Kvik: three-tier data exploration tools for flexible analysis of genomic data in epidemiological studies

Cryptococcus neoformans is an opportunistic human pathogenic fungus that causes meningoencephalitis. Due to the increasing global risk of cryptococcosis and the emergence of drug-resistant strains, the development of predictive genetics platforms for the rapid identification of novel genes governing pathogenicity and drug resistance of C. neoformans is imperative. The analysis of functional genomics data and genome-scale mutant libraries may facilitate the genetic dissection of such complex phenotypes but with limited efficiency. Here, we present a genome-scale co-functional network for C. neoformans, CryptoNet, which covers ~81% of the coding genome and provides an efficient intermediary between functional genomics data and reverse-genetics resources for the genetic dissection of C. neoformans phenotypes. CryptoNet is the first genome-scale co-functional network for any fungal pathogen. CryptoNet effectively identified novel genes for pathogenicity and drug resistance using guilt-by-association and context-associated hub algorithms. CryptoNet is also the first genome-scale co-functional network for fungi in the basidiomycota phylum, as Saccharomyces cerevisiae belongs to the ascomycota phylum. CryptoNet may therefore provide insights into pathway evolution between two distinct phyla of the fungal kingdom. The CryptoNet web server (www.inetbio.org/cryptonet) is a public resource that provides an interactive environment of network-assisted predictive genetics for C. neoformans.

Annotations of gene structures and regulatory elements can inform genome-wide association studies (GWASs). However, choosing the relevant annotations for interpreting an association study of a given trait remains challenging. I describe a statistical model that uses association statistics computed across the genome to identify classes of genomic elements that are enriched with or depleted of loci influencing a trait. The model naturally incorporates multiple types of annotations. I applied the model to GWASs of 18 human traits, including red blood cell traits, platelet traits, glucose levels, lipid levels, height, body mass index, and Crohn disease. For each trait, I used the model to evaluate the relevance of 450 different genomic annotations, including protein-coding genes, enhancers, and DNase-I hypersensitive sites in over 100 tissues and cell lines. The fraction of phenotype-associated SNPs influencing protein sequence ranged from around 2% (for platelet volume) up to around 20% (for low-density lipoprotein cholesterol), repressed chromatin was significantly depleted for SNPs associated with several traits, and cell-type-specific DNase-I hypersensitive sites were enriched with SNPs associated with several traits (for example, the spleen in platelet volume). Finally, reweighting each GWAS by using information from functional genomics increased the number of loci with high-confidence associations by around 5%.

A CEBPB/IL-1β/TNF-α feedback loop drives drug resistance to venetoclax and MDM2 inhibitors in monocytic leukemia.

The effects of petroleum hydrocarbons on lipid metabolism and energetics of larval development and metamorphosis in the american lobster (homarus americanus Milne Edwards)

Nutrition supports social insect colonies by regulating both individual performance and colony growth. In honey bee colonies, task-related behaviors such as nursing and foraging are partially mediated by nutrition. Young workers (nurses) consume almost all of the pollen in the hive, while foragers consume mostly nectar. Pollen provides vital proteins and lipids, consumed by nurse bees for approximately 1week post-eclosion. The role that lipids play in the physiology and behavior of adult bees is gaining significant attention. Recent research suggests that diets with balanced ratios of fatty acids increase olfactory learning in honey bees. Olfaction is crucial for young worker bees to perform brood care and cell cleaning behaviors, which is important for hive health and disease control. Thus, we targeted the early adult, pollen-feeding stage to examine how fatty acids affect cognition to hive-relevant odors. We fed young workers (days 0-9) diets balanced or unbalanced in their ratio of essential fatty acids (ω-6:3) sourced from pollen or cooking oils. We then measured their ability to learn healthy and damaged brood odors, as well as their ability to discriminate between the two. Workers fed balanced diets could learn and discriminate between brood odors better than workers fed unbalanced diets. Consumption of both diet types decreased with age, but their cognitive effects remained. These results suggest that diet affects young worker cognitive development, which may affect task-related behaviors and colony hygiene.

Web application development from simple web pages to complex interactive platforms (including social networks, e-commerce systems, corporate portals) requires new approaches, tools and technologies. JavaScript libraries and frameworks play a special role in developing web applications, simplifying the creation of effective, scalable, and convenient interfaces. The purpose of the article is to research the problems and prospects of using React in combination with Redux when creating web applications with a complex structure, to assess the advantages of their joint use in comparison with similar tools and to develop the web application “FarmerProducts”. The research methodology consists of the main methodological approaches and technological tools for developing web applications. Such methods, in particular, are: system and comparative analysis – to identify the features of creating web applications; method of expert assessments, which involves the study of literary sources and information resources, conducting interviews and surveys of experts, as well as the processes of developing and testing scalable and high-performance web applications based on the use of React and Redux. The scientific novelty of the research is the analysis of modern tools (React, Angular, Vue. js) for developing web applications, identifying problems and prospects for their use, creating an author’s web application (using React and Redux), which includes an intuitive interface, a flexible database, simplifying the process of working with the application by using a stack of modern technologies. Conclusions. The paper analyses the problems and prospects of using modern web application development tools; focuses on React, which is suitable for different projects; conducts a comparative analysis of React with Angular, Vue. js and Svelte, identifies their main characteristics, advantages, disadvantages; demonstrates the dependence of the choice of tools on the project context (React in combination with Redux can provide an optimal balance between performance, flexibility and scalability); describes the author’s web application – the FarmerProducts online store; identifies further ways to improve this web application.

Concentration and ratio of essential fatty acids influences the inflammatory response in lipopolysaccharide challenged mice

Abstract—In this article I have deployed a web-based applica- tion to Docker using Amazon web service (EC2 Instance). Elastic Cloud Compute service is used to the run the docker applications on scalable clusters. Amazon EC2 is fully managed and secured Container orchestration service that makes to deploy, manage and scale Dockerized web application. Docker containers on an EC2 instance to run a university management system website on the Amazon Web Services (AWS) cloud. For educational institutions, a university management system is a crucial tool that enables administrators to manage student records, course information, and other crucial data. The introduction to Docker, a containerization technology that makes it simple to build and manage web applications, follows a discussion of the advantages of hosting a university management system website on the cloud. The next section of the paper focuses on the AWS EC2 service and its capabilities, such as its capability for flexible computing and scalability. The paper also offers a step-by-step tutorial on how to use Docker to deploy a university administration system website on an EC2 instance, including instructions on how to set up the EC2 instance, install and configure Docker, and deploy the website code in a Docker container. Elastic Load Balancer and Auto Scaling, two AWS services, are used in the process of setting up security and scalability for the website. The benefits of using Docker to host a university administration system website on AWS EC2 are outlined in the paper’s conclusion, along with predictions for the development of cloud-based web application hosting. This research paper offers a thorough overview of the steps involved in hosting a university management system website using Docker on AWS EC2, making it a useful tool for educational institutions looking to improve their information management procedures and take advantage of cloud computing and Docker- Containerization.

High throughput experimental technologies, also called "omics" technologies, generate considerable amounts of data. Research laboratories can approach their scientific questions from an "omics" perspective. In this context, they can either generate new experimental data or collect published data among the one already available in the public databases (SRA, GEO, PRIDE, etc.). One experimental data are collected, the challenge remains to analyse them and also to integrate them to answer the initial scientific question. This is a clear challenge from an informatic, statistical and methodological point of view. Indeed, many analyses can be performed on a single experimental data set, using multiple bioinformatics tools or softwares, with different sets of parameters. Therefore, the issues of annotation, storage, mining and integration of multi-omics data analysis results is an important challenge in biology. In our laboratory, our aim is to perform an in silico modeling of iron metabolism and homeostasis in pathogenic yeasts. This requires the data mining of hundred high throughput experiments (genomics, transcriptomics and proteomics). With the help of TailorDev, we improved our methodology for monitoring our analyses and the associated results. This partnership led to the creation of the Pixel Web Application (Web App). Pixel was developed following expert development practices (unit and functional tests, integration and continuous deployment, code review, etc.). With the idea to respect FAIR principles, Pixel was designed to help data storage in such a way that all information required to reproduce any time a particular analysis, can be easily possible. Also, a hierarchical system of tags, dynamically managed via the web application, empowers the queries and the filters to find interesting results in the system. Several functionalities were also developed to combine and integrate them for a new cycle of data analysis and exploration. The Pixel project was designed as an Open Source solution. The source code is publicly available on GitHub ( https://github.com/Candihub/pixel ) and distributed as a Docker container on DockerHub.

Digital transformation and the adoption of ICT technologies in the factory of the future are growing faster and faster. In particular, data exploration methods and techniques are enabling the development of data-intensive Remote Monitoring Services for anomaly detection and predictive maintenance purposes. Remote Monitoring Services involve different actors across organizations. The Original Equipment Manufacturer explores high volume of data collected by sensors on the monitored machines to provide anomaly detection and predictive maintenance services. Insurance agencies may provide support to sustain maintenance costs. Spare parts suppliers can schedule the delivery of mechanical parts required for maintenance interventions. In this scenario, trust among participants becomes a critical issue. On the one hand, providers of anomaly detection and predictive maintenance services as well as insurance agencies must trust the way machines have been used by collecting and analysing sensors data. On the other hand, owners of monitored machines must trust the use of collected data to implement services, based on which maintenance costs are calculated. The goal of this paper is to leverage blockchain and smart contracts to ensure the required level of trust when implementing data exploration for Remote Monitoring Services. Events occurring on the monitored machines are stored as transactions in a blockchain-based system, to ensure non repudiation. Moreover, trust-demanding services are implemented as smart contracts, to guarantee the required level of trustworthiness among participants. The approach is integrated with a tool for data exploration in the digital factory, and has been validated taking into account performances and cost requirements.

Nutrition has been suggested as an important environmental factor other than viruses and chemicals in the pathogenesis of type 1 diabetes (T1D). Whereas various maternal dietary nutritional elements have been suggested and examined in T1D of both humans and experimental animals, the results largely remain controversial. In a series of studies using T1D model nonobese diabetic (NOD) mice, maternal dietary n-6/n-3 essential fatty acid ratio during pregnancy and lactation period, that is, early life stages of the offspring, has been shown to affect pathogenesis of insulitis and strongly prevent overt T1D of the offspring, which is consistent with its preventive effects on other allergic diseases.

The integration of neuroimaging and transcriptomics data has revolutionized our understanding of complex brain phenomena and holds promise for linking molecular level genetic markers to brain dynamics and function. However, the involved data differ strongly across biological scales and acquisition modalities, presenting significant preprocessing and analytical challenges. In this context, multi-modal brain data exploration software offers a low-threshold, holistic, and non-biased approach to hypothesis generation that is complementary to literature search. This review assesses current data exploration tools that combine transcriptomic and neuroimaging data, evaluating them based on species coverage, data modalities, data integration approaches, visualization capabilities, and user data integration. We highlight the potential of these tools by discussing their applicability for example research questions and identify yet unaddressed workflows and promising approaches to support imaging transcriptomics analyses. This comprehensive survey aims to inform researchers in their selection of suitable software for their specific research needs and to guide the development of more effective multi-modal brain data exploration tools.

Complex event processing (CEP) and Reactive Languages (RLs) are examples of solutions for the so-called reactive applications. Such applications are designed to detect and react to changes or event occurrences as they happen in a timely fashion. Both CEP and RLs have been developed by different communities, yet some researchers agree that they share certain aspects and could perhaps be integrated. With that in mind, we developed a JavaScript library called CEP.js that leverages the well-known Reactive Extensions for JavaScript (RxJS) to offer not only general-purpose stream operations but also CEP ones. The fact of being a JavaScript library allows CEP.js to be used in Web applications and easily embedded into mobile applications. Therefore, it opens many possibilities for CEP in mobile client applications. It also raises the concern of energy efficiency since CEP applications commonly have to deal with a significant number of events, and its continuous operations on data flows may incur significant processing. Even though CEP.js has been designed after RxJS, it was conceived in a loosely coupled way that the underlying reactive library should be easily replaced if needed. In addition to presenting the CEP.js library, in this paper, we investigate if there is any significant change in performance by running an experiment where the replacement of the reactive library used in CEP.js is the main factor analyzed. The experiment was executed in different Android devices, focusing specifically on energy consumption, an essential non-functional requirement in the smartphone realm.

JavaScript libraries, such as JQuery, are widely used in web applications. In these libraries' event delegation models, a DOM element's event handler is usually bound to its parent nodes. This makes it difficult for developers to figure out the user-defined event handlers of a specified DOM element. In this paper, we propose an approach that identifies the user-defined event handlers of DOM elements in a web page. We dynamically collect the execution trace for each triggered event in a web page, and analyze how each function is used in the execution trace to discover the event handlers for each event. We evaluate our approach on seven real-world web applications. The result shows that our approach is effective, with an overall precision of 100% and recall of 99.8%.

Robotic era is near, has never been before. In this new era, robotic education must have quality and accessibility for everyone. In this study, a disruptive technology for future of distance education based on virtual robotic laboratory (U-Plat) is presented. The created robotics education platform allows users to access a virtual robotics laboratory and training programs using internet interfaces. This environment allows them to control simulated robots, analyze and evaluate the results of experiments performed. U-Plat gives researchers, students and people working in the field of robotics the chance to learn Robot Operating System (ROS) and increase their knowledge with robotics training from beginner to advanced level. Also, U-Plat gives researchers opportunity to try their codes in online platform. Compared to traditional learning methods, U-Plat can be seen as an easier and more effective learning/teaching platform for ROS exercises, as it is an open source system. The user experience has been tried to be provided in all training tools with a very simplified and easily understandable interface. All designed training tools are provided through a web interface supported by advanced cloud systems and Docker container infrastructure. As a result, U-Plat is a novel robotic learning platform that can lead future laboratory research and distance robotic education.