Biomedical Experiments Research Articles

Hybridization of Machine Learning Model with Bee Colony based Feature Selection for Medical Data Classification

Nowadays, an important count of biomedical data is created continuously in several biomedical equipment and experiments because of quick technical enhancements in biomedical science. The study of clinical and health data is vital to enhance the analysis precision, prevention, and treatment. Initial analysis and treatment are extremely important approaches for preventing deaths in many diseases. Accordingly, the data mining and machine learning (ML) approaches are helpful tools for utilizing minimization error and for providing helpful data for analysis. But the data obtained in digital machines takes higher dimensionality, and not every data attained in digital machines is significant to specific diseases. This article develops an artificial bee colony-based feature selection with optimal hybrid ML model for medical data classification (ABCFS-OHML) technique. The presented ABCFS-OHML technique mainly aims to identify and classify the presence of disease using medical data. To attain this, the presented ABCFS-OHML technique initially pre-processes the input data in two ways namely null value removal and data transformation. Furthermore, the presented ABCFS-OHML technique uses ABCFS model for the choice of effectual subset of features. At last, root means square propagation with convolutional neural network-Hop field neural network (CNN-HFNN) model for classification purposes. The usage of RMSProp optimizer assists in attaining optimal hyperparameter selection of the CNN-HFNN method. The performance validation of the ABCFS-OHML technique takes place using three medical datasets. The comparison study reported that the ABCFS-OHML technique has accurately classified the medical data over other recent approaches.

THE CONCEPT OF THE SYSTEM OF LEGAL PROTECTION OF OBJECTS WILDLIFE AS A RESULT OF INTELLECTUAL ACTIVITY

The problems of the legal regime of the results of creative activity related to wildlife and humans have acquired special scientific significance and practical value in many countries, including Russia and Kazakhstan. Therefore, research on the development of concepts for the adaptation of the intellectual property law system as a sub-branch of civil law, the definition of the legal regime of new wildlife objects resulting from intellectual activity, and their integration into the already existing legal system, have a strategic level of state tasks aimed at achieving a balance of public and private interests, especially in the field of biomedical technologies and genomic experiments that create very significant risks not only for the living humanity, but also for future generations. Taking into account the above, this article presents the results of a scientific analysis conducted in order to develop a theoretical concept for building a system of legal protection of wildlife objects as the results of intellectual activity and to make proposals for improving legislation in the field of intellectual property law. Based on the results of the study, it is proposed to modernize the system of law in the field of intellectual property in terms of objects of wildlife, including new objects in addition to existing breeding achievements, namely: strains of microorganisms, genetically modified organisms, biomedical cell products, genomes, and other results of intellectual activity created using human and animal biomaterials, including birds, fish and other representatives of fauna, and provide them with an independent legal regime. The revision of the last object "other results ..." allows you to leave the list of wildlife objects open in order, if necessary, to introduce another innovative object into the intellectual property system, providing it with an appropriate legal regime, without additional changes to the law.

Современные биоэтические проблемы в контексте основных принципов буддийской этики

The relevance of this research consists in reconsideration of the main approaches to solving bioethical problems based on the religious and ethical principles of Buddhism. The purpose of this research is to analyze Buddhist principles that can be consistently applied to a range of biomedical problems (euthanasia, biomedical experiments with animals, etc.). The subject of our research is ethics in the context of medicine, namely the relationship between Buddhism and medical practice. The research materials are based on many years of teaching the bioethics course at St. Petersburg State University of Chemistry and Pharmacy and Tyumen State Medical University, as well as on the results of research related to the development of scientific research of bioethical issues. The central question of modern bioethics about the nature and status of the moral subject in Buddhism is based on the principle of the moral dignity of all living beings: from human life to the life of animals and, perhaps, even plants. Belief in interspecific rebirth and respect for animal life are typical of Buddhist ethics. In modern ethics, Buddhism is a teleological ethics of virtue, which postulates a certain end result of life as the implementation of human potential and asserts that this goal should be realized through cultivation of certain spiritual practices, which implies the rejection of euthanasia, abortion, artificial insemination and other dvanced medical technologies.

An Open-Source 3D-Printed Recording Stage with Customizable Chambers for Ex Vivo Experiments.

Much of what has been discovered concerning neurophysiological mechanisms can be credited to ex vivo biomedical experiments. Beyond these discoveries, ex vivo research techniques have enhanced the global understanding of human physiology and pathology in almost every biomedical specialty. Naturally, ex vivo experiments are among the most desired methods of research, particularly in the field of neuroscience. Ex vivo experiment platforms may be purchased commercially. However, their substantial cost and sometimes limited availability can render them inaccessible to many research labs. Moreover, these manufactured systems are often rigid in function with no possibility of customization, severely narrowing their capabilities. However, developing essential components for ex vivo laboratory systems with a fused deposition modeling printer provides a practical solution to each of these obstacles. Here, we provide the designs and construction process for an easily accessible, highly adaptable recording stage with modifiable submersion chambers using a 3D printer for a total cost under $15.00. With the versatility afforded by the exchangeable custom chambers, the system may be used to conduct research on a variety of ex vivo tissue preparations, paving the way for novel research.

Perspectives on Conservation Impacts of the Global Primate Trade

The global trade in nonhuman primates represents a substantial threat to ecosystem health, human health, and primate conservation worldwide. Most of the primate trade involves trade for pet-keeping, consumption, or biomedical experimentation. We present an overview of international primate trade through five case studies; each describes a different facet of this trade. We draw on published scientific literature, media outlets, and open access datasets, including the CITES Trade Database to build these case studies. Case study 1 describes the role of introduced island populations of Macaca and Chlorocebus in trade for biomedical experimentation; case study 2 covers the global health threats posed by the primate trade, including zoonotic disease transmission once animals enter the trade pipeline; case study 3 addresses the ways that changing patterns of primate trade, from local markets to online, have increased the demand for primates as pets; case study 4 recognizes the role that local environmental activism can play in mitigating trade; and case study 5 shows variation between global regions in their contribution to the primate trade. We recommend greater oversight of primate trade, especially domestic trade within primate range countries, and real-time reporting to CITES to accurately track primate trade. Effective conservation-focused regulations that can minimise the negative effects of primate trade must be tailored to specific regions and species and require transparency, careful regulation, field research, and an understanding of the magnitude of this trade.

Nonparametric tests for combined location-scale and Lehmann alternatives using adaptive approach and max-type metric

The paper deals with the classical two-sample problem for the combined location-scale and Lehmann alternatives, known as the versatile alternative. Recently, a combination of the square of the standardized Wilcoxon, the standardized Ansari–Bradley and the standardized Anti-Savage statistics based on the Euclidean distance has been proposed. The Anti-Savage test is the locally most powerful rank test for the right-skewed Gumbel distribution. Furthermore, the Savage test is the locally most powerful linear rank test for the left-skewed Gumbel distribution. Then, a test statistic combining the Wilcoxon, the Ansari–Bradley, and Savage statistics is proposed. The limiting distribution of the proposed statistic is derived under the null and the alternative hypotheses. In addition, the asymptotic power of the suggested statistic is investigated. Moreover, an adaptive test is proposed based on a selection rule. We compare the power performance against various fixed alternatives using Monte Carlo. The proposed test statistic displays outstanding performance in certain situations. An illustration of the proposed test statistic is presented to explain a biomedical experiment. Finally, we offer some concluding remarks.

Optimisation of the composition of safe dental gel with IL-1β antagonist for the treatment of inflammatory periodontal diseases

Aim. The study aims to develop the composition of the oromucosal gel with the IL-1β interleukin antagonist for complex treatment of inflammatory periodontal diseases. Materials and methods. Experimental studies were conducted based on the Department of Medicines Technology of Zaporizhzhia State Medical and Pharmaceutical University and the Training Medical and Laboratory Center of Zaporizhzhia State Medical and Pharmaceutical University of the Ministry of Health of Ukraine. As an active component, in the recipe of oromucosal gel, used antagonist of the interleukin IL-1B. Excipients: D-panthenol (the plasticizer), carboxymethylcellulose sodium salt (the viscosity modifier and mucoadhesive component), Tween-80 (the enhancer absorption), benzalkonium chloride (the preservative), sodium hydrophosphate + citric acid (the phosphate buffer solution), purified water. The experiments used existing and auxiliary ingredients of pharmaceutical purity, which were obtained from Sinbias LLC, Istok-Plus LLC, LLC “Mobile Medical”. For the design of the experiment, the methodology of the response surface (Box-Behnken Design) is used: Na CMC, Tween-80, D-panthenol; and four answers: pH, viscosity test, system type, mucoadhesive properties. Research methods: rheological research (viscosity test, amplitude test, frequency test, mucoadhesive test, thixotropy test) performed in oscillation mode on the modular compact Rheometer Anton Paar MCR 302 (CP50-1 SN71317), which, compared to cylindrical devices, requires a much smaller amount of gel sample and allows the planned tests in the oscillation mode, the temperature in the experiments was provided with a built-in thermostat (Peltier Temperature Control, C-PTD 200). Pharmaco-toxicological studies were conducted on 46 white outbred rats of both sexes, weighing 160–180 grams, which were received from Vivarium by the Institute of Pharmacology and Toxicology. The studies were performed on enough animals, all manipulations were carried out by the provisions on the use of animals in biomedical experiments. The results of the study were calculated using the standard statistical package of the Statistica for Windows 13 (StatSoft Inc., No. JPZ804I382130ARCN10-J), as well as SPSS 16.0, Microsoft Office Excel 2003. Results. According to the design of the experiment, it is established that the components of the system do not change the value of pH in experimental oromucosal gels (6.5500 ± 0.0334). The Anova for Quadratic Model statistical analysis data certify the significant impact of Na CMC, and Tween-80 factors on the viscous characteristics of oromucosal gels (F-value > p-value). Comparison of mucoadhesive characteristics of the studied samples of oromucosal gels was made using dynamic mechanical analysis and the results of statistical analysis of ANOVA for Quadratic Model highlight the significant influence of Na CMC, D-panthenol, Tween-80. Optimized oromucosal gel test data is obtained that its structure is restored after the applied effort, namely the restoration of the structure after 10 seconds occurs by 69.5 %, after 30 s by 76.1 %, after 180 s by 85.4 %, after 180 s which allows to predict the stability of the dosage form, both after manufacture and after use. Conclusions. The composition of the oromucosal gel of anti-inflammatory action with the IL-1β interleukin antagonist for the complex treatment of inflammatory diseases of periodontal is developed. The optimized composition of the oromucosal gel obtained has satisfactory performance of kinetic stability and thixotropic properties. The developed gel for dentistry meets all the requirements for harmlessness and safety for dosage forms of this group toxicity, lack of local irritant and allergic action.

Incorporating high-frequency information into edge convolution for link prediction in complex networks

Link prediction in complex networks aims to mine hidden or to-be-generated links between network nodes, which plays a significant role in fields such as the cold start of recommendation systems, knowledge graph completion and biomedical experiments. The existing link prediction models based on graph neural networks, such as graph convolution neural networks, often only learn the low-frequency information reflecting the common characteristics of nodes while ignoring the high-frequency information reflecting the differences between nodes when learning node representation, which makes the corresponding link prediction models show over smoothness and poor performance. Focusing on links in complex networks, this paper proposes an edge convolutional graph neural network EdgeConvHiF that fuses high-frequency node information to achieve the representation learning of links so that link prediction can be realized by implementing the classification of links. EdgeConvHiF can also be employed as a baseline, and extensive experiments on real-world benchmarks validate that EdgeConvHiF not only has high stability but also has more advantages than the existing representative baselines.

An efficient approach for identifying important biomarkers for biomedical diagnosis

In this paper, we explore the challenges associated with biomarker identification for diagnosis purpose in biomedical experiments, and propose a novel approach to handle the above challenging scenario via the generalization of the Dantzig selector. To improve the efficiency of the regularization method, we introduce a transformation from an inherent nonlinear programming due to its nonlinear link function into a linear programming framework under a reasonable assumption on the logistic probability range. We illustrate the use of our method on an experiment with binary response, showing superior performance on biomarker identification studies when compared to their conventional analysis. Our proposed method does not merely serve as a variable/biomarker selection tool, its ranking of variable importance provides valuable reference information for practitioners to reach informed decisions regarding the prioritization of factors for further investigations.

Integrating Microfluidic and Biosensors: A Mini Review

In recent years, the field of analytical research has witnessed a significant transformation driven by the emergence of integrated microfluidic sensors. This ground-breaking technology has been extensively studied, resulting in the resolution of diverse challenges and a revolutionary impact on experiments, particularly in the biomedical domain. By combining the biosensors with microfluidics, there is a tremendous potential to enhance measurement accuracy and expand the capacity of specimens utilized in biomedical applications and experiments. The integration of biosensors with microfluidics enables effective sample separation, precise control over chemical reactions, and the measurement of various critical parameters. Furthermore, the primary objective of this research is to identify gaps in the existing literature concerning integrated microfluidic sensors. This pursuit involves employing comprehensive bibliometric analysis and conducting a systematic literature review of Scopus-indexed publications that are relevant to the field of integrated microfluidic sensors. PRISMA method was being used to filter the documents that are gathered from Scopus database. The outcomes of this study underscore the pressing need for further research in leveraging electrochemical sensors for specimen analysis by integrating them with the advanced technique of microfluidics. The paper emphasizes the significance of continuous research and development efforts in the realm of integrated microfluidic sensors to fully exploit the potential of electrochemical sensors and enhance the overall research process.

On the (Apparently) Paradoxical Role of Noise in the Recognition of Signal Character of Minor Principal Components

The usual method of separating signal and noise principal components on the sole basis of their eigenvalues has evident drawbacks when semantically relevant information ‘hides’ in minor components, explaining a very small part of the total variance. This situation is common in biomedical experimentation when PCA is used for hypothesis generation: the multi-scale character of biological regulation typically generates a main mode explaining the major part of variance (size component), squashing potentially interesting (shape) components into the noise floor. These minor components should be erroneously discarded as noisy by the usual selection methods. Here, we propose a computational method, tailored for the chemical concept of ‘titration’, allowing for the unsupervised recognition of the potential signal character of minor components by the analysis of the presence of a negative linear relation between added noise and component invariance.

Generalized Jaccard feature screening for ultra-high dimensional survival data

<p>To identify critical genomes that influence a cancer patient's survival time, feature screening methods play a vital role in this biomedical field. Most of the current research relies on a fixed survival function model, which limits its universality in practical applications. In this paper, we propose the Generalized Jaccard coefficient (GJAC), which extends the traditional Jaccard coefficient from comparing binary vectors' similarity to calculating the correlation between the general vectors. The larger the GJAC value, the higher the sample similarity. Using the GJAC, we introduce a novel model-free screening method to select the active set of covariates in ultra-high dimensional survival data. Through Monte Carlo simulations, GJAC-Sure Independence Screening (GJAC-SIS) shows a higher accuracy, lower errors, and an excellent applicability in different types of survival data compared with other existing model-free feature screening methods in survival data. Additionally, in the real cancer datasets (DLBCL), GJAC-SIS can screen out two additional important genomes, which are certified in the real biomedical experiment, while the other five methods can't. As a result, GJAC-SIS achieves a high screening precision, delivers a more effective screening outcome, and has a better utility and universality.</p>

Streptozotocin induced hyperglycaemia in the invertebrate diabetic model Bombyx mori

AbstractWorldwide spread in the incidence of diabetes justified the need of extensive research in an appropriate model system to develop an effective treatment strategy for diabetology. In recent years, because of animal ethical issues and limitations, the silkworm (Bombyx mori) has emerged as a perfect invertebrate model for various biomedical experiments. However, there are several issues related to induce hyperglycaemia in the mammalian system that have not been studied in the silkworms. In the present study, we investigated the consequences of induced hyperglycaemia by oral and intravascular administration of streptozotocin (STZ) and glucose in the silkworms. Interestingly, results confirmed the competence of STZ to induce hyperglycaemia when administered through intravascular route, but suppress the glucose concentration if administrated orally in the silkworms. Comparatively, the severity of induced hyperglycaemia in the silkworms remained nearly the same in response to the oral and intravascular administration of glucose. Furthermore, prolonged administration of STZ has recorded negative effect on the growth rate of the silkworms, whereas a drastic decline in the same was reported in the silkworms administered with glucose. Notably, these results confirm that the response shown by the silkworms to STZ is very similar to that of mammals, making it an excellent model to study diabetic complications and consequences associated with STZ in diabetology.

Neuroethics, Neuroscience and Neurohacking: Legal Foundations of the Medical Experiment on <i>Terra Incognita</i>

The results of complex and interdisciplinary research conducted at the intersection of legal and medical sciences allow us to create new points of support for the development of innovative technologies. One of the controversial ways to treat neurological pathology is neurohacking. Experimental intervention in the human brain can not only be of a positive therapeutic nature, but also harm the triad of human—society—state security. The main purpose of the paper is to highlight the latest achievements of neuroscience, focusing on the insufficiency of legal regulation of medical experiment in the Russian Federation. Justification of the need for medical research on the higher nervous system is possible only after a thorough analysis of the clinical situation, taking measures to prevent harm to the health of a particular patient, eliminating the impact on an unspecified group of people, as well as motivating the exclusivity of the task, assessing all legal and biological risks. The paper presents the stages of the origin and development of neuroethics in the country, substantiates the close relationship of neuroscience with the bioethical component, proposes the author’s classification of neurohacking, identifies the legal threats of criminal influence on the human body, and provides an argument for the likelihood of using bioengineering technologies to create bioweapons. The conclusions drawn in the work can be further used in the process of formulating normative legal acts regulating the issues of biomedical experiment and the Provisions on the expert council on bio (neuro) ethics.

MNCLCDA: predicting circRNA-drug sensitivity associations by using mixed neighbourhood information and contrastive learning

BackgroundcircRNAs play an important role in drug resistance and cancer development. Recently, many studies have shown that the expressions of circRNAs in human cells can affect the sensitivity of cells to therapeutic drugs, thus significantly influencing the therapeutic effects of these drugs. Traditional biomedical experiments required to verify this sensitivity relationship are not only time-consuming but also expensive. Hence, the development of an efficient computational approach that can accurately predict the novel associations between drug sensitivities and circRNAs is a crucial and pressing need.MethodsIn this research, we present a novel computational framework called MNCLCDA, which aims to predict the potential associations between drug sensitivities and circRNAs to assist with medical research. First, MNCLCDA quantifies the similarity between the given drug and circRNA using drug structure information, circRNA gene sequence information, and GIP kernel information. Due to the existence of noise in similarity information, we employ a preprocessing approach based on random walk with restart for similarity networks to efficiently capture the useful features of circRNAs and drugs. Second, we use a mixed neighbourhood graph convolutional network to obtain the neighbourhood information of nodes. Then, a graph-based contrastive learning method is used to enhance the robustness of the model, and finally, a double Laplace-regularized least-squares method is used to predict potential circRNA-drug associations through the kernel matrices in the circRNA and drug spaces.ResultsNumerous experimental results show that MNCLCDA outperforms six other advanced methods. In addition, the excellent performance of our proposed model in case studies illustrates that MNCLCDA also has the ability to predict the associations between drug sensitivity and circRNA in practical situations.ConclusionsAfter a large number of experiments, it is illustrated that MNCLCDA is an efficient tool for predicting the potential associations between drug sensitivities and circRNAs, thereby can provide some guidance for clinical trials.

Bioetika i geopolitika - rat u Ukrajini kao povod

The article mainly relies on original scientific papers, and reviews of a large number of bioethical works published from the end of the last century to the present day, but it primarily leans on the reviews, critical reflections and comments of the renowned Croatian philosopher Rade Kalanj. He rightfully warned some thirty years ago that biological and genetic research had reached a level ("a borderline situation"/Jaspers) where the question of the relationship between science and ethics is raised anew, but now in a much sharper and more radical form. Today, in light of the war in Ukraine, we would add: the relationship between bioethics and geopolitics. One of the severe consequences of the tragic events in Ukraine is the danger of exacerbating the already significant global hunger, in which, ultimately, it becomes less important whether food is natural/organic or GMO, but rather whether there is any food at all, primarily the grains. Or, on the contrary, there is an abundance of food, but only for those who have money to buy it, and their numbers are decreasing, so it remains to give them food. But in that case, the profits of global capitalism would be missing, which would certainly be unacceptable for the world's transnational elites and practically endanger the foundations of capitalism, marking the end of the global capitalist system/order. So, a major humanitarian catastrophe is looming, supplemented by millions of refugees, not only from Ukraine but also from around the world. This situation will be exacerbated by poor economic consequences, primarily for the EU and then for the whole world, all of which includes the UN and its specialised agencies, primarily UNHCR and UNESCO, in solving serious international problems, which certainly includes the issue of (un)acceptability of bioethical axioms for all civilisations and cultures. Among other things, the question arises as to who will be responsible/blamed for the global humanitarian catastrophe regarding the war in Ukraine: whether, as before, only Russia, or whether the list of accused will be expanded to include "Third World" countries, primarily China and Iran? Ahead of us lies a spectrum of bioethical questions, moral dilemmas, and temptations, especially when the existence of experimental biomedical laboratories on the territory of western Ukraine is revealed, reminiscent of the horrors of Nazi biomedical experiments in World War II.

LDA-VGHB: identifying potential lncRNA-disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine.

Long noncoding RNAs (lncRNAs) participate in various biological processes and have close linkages with diseases. In vivo and in vitro experiments have validated many associations between lncRNAs and diseases. However, biological experiments are time-consuming and expensive. Here, we introduce LDA-VGHB, an lncRNA-disease association (LDA) identification framework, by incorporating feature extraction based on singular value decomposition and variational graph autoencoder and LDA classification based on heterogeneous Newton boosting machine. LDA-VGHB was compared with four classical LDA prediction methods (i.e. SDLDA, LDNFSGB, IPCARF and LDASR) and four popular boosting models (XGBoost, AdaBoost, CatBoost and LightGBM) under 5-fold cross-validations on lncRNAs, diseases, lncRNA-disease pairs and independent lncRNAs and independent diseases, respectively. It greatly outperformed the other methods with its prominent performance under four different cross-validations on the lncRNADisease and MNDR databases. We further investigated potential lncRNAs for lung cancer, breast cancer, colorectal cancer and kidney neoplasms and inferred the top 20 lncRNAs associated with them among all their unobserved lncRNAs. The results showed that most of the predicted top 20 lncRNAs have been verified by biomedical experiments provided by the Lnc2Cancer 3.0, lncRNADisease v2.0 and RNADisease databases as well as publications. We found that HAR1A, KCNQ1DN, ZFAT-AS1 and HAR1B could associate with lung cancer, breast cancer, colorectal cancer and kidney neoplasms, respectively. The results need further biological experimental validation. We foresee that LDA-VGHB was capable of identifying possible lncRNAs for complex diseases. LDA-VGHB is publicly available at https://github.com/plhhnu/LDA-VGHB.

The Misrepresentation of Petri Dish, as “petri” Dish, in the Scientific Literature

The Petri dish is, without a doubt, a very basic, yet important and popular tool in microbiological and other biomedical experiments. It serves primarily as a support or structural platform for placing, growing or testing biological specimens, whether these be microbiological, animal, plant or human. Given its size, usually about 10 cm in diameter, the Petri dish is an ideal platform for cellular and tissue cultures. Despite the commonality of Petri dishes, quite surprisingly, there is a pervasive error throughout the biomedical literature, namely its misspelling as “petri” dish. This is not a trivial issue since this dish is named after a scientist, Julius Richard Petri (1852–1921), so the upper-case “P” should not be represented as a lower-case “p”. It is important to alert students and seasoned biomedical researchers, as well as the wider public, who might use this term, about the need to use the term Petri accurately, in order to respect its historical foundation. To garner some appreciation of the extent of this error in the biomedical literature, a 2022 search on PubMed for either “Petri dish” or “petri dish” revealed 50 search results, 24 (or 48%) of which were of the latter, erroneous form in titles or abstracts. This suggests that the indicated error, which is in need of correction, may be widely pervasive in the biomedical literature.

Экологический сетевой подход в приложении к биоэтическим организационным структурам

The term ‘bioethics’ (in the narrow sense) or ‘biomedical ethics’ denotes medical ethics at the modern stage of development. Bioethics is currently institutionalized and falls under the responsibility of specialized organizational structures (bioethics commissions, ‘divine committees’, etc.). The article expounds the prospects of applying network structures to institutions and organizations dealing with bioethical issues and tasks (ethical aspects of reproductive technologies, biomedical experiments, organ transplantation, and bioethical education). With the principles of decentralization (‘multiple authority’) and ecology (an integrative approach to issues under study and integrity of a bioethical expert team), network structures promote creative and effective functioning of bioethical organizations. Nonetheless, the centralized hierarchies of traditional educational and research institutions are also expected to perform essential functions. A reasonable combination of network structures and hierarchies provides the latter with a new role: the hierarchies assess the activity of emergent network structures using competent experts and provide selective support (including financing) to the most effective among them.

Identify potential circRNA-disease associations through a multi-objective evolutionary algorithm

More and more studies have demonstrated that circRNAs can be used as markers of various diseases due to their inherent stability. Numerous computational methods, especially artificial intelligence approaches, have been applied to the prediction of circRNA-disease associations. However, the objective functions of these prediction methods are usually single and standard. The single objective function hardly reflects the characteristics of the prediction problem, and leads to low prediction accuracy. There has never been a method to design a set of objective functions for the circRNA-disease prediction problem and solve it by using intelligent optimization algorithms. In this paper, a method ICDMOE is proposed to identify circRNA-disease associations via a multi-objective evolutionary algorithm. A solution space is defined and four objective functions are designed based on matrix factorization and modularity of similarity networks. An improved decomposition-based multi-objective evolutionary algorithm (MOEA/D) is also employed to solve these objective functions. In the MOEA/D, an adaptive penalty-based boundary intersection strategy is proposed, which not only ensures convergence, but also guarantees the diversity of solutions in the Pareto front. Finally, the experimental results show that ICDMOE has better performance than pure matrix factorization-based methods, non-adaptive MOEA/D-based methods and other prediction methods. Furthermore, we find that the predicted disease-circRNAs can be confirmed by existing studies, miRNA regulations and expression profiles, etc. These indicate that ICDMOE can provide good candidates for biomedical experiments.