant symbiotic associations is still very incomplete. Cophylogenetic tools are used to assess the congruence between the phylogenies of two groups of organisms related by extant associations. If phylogenetic congruence is higher than expected by chance, we conclude that there is cophylogenetic signal in the system under study. However, how to quantify cophylogenetic signal is still an open issue. We present a novel approach, Random Tanglegram

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Chengqi Zhang*, Ling Guan**, and Zheru Chi. "Introduction to the Special Issue on Learning in Intelligent Algorithms and Systems Design." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 6 (1999): 439–40. http://dx.doi.org/10.20965/jaciii.1999.p0439.

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Learning has long been and will continue to be a key issue in intelligent algorithms and systems design. Emulating the behavior and mechanisms of human learning by machines at such high levels as symbolic processing and such low levels as neuronal processing has long been a dominant interest among researchers worldwide. Neural networks, fuzzy logic, and evolutionary algorithms represent the three most active research areas. With advanced theoretical studies and computer technology, many promising algorithms and systems using these techniques have been designed and implemented for a wide range

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Shcherbakova, Olena, Volker Gast, Damián E. Blasi, Hedvig Skirgård, Russell D. Gray, and Simon J. Greenhill. "A quantitative global test of the complexity trade-off hypothesis: the case of nominal and verbal grammatical marking." Linguistics Vanguard, December 6, 2022. http://dx.doi.org/10.1515/lingvan-2021-0011.

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Abstract Nouns and verbs are known to differ in the types of grammatical information they encode. What is less well known is the relationship between verbal and nominal coding within and across languages. The equi-complexity hypothesis holds that all languages are equally complex overall, which entails trade-offs between coding in different domains. From a diachronic point of view, this hypothesis implies that the loss and gain of coding in different domains can be expected to balance each other out. In this study, we test to what extent such inverse coevolution can be observed in a sample of

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Wu, Tianqi, Jie Hou, Badri Adhikari, and Jianlin Cheng. "Analysis of several key factors influencing deep learning-based inter-residue contact prediction." Bioinformatics, August 30, 2019. http://dx.doi.org/10.1093/bioinformatics/btz679.

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Abstract Motivation Deep learning has become the dominant technology for protein contact prediction. However, the factors that affect the performance of deep learning in contact prediction have not been systematically investigated. Results We analyzed the results of our three deep learning-based contact prediction methods (MULTICOM-CLUSTER, MULTICOM-CONSTRUCT and MULTICOM-NOVEL) in the CASP13 experiment and identified several key factors [i.e. deep learning technique, multiple sequence alignment (MSA), distance distribution prediction and domain-based contact integration] that influenced the c

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Chonofsky, Mark, Saulo H. P. de Oliveira, Konrad Krawczyk, and Charlotte M. Deane. "The evolution of contact prediction: Evidence that contact selection in statistical contact prediction is changing." Bioinformatics, November 6, 2019. http://dx.doi.org/10.1093/bioinformatics/btz816.

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Abstract Motivation Over the last few years, the field of protein structure prediction has been transformed by increasingly-accurate contact prediction software. These methods are based on the detection of coevolutionary relationships between residues from multiple sequence alignments. However, despite speculation, there is little evidence of a link between contact prediction and the physico-chemical interactions which drive amino-acid coevolution. Furthermore, existing protocols predict only a fraction of all protein contacts and it is not clear why some contacts are favoured over others. Usi

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Ritter, Seth C., and Benjamin J. Hackel. "Validation and Stabilization of a Prophage Lysin of Clostridium perfringens by Using Yeast Surface Display and Coevolutionary Models." Applied and Environmental Microbiology 85, no. 10 (2019). http://dx.doi.org/10.1128/aem.00054-19.

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ABSTRACT Bacteriophage lysins are compelling antimicrobial proteins whose biotechnological utility and evolvability would be aided by elevated stability. Lysin catalytic domains, which evolved as modular entities distinct from cell wall binding domains, can be classified into one of several families with highly conserved structure and function, many of which contain thousands of annotated homologous sequences. Motivated by the quality of these evolutionary data, the performance of generative protein models incorporating coevolutionary information was analyzed to predict the stability of varian

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Acharya, Debarun, and Tapan K. Dutta. "Elucidating the network features and evolutionary attributes of intra- and interspecific protein–protein interactions between human and pathogenic bacteria." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-020-80549-x.

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AbstractHost–pathogen interaction is one of the most powerful determinants involved in coevolutionary processes covering a broad range of biological phenomena at molecular, cellular, organismal and/or population level. The present study explored host–pathogen interaction from the perspective of human–bacteria protein–protein interaction based on large-scale interspecific and intraspecific interactome data for human and three pathogenic bacterial species, Bacillus anthracis, Francisella tularensis and Yersinia pestis. The network features revealed a preferential enrichment of intraspecific hubs

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Acharya, Debarun, and Tapan K. Dutta. "Elucidating the network features and evolutionary attributes of intra- and interspecific protein–protein interactions between human and pathogenic bacteria." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-020-80549-x.

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AbstractHost–pathogen interaction is one of the most powerful determinants involved in coevolutionary processes covering a broad range of biological phenomena at molecular, cellular, organismal and/or population level. The present study explored host–pathogen interaction from the perspective of human–bacteria protein–protein interaction based on large-scale interspecific and intraspecific interactome data for human and three pathogenic bacterial species, Bacillus anthracis, Francisella tularensis and Yersinia pestis. The network features revealed a preferential enrichment of intraspecific hubs

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Kennedy, Emily N., Clay A. Foster, Sarah A. Barr, and Robert B. Bourret. "General strategies for using amino acid sequence data to guide biochemical investigation of protein function." Biochemical Society Transactions, November 23, 2022. http://dx.doi.org/10.1042/bst20220849.

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The rapid increase of ‘-omics' data warrants the reconsideration of experimental strategies to investigate general protein function. Studying individual members of a protein family is likely insufficient to provide a complete mechanistic understanding of family functions, especially for diverse families with thousands of known members. Strategies that exploit large amounts of available amino acid sequence data can inspire and guide biochemical experiments, generating broadly applicable insights into a given family. Here we review several methods that utilize abundant sequence data to focus exp

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Auer, S., J. Heitzig, U. Kornek, E. Schöll, and J. Kurths. "The Dynamics of Coalition Formation on Complex Networks." Scientific Reports 5, no. 1 (2015). http://dx.doi.org/10.1038/srep13386.

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Abstract Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier res

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Lee, Jaekwon, Seung Yeob Shin, Shiva Nejati, and Lionel C. Briand. "Optimal priority assignment for real-time systems: a coevolution-based approach." Empirical Software Engineering 27, no. 6 (2022). http://dx.doi.org/10.1007/s10664-022-10170-1.

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AbstractIn real-time systems, priorities assigned to real-time tasks determine the order of task executions, by relying on an underlying task scheduling policy. Assigning optimal priority values to tasks is critical to allow the tasks to complete their executions while maximizing safety margins from their specified deadlines. This enables real-time systems to tolerate unexpected overheads in task executions and still meet their deadlines. In practice, priority assignments result from an interactive process between the development and testing teams. In this article, we propose an automated meth

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Malinverni, Duccio, Alfredo Jost Lopez, Paolo De Los Rios, Gerhard Hummer, and Alessandro Barducci. "Modeling Hsp70/Hsp40 interaction by multi-scale molecular simulations and coevolutionary sequence analysis." eLife 6 (May 12, 2017). http://dx.doi.org/10.7554/elife.23471.

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The interaction between the Heat Shock Proteins 70 and 40 is at the core of the ATPase regulation of the chaperone machinery that maintains protein homeostasis. However, the structural details of the interaction remain elusive and contrasting models have been proposed for the transient Hsp70/Hsp40 complexes. Here we combine molecular simulations based on both coarse-grained and atomistic models with coevolutionary sequence analysis to shed light on this problem by focusing on the bacterial DnaK/DnaJ system. The integration of these complementary approaches resulted in a novel structural model

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