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Determining the physicochemical properties of a protein can reveal important insights in their structure, biological functions, stability, and interactions with other molecules. Although tools for computing properties of proteins already existed, we could not find a comprehensive tool that enables the calculations of multiple properties for multiple input proteins on the proteome level at once. Facing this limitation, we developed Multiple Protein Profiler (MPP) 1.0 as an integrated tool that allows the profiling of 12 individual properties of multiple proteins in a significant manner. MPP provides a tabular and graphic visualization of properties of multiple proteins. The tool is freely accessible at https://mproteinprofiler.microbiologyandimmunology.dal.ca/. [ABSTRACT FROM AUTHOR]

This research contains the design of an Industrial Network using the Industrial Ethernet-based communication protocol (Profinet) applied to the electro-pneumatic control of a distributed system of discrete processes, with the purpose of establishing a send/receive of data between an S7-1200 controller that acts as a server and two LOGO controllers that act as clients. For this network, local monitoring was established through a TP-700 screen, which is linked to the Siemens Sm@rt Client application, which allows monitoring processes from a Pc System and a smartphone mobile device, while activating the WebServer in the controller, which is a server to control and monitor processes on the web. From the study carried out, it is concluded that Profinet is an Ethernet protocol that allows the transfer of data in real time, which is suitable for applications that require a fast response. This protocol uses an industrial Ethernet network that supports high speeds, recommended for applications of high complexity. An important aspect to consider when deploying both the Sm@rt Client application and the WebServer is that they must be connected either wirelessly or by Ethernet cable to the intranet where the processes are implemented in order to ensure that the two applications work correctly. [ABSTRACT FROM AUTHOR]

LTR-retrotransposons (LTR-RTs) are a class of RNA-replicating transposon elements (TEs) that can alter genome structure and function by moving positions, repositioning genes, shifting exons, and causing chromosomal rearrangements. LTR-RTs are widespread in many plant genomes and constitute a significant portion of the genome. Their movement and activity in eukaryotic genomes can provide insight into genome evolution and gene function, especially when LTR-RTs are located near or within genes. Building the redundant and non-redundant LTR-RTs libraries and their annotations for species lacking this resource requires extensive bioinformatics pipelines and expensive computing power to analyze large amounts of genomic data. This increases the need for online services that provide computational resources with minimal overhead and maximum efficiency. Here, we present MegaLTR as a web server and standalone pipeline that detects intact LTR-RTs at the whole-genome level and integrates multiple tools for structure-based, homologybased, and de novo identification, classification, annotation, insertion time determination, and LTR-RT gene chimera analysis. MegaLTR also provides statistical analysis and visualization with multiple tools and can be used to accelerate plant species discovery and assist breeding programs in their efforts to improve genomic resources. We hope that the development of online services such as MegaLTR, which can analyze large amounts of genomic data, will become increasingly important for the automated detection and annotation of LTR-RT elements. [ABSTRACT FROM AUTHOR]

The development in the field of cloud webserver management for the execution of the workflow and meeting the quality-of-service (QoS) prerequisites in a distributed cloud environment has been a challenging task. Though, internet of things (IoT) of work presented for the scheduling of the workflow in a heterogeneous cloud environment. Moreover, the rapid development in the field of cloud computing like edge-cloud computing creates new methods to schedule the workflow in a heterogenous cloud environment to process different tasks like IoT, event-driven applications, and different network applications. The current methods used for workflow scheduling have failed to provide better trade-offs to meet reliable performance with minimal delay. In this paper, a novel web server resource management framework is presented namely the reliable and efficient webserver management (REWM) framework for the edge-cloud environment. The experiment is conducted on complex bioinformatic workflows; the result shows the significant reduction of cost and energy by the proposed REWM in comparison with standard webserver management methodology. [ABSTRACT FROM AUTHOR]

Cancer is the leading cause of death worldwide, resulting in the mortality of more than 10 million people in 2020, according to Global Cancer Statistics 2020. A potential cancer therapy involves targeting the DNA repair process by inhibiting PARP-1. In this study, classification models were constructed using a non-redundant set of 2018 PARP-1 inhibitors. Briefly, compounds were described by 12 fingerprint types and built using the random forest algorithm concomitant with various sampling approaches. Results indicated that PubChem with an oversampling approach yielded the best performance, with a Matthews correlation coefficient > 0.7 while also affording interpretable molecular features. Moreover, feature importance, as determined from the Gini index, revealed that the aromatic/cyclic/heterocyclic moiety, nitrogen-containing fingerprints, and the ether/aldehyde/alcohol moiety were important for PARP-1 inhibition. Finally, our predictive model was deployed as a web application called PARP1pred and is publicly available at https://parp1pred.streamlitapp.com, allowing users to predict the biological activity of query compounds using their SMILES notation as the input. It is anticipated that the model described herein will aid in the discovery of effective PARP-1 inhibitors. [ABSTRACT FROM AUTHOR]

Predicting the native or near-native binding pose of a small molecule within a protein binding pocket is an extremely important task in structure-based drug design, especially in the hit-to-lead and lead optimization phases. In this study, fastDRH, a free and open accessed web server, was developed to predict and analyze protein–ligand complex structures. In fastDRH server, AutoDock Vina and AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA free energy calculation procedures and multiple poses based per-residue energy decomposition analysis were well integrated into a user-friendly and multifunctional online platform. Benefit from the modular architecture, users can flexibly use one or more of three features, including molecular docking, docking pose rescoring and hotspot residue prediction, to obtain the key information clearly based on a result analysis panel supported by 3Dmol.js and Apache ECharts. In terms of protein–ligand binding mode prediction, the integrated structure-truncated MM/PB(GB)SA rescoring procedures exhibit a success rate of >80% in benchmark, which is much better than the AutoDock Vina (~70%). For hotspot residue identification, our multiple poses based per-residue energy decomposition analysis strategy is a more reliable solution than the one using only a single pose, and the performance of our solution has been experimentally validated in several drug discovery projects. To summarize, the fastDRH server is a useful tool for predicting the ligand binding mode and the hotspot residue of protein for ligand binding. The fastDRH server is accessible free of charge at http://cadd.zju.edu.cn/fastdrh/. [ABSTRACT FROM AUTHOR]

• 40 years of research resulted in the development of 100+ disorder predictors. • Disorder resources include meta webservers, databases and quality assessment tools. • Disorder predictions are used across many fields including drug design and genomics. With over 40 years of research, researchers in the intrinsic disorder prediction field developed over 100 computational predictors. This review offers a holistic perspective of this field by highlighting accurate and popular disorder predictors and introducing a wide range of practical resources that support collection, interpretation and application of disorder predictions. These resources include meta webservers that expedite collection of multiple disorder predictions, large databases of pre-computed disorder predictions that ease collection of predictions particularly for large datasets of proteins, and modern quality assessment tools. The latter methods facilitate identification of accurate predictions in a specific protein sequence, reducing uncertainty associated to the use of the putative disorder. Altogether, we review eleven predictors, four meta webservers, three databases and two quality assessment tools, all of which are conveniently available online. We also offer a perspective on future developments of the disorder prediction and the quality assessment tools. The availability of this comprehensive toolbox of useful resources should stimulate further growth in the application of the disorder predictions across many areas including rational drug design, systems medicine, structural bioinformatics and structural genomics. [ABSTRACT FROM AUTHOR]

Rapid progresses in RNA-Seq and computational methods have assisted in quantifying A-to-I RNA editing and altered RNA editing sites have been widely observed in various diseases. Nevertheless, functional characterization of the altered RNA editing sites still remains a challenge. Here, we developed perturbations of RNA editing sites (PRES; http://bio-bigdata.hrbmu.edu.cn/PRES/) as the webserver for decoding functional perturbations of RNA editing sites based on editome profiling. After uploading an editome profile among samples of different groups, PRES will first annotate the editing sites to various genomic elements and detect differential editing sites under the user-selected method and thresholds. Next, the downstream functional perturbations of differential editing sites will be characterized from gain or loss miRNA/RNA binding protein regulation, RNA and protein structure changes, and the perturbed biological pathways. A prioritization module was developed to rank genes based on their functional consequences of RNA editing events. PRES provides user-friendly functionalities, ultra-efficient calculation, intuitive table and figure visualization interface to display the annotated RNA editing events, filtering options and elaborate application notebooks. We anticipate PRES will provide an opportunity for better understanding the regulatory mechanisms of RNA editing in human complex diseases. [ABSTRACT FROM AUTHOR]

Proper monitoring of environmental air parameters is necessary to create awareness of how some of our activities affect the quality of air around us, in addition to alerting us to take necessary precautions that will preserve our health and wellness and sustainlife. Hence in this paper, a realtimeair quality monitoring system for air pollutant detection was designed and developed. The system uses the DHT11 temperature and humidity sensor and the MQ series sensors to measure environmental air parameters like temperature and humidity, the amount of smoke present in the environment, and the concentrations of gases like CO, H2S, and NH3gases detected in Ubeji area of Delta State in Nigeria. The real-time sensed data is processed by the ATmega328P microcontroller,displayed on anLCD andsent via the ESP32 Wi-Fi module unit to a webserver where the data is stored. This makes it possible to have a picture of the acquired data in real time to ensure adequate monitoring of the air quality and it serves as a database for future reference. [ABSTRACT FROM AUTHOR]

Background. Next Generation Sequencing (NGS) techniques dominate today's landscape of genetics and genomics research. Though Illumina still dominates worldwide sequencing, Oxford Nanopore is one of the leading technologies currently being used by biologists, medics and geneticists across various applications. Oxford Nanopore is automated and relatively simple for conducting experiments, but generates gigabytes of raw data, to be processed by often ambiguous set of alternative bioinformatics commandline tools, and genomics frameworks which require a knowledge of bioinformatics to run. Results. We established an inter-collegiate collaboration across experimentalists and bioinformaticians in order to provide a novel bioinformatics tool, free for academics. This tool allows people without extensive bioinformatics knowledge to simply process their raw genome sequencing data. Currently, due to ICT resources' maintenance reasons, our server is only capable of handling small genomes (up to 15 Mb). In this paper, we introduce our tool, NanoForms: an intuitive and integrated web server for the processing and analysis of raw prokaryotic genome data, coming from Oxford Nanopore. NanoForms is freely available for academics at the following locations: http://nanoforms.tech (webserver) and https://github.com/czmilanna/nanoforms (GitHub source repository). [ABSTRACT FROM AUTHOR]

Reversible post-translational modification (PTM) orchestrates various biological processes by changing the properties of proteins. Since many proteins are multiply modified by PTMs, identification of PTM crosstalk site has emerged to be an intriguing topic and attracted much attention. In this study, we systematically deciphered the in situ crosstalk of ubiquitylation and SUMOylation that co-occurs on the same lysine residue. We first collected 3363 ub iquitylation- S UMOylation (UBS) crosstalk site on 1302 proteins and then investigated the prime sequence motifs, the local evolutionary degree and the distribution of structural annotations at the residue and sequence levels between the UBS crosstalk and the single modification sites. Given the properties of UBS crosstalk sites, we thus developed the mUSP classifier to predict UBS crosstalk site by integrating different types of features with two-step feature optimization by recursive feature elimination approach. By using various cross-validations, the mUSP model achieved an average area under the curve (AUC) value of 0.8416, indicating its promising accuracy and robustness. By comparison, the mUSP has significantly better performance with the improvement of 38.41 and 51.48% AUC values compared to the cross-results by the previous single predictor. The mUSP was implemented as a web server available at http://bioinfo.ncu.edu.cn/mUSP/index.html to facilitate the query of our high-accuracy UBS crosstalk results for experimental design and validation. [ABSTRACT FROM AUTHOR]

The locations of the initiation of genomic DNA replication are defined as origins of replication sites (ORIs), which regulate the onset of DNA replication and play significant roles in the DNA replication process. The study of ORIs is essential for understanding the cell-division cycle and gene expression regulation. Accurate identification of ORIs will provide important clues for DNA replication research and drug development by developing computational methods. In this paper, the first integrated predictor named iORI-Euk was built to identify ORIs in multiple eukaryotes and multiple cell types. In the predictor, seven eukaryotic (Homo sapiens, Mus musculus , Drosophila melanogaster , Arabidopsis thaliana , Pichia pastoris , Schizosaccharomyces pombe and Kluyveromyces lactis) ORI data was collected from public database to construct benchmark datasets. Subsequently, three feature extraction strategies which are k -mer, binary encoding and combination of k -mer and binary were used to formulate DNA sequence samples. We also compared the different classification algorithms' performance. As a result, the best results were obtained by using support vector machine in 5-fold cross-validation test and independent dataset test. Based on the optimal model, an online web server called iORI-Euk (http://lin-group.cn/server/iORI-Euk/) was established for the novel ORI identification. [ABSTRACT FROM AUTHOR]

Background: Epigenetic regulation is essential in regulating gene expression across a variety of biological processes. Many high-throughput sequencing technologies have been widely used to generate epigenetic data, such as histone modification, transcription factor binding sites, DNA modifications, chromatin accessibility, and etc. A large scale of epigenetic data is stored in NCBI Gene Expression Omnibus (GEO). However, it is a great challenge to reanalyze these large scale and complex data, especially for researchers who do not specialize in bioinformatics skills or do not have access to expensive computational infrastructure. Results: GsmPlot can simply accept GSM IDs to automatically download NCBI data or can accept user's private bigwig files as input to plot the concerned data on promoters, exons or any other user-defined genome locations and generate UCSC visualization tracks. By linking public data repository and private data, GsmPlot can spark data-driven ideas and hence promote the epigenetic research. Conclusions: GsmPlot web server allows convenient visualization and efficient exploration of any NCBI epigenetic data in any genomic region without need of any bioinformatics skills or special computing resources. GsmPlot is freely available at https://gsmplot.deqiangsun.org/. [ABSTRACT FROM AUTHOR]

Automation of industrial installations is an assembly of mechanical and electrical equipment that can generate logical commands, through a software program, in order to replace the manual orders made by human operators. At present, there are automation systems such as PLC, DCS (Distributed Control System), HMI (Operator Interface), SCADA (Data Control and Acquisition System), ANN (Artificial Neural Networks) and more. Siemens has integrated into the standard PLC with Ethernet communication interface, a web server able to reading the tags from it and displaying them on a customizable HTML page. This web page can be accessed from within the network where it is located and from the outside of the network, a VPN connection, from a web-browsing device, accessing via the IP address of the PLC. [ABSTRACT FROM AUTHOR]

The identification of bacteriophage proteins in the host subcellular localization could provide important clues for understanding the interaction between phage and host bacteria as well as antibacterial drug design. To date, computational methods have been reported to identify bacteriophage proteins located in the host cell. However, there is still space for improving the prediction accuracy. The existing methods considering the sequence order correlation and the physicochemical property of protein provide us insights to construct an integrated descriptor based on sequence for phage proteins. Meanwhile, we proposed a feature selection technique to obtain the optimal features. In the jackknife test, the prediction accuracies are 86.7% and 97.9%, respectively for discrimination between PH proteins and non-PH proteins as well as PHM proteins and PHC proteins. Based on our model, we updated the web server PHPred to version 2.0 which can be freely accessed from http://lin-group.cn/server/PHPred2.0 . [ABSTRACT FROM AUTHOR]

Discovering new anticancer drugs has been widely concerned and remains an open challenge. Target- and phenotypic-based experimental screening represent two mainstream anticancer drug discovery methods, which suffer from time-consuming, labor-intensive, and high experimental costs. In this study, we collected 485,900 compounds involving in 3,919,974 bioactivity records against 426 anticancer targets and 346 cancer cell lines from academic literature, as well as 60 tumor cell lines from NCI-60 panel. A total of 832 classification models (426 target- and 406 cell-based predictive models) were then constructed to predict the inhibitory activity of compounds against targets and tumor cell lines using FP-GNN deep learning method. Compared to the classical machine learning and deep learning methods, the FP-GNN models achieve considerable overall predictive performance, with the highest AUC values of 0.91, 0.88, 0.91 for the test sets of targets, academia-sourced and NCI-60 cancer cell lines, respectively. A user-friendly webserver called DeepCancerMap and its local version were developed based on these high-quality models, enabling users to perform anticancer drug discovery-related tasks including large-scale virtual screening, profiling prediction of anticancer agents, target fishing, and drug repositioning. We anticipate this platform to accelerate the discovery of anticancer drugs in the field. DeepCancerMap is freely available at https://deepcancermap.idruglab.cn. A precise and user-friendly deep learning-based web server called DeepCancer was built for the discovery of anticancer drug. [Display omitted] • A comprehensive anticancer dataset was constructed including 25,631,674 records. • Advanced DL algorithm FP-GNN was employed and outperformed classical methods. • Time-split external test set has proved the satisfactory reliability and precision. • A platform with functions of Selectivity Predict, VS and Similarity Search was built. [ABSTRACT FROM AUTHOR]

This paper details how to build a simple energy monitor that can be used to measure how much electrical energy you use in home place. It measures current, but uses an assumed fixed value for voltage and calculates apparent power and show the dates in one web page. Although not as accurate as a monitor that measures voltage as well as current, it is a method commonly used in commercially available whole house energy monitors for reasons of simplicity and cost. This paper then highlights selected approaches to monitoring and evaluation and the conditions under which each might be useful, and how and by whom lessons are to be learned. Attention is paid to key elements of monitoring and evaluation such as the development of indicators and the measurement of impacts. In the light of the many failed energy projects, this paper closes with some suggestions of how monitoring and evaluation processes and capacity may be improved. [ABSTRACT FROM AUTHOR]

This column discusses the author's attempts to find Apache's value by determining how many webpages it serves in the United States. [ABSTRACT FROM PUBLISHER]