Stable Consensus Research Articles

Consensus QTL map deciphered genes and pathways regulating tolerance to post‐flowering diseases in maize

AbstractPost‐flowering diseases (PFDs), such as ear rot, stalk rot and smut, affect maize yield and quality by damaging the reproductive organs, stalks and seeds. We hypothesized that quantitative trait loci (QTL) associated with different PFDs colocalize and share similar defence mechanisms. Hence, to find a stable consensus meta‐QTL (MQTL) for single or multiple PFDs, MQTL analysis was performed. QTL conferring resistance to PFD reported in 31 independent studies were collated to develop a consensus map. As many as 49 MQTL conferring PFD resistance were projected using appropriate algorithms. Most MQTL regions encompass genes encoding a wide range of defence‐related proteins. MQTL1.1 and MQTL10.5 included QTL/genes for resistance to all PFDs, which supported our hypothesis. Candidate genes for PFDs in MQTL7.1 were associated with pathogenesis‐related 1 protein and mitogen‐activated protein kinase (MAPK) signalling. MQTL5.2 encompassed chalcone flavanone isomerase and cinnamoyl coenzyme A (CoA) reductase genes involved in flavonoid and phenylpropanoid biosynthesis, respectively. Furthermore, MQTL10.4 was found to harbour genes encoding E3 ubiquitin ligase, WRKY‐TF11, calcium‐binding domains and zinc finger motifs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis reiterated the role of genes within MQTL7.1 in the MAPK signalling pathway, phytohormone signal transduction and plant–pathogen interaction. Hence, we propose that these genes are potential candidates for PFD resistance. Furthermore, 75% of the genes within the MQTL showed orthology with sorghum and rice, indicating that these genes were conserved across species. The role of 27 MQTL, including the six most significant MQTL, was confirmed with reported genome‐wide association study (GWAS) results. Thus, the hotspots associated with PFDs identified in our study could be reliably used in marker‐assisted breeding for PFD resistance.

The modernisation of newborn screening as a pan-European challenge – An international delphi study

Newborn screening is a public health measure to diagnose rare diseases at birth, thereby minimising negative effects of late treatment. Genomic technologies promise an unprecedented expansion of screened diseases at low cost and with transformative potential for newborn screening programmes. However, barriers to the public funding of genomic newborn screening are poorly understood, particularly in light of the heterogenous European newborn screening landscape. This study therefore aims to understand whether international newborn screening experts share a common understanding of the barriers to fund genomic newborn screening. For this purpose, we convened 21 European newborn screening experts across a range of professions and national backgrounds in a Delphi study. Stable consensus, determined via the Wilcoxon matched-pairs signed-ranks test, was found via three consecutive survey rounds for all presented barriers. Experts generally judged the scenario of genomic newborn screening being available to every newborn in seven years to be unlikely, identifying treatability and the absence of counselling and a skilled workforce as the most significant barriers to public funding. We identify value re-definition for rare disease treatments, centralisation of genomic expertise, and international research consortia as avenues for pan-European actions which build on the consensus achieved by our Delphi panel.

Looking for Stability in Proof-of-Stake based Consensus Mechanisms

The Proof-of-Stake (PoS) consensus algorithm has been criticized, in the literature and in several cryptocurrencies communities, due to the so-called compounding effect: who is richer has more coins to stake, therefore higher probability of being selected as a block validator and obtaining the corresponding rewards, thus becoming even richer. In this paper, we present a PoS simulator written in the Julia language that allows one to test several variants of PoS-based consensus algorithms, tweaking their parameters, and observe how the distribution of cryptocurrency coins among the users evolves over time. Such a tool can be used to investigate which combinations of parameters values allow to obtain a “fair” and stable consensus algorithm, in which, over the long term, no one gets richer or poorer by the mere act of validating blocks. Based on this investigation, we also introduce a new PoS-based consensus mechanism that allows the system to keep the wealth distribution stable even after a large number of epochs.

The importance of input sequence set to consensus-derived proteins and their relationship to reconstructed ancestral proteins.

A protein sequence encodes its energy landscape-all the accessible conformations, energetics, and dynamics. The evolutionary relationship between sequence and landscape can be probed phylogenetically by compiling a multiple sequence alignment of homologous sequences and generating common ancestors via Ancestral Sequence Reconstruction or a consensus protein containing the most common amino acid at each position. Both ancestral and consensus proteins are often more stable than their extant homologs-questioning the differences between them and suggesting that both approaches serve as general methods to engineer thermostability. We used the Ribonuclease H family to compare these approaches and evaluate how the evolutionary relationship of the input sequences affects the properties of the resulting consensus protein. While the consensus protein derived from our full Ribonuclease H sequence alignment is structured and active, it neither shows properties of a well-folded protein nor has enhanced stability. In contrast, the consensus protein derived from a phylogenetically-restricted set of sequences is significantly more stable and cooperatively folded, suggesting that cooperativity may be encoded by different mechanisms in separate clades and lost when too many diverse clades are combined to generate a consensus protein. To explore this, we compared pairwise covariance scores using a Potts formalism as well as higher-order sequence correlations using singular value decomposition (SVD). We find the SVD coordinates of a stable consensus sequence are close to coordinates of the analogous ancestor sequence and its descendants, whereas the unstable consensus sequences are outliers in SVD space.

Meta-QTL analysis reveals the important genomics regions for biotic stresses, nutritional quality and yield related traits in pearl millet

AbstractPearl millet (Cenchrus americanus) is the sixth most significant cereal crop cultivated on 30 million ha and a staple diet for 90 million poor people across the globe. Besides abiotic stresses several biotic stresses have been limiting production of pearl millet in the semi-arid and arid regions. Although, the Quantitative Trait Loci (QTLs) associated with key diseases like blast, rust and downy mildew resistance and nutritional content has been reported, the use of these QTLs is limited in breeding programs. To identify highly stable consensus genomic regions, we conducted Meta-QTL analysis using 191 QTLs reported in 12 independent studies over the last two decades. As a result, we report 34 Meta-QTLs regions on a consensus genetic map comprising of 692 markers and spanning 2070.7 cM. The confidence interval of Meta-QTLs was reduced by 3.63 folds (0.18–7.49 cM), in contrast to projected QTLs interval of 1.11–60.63 cM. Further, a total of 1198 genes were identified in 34 Meta-QTL regions. Among 34 Meta-QTL regions, Meta-QTL1.1 is found to be region of significant importance as it harbours genes for enhanced biotic stress tolerance, plant growth and development as well as genes related with enhanced seed development. Meta-QTL2.4 has highest number of genes with a significant role in disease resistance which contains basic leucine zipper domain, zinc family, leucine rich repeat regions. Meta-QTL3.1 has ABC transporter like activity coupled with the ATPase activity which has a role in Fe and Zn uptake in leaves and root tissues. These Meta-QTL regions can be used in genomics-assisted breeding for enhancing the blast, rust downy mildew resistance as well as yield and nutritional traits.

Selection pressures on evolution of ribonuclease H explored with rigorous free–energy–based design

Understanding natural protein evolution and designing novel proteins are motivating interest in development of high-throughput methods to explore large sequence spaces. In this work, we demonstrate the application of multisite λ dynamics (MSλD), a rigorous free energy simulation method, and chemical denaturation experiments to quantify evolutionary selection pressure from sequence-stability relationships and to address questions of design. This study examines a mesophilic phylogenetic clade of ribonuclease H (RNase H), furthering its extensive characterization in earlier studies, focusing on E. coli RNase H (ecRNH) and a more stable consensus sequence (AncCcons) differing at 15 positions. The stabilities of 32,768 chimeras between these two sequences were computed using the MSλD framework. The most stable and least stable chimeras were predicted and tested along with several other sequences, revealing a designed chimera with approximately the same stability increase as AncCcons, but requiring only half the mutations. Comparing the computed stabilities with experiment for 12 sequences reveals a Pearson correlation of 0.86 and root mean squared error of 1.18 kcal/mol, an unprecedented level of accuracy well beyond less rigorous computational design methods. We then quantified selection pressure using a simple evolutionary model in which sequences are selected according to the Boltzmann factor of their stability. Selection temperatures from 110 to 168 K are estimated in three ways by comparing experimental and computational results to evolutionary models. These estimates indicate selection pressure is high, which has implications for evolutionary dynamics and for the accuracy required for design, and suggests accurate high-throughput computational methods like MSλD may enable more effective protein design.

Education Research: Virtual Patient Management Conference for Epilepsy Surgery in the Post-COVID-19 Era: An Educational Perspective.

The primary objective of this study was to assess the potential educational value of a virtual patient management conference (PMC) with the introduction of inclusive anonymous polling at a comprehensive epilepsy center. The secondary objective was to evaluate differences between faculty and trainee polling results. Two online surveys were sent 1 year apart seeking opinions about a transition to virtual PMC and completed by virtual PMC faculty participants (including representatives from neurology, neurosurgery, and neuropsychology). One online survey was sent to trainees (medical students, residents, and fellows) to assess the educational value of the conference. Anonymous electronic polls surveying treatment options were completed by both faculty and trainees after each virtual PMC presentation but before discussing the case. The results were collected and analyzed over 16 months, including over the course of 1 academic year. The degree of consensus was determined by the maximum percentage of votes that a single choice received. Eleven faculty and 22 trainees responded to their respective surveys. The initial faculty survey revealed that 60.0% of faculty had an "excellent" or "very good" experience with virtual PMC; 1 year later, this proportion increased to 100.0% while trainees reported 90.9%. Each virtual PMC component, including perceived standard of care, was found to be "excellent" or "very good" by most faculty and trainees, and most (91% faculty, 63.7% trainees) were equally comfortable or more comfortable expressing opinions during the virtual discussion. During virtual PMC polls, faculty members were significantly more likely to vote for vagus nerve stimulation as a treatment option, while trainees were more likely to opt for responsive neurostimulation. Linear regression over the course of the academic year showed stable consensus over time for both faculty and trainees; however, the match between faculty and trainee consensus significantly increased over the academic year. Our results demonstrate that the virtual PMC constitutes an effective educational experience as an alternative to in-person conferences for the management of patients with drug-resistant epilepsy.

Lower bounds on the state complexity of population protocols

Population protocols are a model of computation in which an arbitrary number of indistinguishable finite-state agents interact in pairs. The goal of the agents is to decide by stable consensus whether their initial global configuration satisfies a given property, specified as a predicate on the set of configurations. The state complexity of a predicate is the number of states of a smallest protocol that computes it. Previous work by Blondin et al. has shown that the counting predicates x ge eta have state complexity mathcal {O}(log eta ) for leaderless protocols and mathcal {O}(log log eta ) for protocols with leaders. We obtain the first non-trivial lower bounds: the state complexity of x ge eta is Omega (log log eta ) for leaderless protocols, and the inverse of a non-elementary function for protocols with leaders.

The future of space activities and preservation on Mars: A preliminary policy Delphi study

A ‘planetary park’ system has been suggested as a way for Mars to ‘preserve’ land for a multitude of purposes. These parks would represent a diverse portion of martian terrain and would be regulated to minimize human contamination and prevent excess human intervention. One suggestion is a two-part land-use policy for Mars, i.e. planetary parks and Lockean land for the use of non-park areas, in which non-park areas could be opened up for development and settlement. Others have proposed that this planetary parks concept could be extended to appeal to corporate interests as a compromise between protecting environmental interests and allowing private use of resources on Mars. This empirical study aims to help advance the core discussion of the interplay between future space activities and future preservation plans on Mars. Specifically, this work uses a particular strategic foresight method, the Policy Delphi, as a means to reveal positions on that issue and to explore alternative policy options in advance, through the collective judgment of a panel of experts. It should be noted that the goal was not strictly to promote consensus regarding the topic of interest, but to encourage structured dialogue. Consequently, the stable consensus achieved in specific areas indicated that the panel of experts foresees international cooperation on matters related to preservation plans for Mars, which, in turn, will enhance the overall international space governance. Furthermore, the panel foresees the inclusion of varying actors, both state and non-state ones, in the development of a preservation framework for Mars, especially on a national level. To this end, the panel endorses the inclusion of a diversity of values to be protected via the aforementioned framework, and suggests the advancement of broad global dialogue on this matter including academic, industrial, governmental, and public actors. The preliminary insights revealed in this work may inform relevant international discussions towards the formulation of proactive policies that will contribute to the environmental governance of future activities on Mars.

In Search of a Stable Consensus

Rawls’s political turn is the result of his struggle with the problem of stability in his theory of justice. Rawls’s late solution uses the concept of public reason. It requires that the members of the well-ordered society should abide by a political conception of justice for shared public reasons, thus fostering an overlapping consensus. This solution has been criticized by post-Rawlsian scholars endorsing a Diversity-Convergence account of the stability problem. I complement Rawls’s model of public reason by arguing that the stability problem can be solved if members of the well-ordered society are community-based reasoners. This leads to a Wittgensteinian reinterpretation of the concept of public reason. This solution is only partial, however. At the bottom, stability without a minimal form of consensus is unlikely.

Multi-objective optimization of hydrant flushing in a water distribution system using a fast hybrid technique

As a critical element in preserving the health of urban populations, water distribution systems (WDSs) must be ready to implement emergency plans when catastrophic events such as contamination events occur. A risk-based simulation-optimization framework (EPANET–NSGA-III) combined with a decision support model (GMCR) is proposed in this study to determine optimal locations for contaminant flushing hydrants under an array of potentially hazardous scenarios. Risk-based analysis using Conditional Value-at-Risk (CVaR)-based objectives can address uncertainties regarding the mode of WDS contamination, thereby providing a robust plan to minimize the associated risks at a 95% confidence level. Conflict modeling by GMCR achieved an optimal compromise solution within the Pareto front by identifying a final stable consensus among the decision-makers involved. A novel hybrid contamination event grouping-parallel water quality simulation technique was incorporated into the integrated model to reduce model runtime, the main deterrent in optimization-based methods. The nearly 80% reduction in model runtime made the proposed model a viable solution for online simulation-optimization problems. The framework's capacity to address real-world problems was evaluated for the WDS operating in Lamerd, a city in Fars Province, Iran. Results showed that the proposed framework was capable of highlighting a single flushing strategy, which not only optimally reduced risks associated with contamination events, but provided acceptable coverage against such threats, flushing 35–61.3% of input contamination mass on average, and reducing average time-to-return to normal conditions by 14.4–60.2%, while employing less than half of the initial potential hydrants.

Quantitative approaches in multimodal fundus imaging: State of the art and future perspectives.

When it first appeared, multimodal fundus imaging revolutionized the diagnostic workup and provided extremely useful new insights into the pathogenesis of fundus diseases. The recent addition of quantitative approaches has further expanded the amount of information that can be obtained. In spite of the growing interest in advanced quantitative metrics, the scientific community has not reached a stable consensus on repeatable, standardized quantitative techniques to process and analyze the images. Furthermore, imaging artifacts may considerably affect the processing and interpretation of quantitative data, potentially affecting their reliability. The aim of this survey is to provide a comprehensive summary of the main multimodal imaging techniques, covering their limitations as well as their strengths. We also offer a thorough analysis of current quantitative imaging metrics, looking into their technical features, limitations, and interpretation. In addition, we describe the main imaging artifacts and their potential impact on imaging quality and reliability. The prospect of increasing reliance on artificial intelligence-based analyses suggests there is a need to develop more sophisticated quantitative metrics and to improve imaging technologies, incorporating clear, standardized, post-processing procedures. These measures are becoming urgent if these analyses are to cross the threshold from a research context to real-life clinical practice.

Experts' opinions about lasting innovative technologies in City Logistics

The COVID-19 pandemic has highlighted the relevance of goods delivery in urban areas. However, this activity often generates negative environmental impact and several technologies have been proposed in recent years to reduce it, thus forming a complex innovation landscape characterized by different levels of maturity and effects on the City Logistics (CL) system. This complexity causes a deep uncertainty over the future of CL. This paper aims to tackle this uncertainty by forecasting the future of a set of CL technologies. A Delphi survey has been submitted to experts of this field to achieve a stable consensus over 33 projections related to 7 CL technologies for the year 2030. Results show that real-time data collection will help the coordination process between stakeholders, engendering an increased awareness over the value of using logistics data as well as its potential drawbacks. Moreover, experts share a positive attitude towards the expansion of Parcel Lockers, which should be monitored by public authorities to avoid a negative impact on land use. Finally, technologies such as drones and crowd-logistics have drawn the lowest level of consensus due to their lower level of maturity, which arouse the necessity to further explore several issues such as legal and technical barriers.

The Paradigm Shift of Danish Development Policy (1990–2020)

For decades, Danish Development Policy was characterized by continuity, backed, as it was, by a relatively stable consensus across the political spectrum. However, this changed in the new Millennium where a paradigm shift in Danish development policy took place. This article characterizes and explains the paradigm shift and identifies its main driving forces. Drawing on Peter Hall’s policy paradigm framework, I identify development policy changes as a first, second, as well as a third order change, which constitutes a fundamental paradigm shift. Aid has been cut by almost a third, and the composition of instruments has changed with reduced allocations to bilateral country programmes, reduced allocations to the poorest and most stable countries, and increased allocations to humanitarian aid and areas of origin of migrants. Other purposes such as e.g. security concerns, global climate mitigation, or reducing migration flows, have to a large extent substituted the longstanding main objective of poverty reduction. International events and tendencies are of course important factors in explaining these significant development policy shifts, but domestic driving forces are equally important and consist mainly in a politicization of development aid enabled by a prior shift in policy-arena, both driven by domestic coalition politics. The politicization happened when a centre-right government was elected in 2001 and enabled a paradigm shift that happened over the 00s and which has been consolidated by the Social democratic minority government since 2019.

Two-level consensus modeling with utility and cost constraints

There exist many two-level group consensus problems with different psychological behaviors of decision makers. To deal with these group consensus problems and reach a stable consensus, based on the principles and methods of grey system, utility theory and group consensus, we use grey utility function to describe and reflect decision makers' opinion preferences in different subgroups and different levels, and then we construct a two-level group consensus method with a moderator, and exploit it to solve the negotiation problems of the natural gas subsidy.

Rapid SARS-CoV-2 Adaptation to Available Cellular Proteases.

ABSTRACTRecent emergence of SARS-CoV-1 variants demonstrates the potential of this virus for targeted evolution, despite its overall genomic stability. Here we show the dynamics and the mechanisms behind the rapid adaptation of SARS-CoV-2 to growth in Vero E6 cells. The selective advantage for growth in Vero E6 cells is due to increased cleavage efficiency by cathepsins at the mutated S1/S2 site. S1/S2 site also constitutes a heparan sulfate (HS) binding motif that influenced virus growth in Vero E6 cells, but HS antagonist did not inhibit virus adaptation in these cells. The entry of Vero E6-adapted virus into human cells is defective because the mutated spike variants are poorly processed by furin or TMPRSS2. Minor subpopulation that lack the furin cleavage motif in the spike protein rapidly become dominant upon passaging through Vero E6 cells, but wild type sequences are maintained at low percentage in the virus swarm and mediate a rapid reverse adaptation if the virus is passaged again on TMPRSS2+ human cells. Our data show that the spike protein of SARS-CoV-2 can rapidly adapt itself to available proteases and argue for deep sequence surveillance to identify the emergence of novel variants.IMPORTANCE Recently emerging SARS-CoV-2 variants B.1.1.7 (alpha variant), B.1.617.2 (delta variant), and B.1.1.529 (omicron variant) harbor spike mutations and have been linked to increased virus pathogenesis. The emergence of these novel variants highlights coronavirus adaptation and evolution potential, despite the stable consensus genotype of clinical isolates. We show that subdominant variants maintained in the virus population enable the virus to rapidly adapt to selection pressure. Although these adaptations lead to genotype change, the change is not absolute and genomes with original genotype are maintained in the virus swarm. Thus, our results imply that the relative stability of SARS-CoV-2 in numerous independent clinical isolates belies its potential for rapid adaptation to new conditions.

Opinion Dynamics on the Sphere for Stable Consensus and Stable Bipartite Dissensus

In this paper, we develop a multi-agent model for opinion dynamics that offers rich behaviors of opinion formations. The states of the model are the opinions of the agents which are designed to evolve on a unit-sphere. The model is novel in that the input to the system is designed based on a correlation matrix of the opinions of neighboring agents. Interestingly, the model demonstrates both stable consensus as well as stable bipartite dissensus behaviors using an unsigned communication graph. This is different than existing results where stable dissensus can only be achieved via a signed graph. We present various stability results about the different equilibrium configurations. Additionally, we provide simulation results for a 2-dimensional system demonstrating the different resulting behaviors of the system.

Афганистан и новая международная конфигурация в Азии

The development of the international political changes in Central and South Asia is analyzed in the article in connection with the consequences of the withdrawal of foreign troops from Afghanistan and the Taliban’s second rise to power (the first one was in 1996). It is shown that the peaceful transformation of Afghanistan is impeded by such persistent threats as religious extremism, terrorism, illegal drug trafficking. The complex mosaic of regional relations, in which Afghanistan is becoming an important element due to the changes that have happened in this country, is determined in Asia by the growing rivalry and competitive struggle of major economic states of the region, as well as global players, and by the efforts of all of them to build various international coalitions (Shanghai Cooperation Organization, RIC – Russia, India, China; Quadripartite Security Dialogue – QUAD, C5+1, Organization of Turkic States, etc.). Of particular interest in this regard is the position of the neighboring states – the three Central Asian nations (Tajikistan, Uzbekistan, Turkmenistan), as well as China, Pakistan, India and Iran. Apart from that, this study also outlines the most important challenges for the national security interests of Afghanistan’s Asian neighbors. An optimal scenario for both Afghanistan’s Asian neighbors and Russia would imply achieving a stable consensus in this country. Afghanistan becoming a full member of such an influential international bloc as the Shanghai Cooperation Organization, where Russia, Central Asian states and major Asian economic powers are already represented, can have positive consequences for the stabilization of the situation in the country and the whole Asian region. This would create favorable conditions for successful economic and political interaction between the Central and South Asian states. In conclusion the author emphasizes that the transformations in Afghanistan have complicated regional challenges, prompting neighboring states to focus on the military-political component of their security. Aiming to prevent a negative scenario in Afghanistan, they also multiplied diplomatic contacts with the current leadership of the country. The new international political configuration that is emerging in modern Asia dictates new approaches in the security sphere for the Asian states.

Targeting OLFML3 in Colorectal Cancer Suppresses Tumor Growth and Angiogenesis, and Increases the Efficacy of Anti-PD1 Based Immunotherapy.

Simple SummaryTumor vascularization promotes tumor growth and is intimately connected to immune system function. Despite efforts to use antiangiogenic therapies, their clinical effects are less pronounced than expected. Compensatory angiogenic responses and resistance to treatment are responsible for these limited therapeutic effects. Inhibition of OLFML3 suppresses the growth of colorectal cancer in preclinical models. Our study identified OLFML3 as a key regulator of angiogenesis, lymphangiogenesis, pericyte coverage, tumor-associated macrophage recruitment, and enhanced NKT lymphocyte recruitment associated with its antitumor effects. We also highlight that OLFML3 antibodies increase the efficacy of anti-PD-1-based therapies. These results are in agreement with the high expression of OLFML3 observed in colorectal carcinoma patients associated with shorter relapse-free survival, higher grade, and angiogenic microsatellite stable (CMS4) subtype. Clinically, high OLFML3 expression correlates with reduced disease-free survival in human colorectal cancer patients, suggesting a potential role as a therapeutic target.The role of the proangiogenic factor olfactomedin-like 3 (OLFML3) in cancer is unclear. To characterize OLFML3 expression in human cancer and its role during tumor development, we undertook tissue expression studies, gene expression analyses of patient tumor samples, in vivo studies in mouse cancer models, and in vitro coculture experiments. OLFML3 was expressed at high levels, mainly in blood vessels, in multiple human cancers. We focused on colorectal cancer (CRC), as elevated expression of OLFML3 mRNA correlated with shorter relapse-free survival, higher tumor grade, and angiogenic microsatellite stable consensus molecular subtype 4 (CMS4). Treatment of multiple in vivo tumor models with OLFML3-blocking antibodies and deletion of the Olfml3 gene from mice decreased lymphangiogenesis, pericyte coverage, and tumor growth. Antibody-mediated blockade of OLFML3 and deletion of host Olfml3 decreased the recruitment of tumor-promoting tumor-associated macrophages and increased infiltration of the tumor microenvironment by NKT cells. Importantly, targeting OLFML3 increased the antitumor efficacy of anti-PD-1 checkpoint inhibitor therapy. Taken together, the results demonstrate that OLFML3 is a promising candidate therapeutic target for CRC.

Hybrid genetic model for clustering ensemble

Clustering ensemble has received considerable research interest and led to a proliferation of studies, since it has great capabilities to combine multiple base clusters to generate a more robust and stable consensus result. Genetic algorithms are optimization methods which can search heuristically by simulating the natural evolution process with highly parallel and adaptive characteristics. However, to our knowledge, there are very few existing methods using a genetic model to solve clustering ensemble problems. In this paper, a novel hybrid genetic model for clustering ensemble (HGMCE) is proposed innovatively, and the corresponding objective function is designed. Each base clustering is regarded as a new attribute of data, and the result of clustering ensemble can be evaluated by the objective function. Then the proposed model can be inferred with the optimization, combination, and transcendence of base clustering results step by step, which makes it possible to maintain the diversity of the population and provides more possibilities to avoid falling into the local optimal solution. Furthermore, an algorithm named HGCEA corresponding to the proposed model is designed to solve the clustering ensemble problem. To evaluate the potential of HGCEA, extensive experiments are carried out on ten real datasets, including comparison with clustering groups and clustering ensemble groups. The results of accuracy and normalized mutual information demonstrate the superiority of the proposed algorithm in integrating effective clustering over the state-of-the-art.