Updated Web Research Articles

FluxCT V2.0: Updates to a Web Tool Identifying Contaminating Flux in Space Telescope Data

We present FluxCT V2.0, an updated web tool for identifying contaminating flux in Kepler and TESS target pixel files. FluxCT V2.0 focuses on enhancing functionality, user experience, and data processing capabilities. We resolved existing issues to allow for an extended user base, removed known bugs, and extended the tool to any TESS pixel file, allowing the user to search any TESS point object. A batch code for TESS is now available on the companion GitHub. Additional output parameters, such as amplitude dilution and a magnitude cut, have been added to the tool, allowing users more freedom to analyze the possible effects of target sources.

CSSP-2.0: A refined consensus method for accurate protein secondary structure prediction

Studying the relationship between sequences and their corresponding three-dimensional structure assists structural biologists in solving the protein-folding problem. Despite several experimental and in-silico approaches, still understanding or decoding the three-dimensional structures from the sequence remains a mystery. In such cases, the accuracy of the structure prediction plays an indispensable role. To address this issue, an updated web server (CSSP-2.0) has been created to improve the accuracy of our previous version of CSSP by deploying the existing algorithms. It uses input as probabilities and predicts the consensus for the secondary structure as a highly accurate three-state Q3 (helix, strand, and coil). This prediction is achieved using six recent top-performing methods: MUFOLD-SS, RaptorX, PSSpred v4, PSIPRED, JPred v4, and Porter 5.0. CSSP-2.0 validation includes datasets involving various protein classes from the PDB, CullPDB, and AlphaFold databases. Our results indicate a significant improvement in the accuracy of the consensus Q3 prediction. Using CSSP-2.0, crystallographers can sort out the stable regular secondary structures from the entire complex structure, which would aid in inferring the functional annotation of hypothetical proteins. The web server is freely available at https://bioserver3.physics.iisc.ac.in/cgi-bin/cssp-2/

The HADDOCK2.4 web server for integrative modeling of biomolecular complexes.

Interactions between macromolecules, such as proteins and nucleic acids, are essential for cellular functions. Experimental methods can fail to provide all the information required to fully model biomolecular complexes at atomic resolution, particularly for large and heterogeneous assemblies. Integrative computational approaches have, therefore, gained popularity, complementing traditional experimental methods in structural biology. Here, we introduce HADDOCK2.4, an integrative modeling platform, and its updated web interface ( https://wenmr.science.uu.nl/haddock2.4 ). The platform seamlessly integrates diverse experimental and theoretical data to generate high-quality models of macromolecular complexes. The user-friendly web server offers automated parameter settings, access to distributed computing resources, and pre- and post-processing steps that enhance the user experience. To present the web server's various interfaces and features, we demonstrate two different applications: (i) we predict the structure of an antibody-antigen complex by using NMR data for the antigen and knowledge of the hypervariable loops for the antibody, and (ii) we perform coarse-grained modeling of PRC1 with a nucleosome particle guided by mutagenesis and functional data. The described protocols require some basic familiarity with molecular modeling and the Linux command shell. This new version of our widely used HADDOCK web server allows structural biologists and non-experts to explore intricate macromolecular assemblies encompassing various molecule types.

A computational model of circRNA-associated diseases based on a graph neural network: prediction and case studies for follow-up experimental validation

BackgroundCircular RNAs (circRNAs) have been confirmed to play a vital role in the occurrence and development of diseases. Exploring the relationship between circRNAs and diseases is of far-reaching significance for studying etiopathogenesis and treating diseases. To this end, based on the graph Markov neural network algorithm (GMNN) constructed in our previous work GMNN2CD, we further considered the multisource biological data that affects the association between circRNA and disease and developed an updated web server CircDA and based on the human hepatocellular carcinoma (HCC) tissue data to verify the prediction results of CircDA.ResultsCircDA is built on a Tumarkov-based deep learning framework. The algorithm regards biomolecules as nodes and the interactions between molecules as edges, reasonably abstracts multiomics data, and models them as a heterogeneous biomolecular association network, which can reflect the complex relationship between different biomolecules. Case studies using literature data from HCC, cervical, and gastric cancers demonstrate that the CircDA predictor can identify missing associations between known circRNAs and diseases, and using the quantitative real-time PCR (RT-qPCR) experiment of HCC in human tissue samples, it was found that five circRNAs were significantly differentially expressed, which proved that CircDA can predict diseases related to new circRNAs.ConclusionsThis efficient computational prediction and case analysis with sufficient feedback allows us to identify circRNA-associated diseases and disease-associated circRNAs. Our work provides a method to predict circRNA-associated diseases and can provide guidance for the association of diseases with certain circRNAs. For ease of use, an online prediction server (http://server.malab.cn/CircDA) is provided, and the code is open-sourced (https://github.com/nmt315320/CircDA.git) for the convenience of algorithm improvement.

Experimental investigation on cold-formed Z-sections under two-flange loadings

This article presents the updated web crippling coefficients of cold-formed Z-sections under two-flange loading conditions. AISI Specification defines end-two-flange (ETF) and interior-two-flange (ITF) load cases under two-flange loading conditions. The web crippling capacity can be calculated by the empirical equation provided by AISI, Eurocode, and IS Specifications. This empirical equation is associated with web crippling coefficients. This coefficient is not updated for the Z-section under two-flange loadings after the development of the AISI test standard for web crippling investigations. Hence, the authors conducted an experimental investigation of cold-formed Z-sections using 28 tests under ETF and ITF load cases. The experimental investigation is carried out according to AISI guidelines. The result of the experimental work is validated with finite element analysis (FEA) results. The web crippling capacity obtained from experimentation and FEA are compared with AISI, Eurocode, and IS Specifications. It is observed that web crippling strength prediction from cold-formed specifications is over-conservative under both ETF and ITF load cases. This research also highlighted the effect of higher web height to thickness and inside bend radius to thickness ratio. Hence, the authors suggested new web crippling coefficients that can better predict the web crippling capacity of Z-sections according to the AISI Specification.

PICKLES v3: the updated database of pooled in vitro CRISPR knockout library essentiality screens.

PICKLES (https://pickles.hart-lab.org) is an updated web interface to a freely available database of genome-scale CRISPR knockout fitness screens in human cell lines. Using a completely rewritten interface, researchers can explore gene knockout fitness phenotypes across cell lines and tissue types and compare fitness profiles with fitness, expression, or mutation profiles of other genes. The database has been updated to include data from three CRISPR libraries (Avana, Score, and TKOv3), and includes information from 1162 whole-genome screens probing the knockout fitness phenotype of 18 959 genes. Source code for the interface and the integrated database are available for download.

GALAXY ver3: updated web application for glycosylation profiling based on 3D HPLC map.

High-performance liquid chromatography (HPLC) elution data provide a useful tool for quantitative glycosylation profiling, discriminating isomeric oligosaccharides. The web application Glycoanalysis by the Three Axes of MS and Chromatography (GALAXY), which is based on the three-dimensional HPLC map of N-linked oligosaccharides with pyridyl-2-amination developed by Dr. Noriko Takahashi, has been extensively used for N-glycosylation profiling at molecular, cellular, and tissue levels. Herein, we describe the updated GALAXY as version 3, which includes new HPLC data including those of glucuronylated and sulfated glycans, an improved graphical user interface using modern technologies, and linked to glycan information in GlyTouCan and the GlyCosmos Portal. This liaison will facilitate glycomic analyses of human and other organisms in conjunction with multiomics data.

CircR2Disease v2.0: An Updated Web Server for Experimentally Validated circRNA–disease Associations and Its Application

With accumulating dysregulated circular RNAs (circRNAs) in pathological processes, the regulatory functions of circRNAs, especially circRNAs as microRNA (miRNA) sponges and their interactions with RNA-binding proteins (RBPs), have been widely validated. However, the collected information on experimentally validated circRNA–disease associations is only preliminary. Therefore, an updated CircR2Disease database providing a comprehensive resource and web tool to clarify the relationships between circRNAs and diseases in diverse species is necessary. Here, we present an updated CircR2Disease v2.0 with the increased number of circRNA–disease associations and novel characteristics. CircR2Disease v2.0 provides more than 5-fold experimentally validated circRNA–disease associations compared to its previous version. This version includes 4201 entries between 3077 circRNAs and 312 disease subtypes. Secondly, the information of circRNA–miRNA, circRNA–miRNA–target, and circRNA–RBP interactions has been manually collected for various diseases. Thirdly, the gene symbols of circRNAs and disease name IDs can be linked with various nomenclature databases. Detailed descriptions such as samples and journals have also been integrated into the updated version. Thus, CircR2Disease v2.0 can serve as a platform for users to systematically investigate the roles of dysregulated circRNAs in various diseases and further explore the posttranscriptional regulatory function in diseases. Finally, we propose a computational method named circDis based on the graph convolutional network (GCN) and gradient boosting decision tree (GBDT) to illustrate the applications of the CircR2Disease v2.0 database. CircR2Disease v2.0 is available at http://bioinfo.snnu.edu.cn/CircR2Disease_v2.0 and https://github.com/bioinforlab/CircR2Disease-v2.0.

BAGET 2.0: an updated web tool for the effortless retrieval of prokaryotic gene context and sequence.

MotivationThe retrieval of a single gene sequence and context from completely sequenced bacterial and archaeal genomes constitutes an intimidating task for the wet bench biologist. Existing web-based genome browsers are either too complex for routine use or only provide a subset of the available prokaryotic genomes.ResultsWe have developed BAGET 2.0 (Bacterial and Archaeal Gene Exploration Tool), an updated web service granting access in just three mouse clicks to the sequence and synteny of any gene from completely sequenced bacteria and archaea. User-provided annotated genomes can be processed as well. BAGET 2.0 relies on a local database updated on a daily basis.Availability and implementationBAGET 2.0 befits all current browsers such as Chrome, Firefox, Edge, Opera and Safari. Internet Explorer 11 is supported. BAGET 2.0 is freely accessible at https://archaea.i2bc.paris-saclay.fr/baget/

An explainable data-driven approach to web directory taxonomy mapping

Abstract The spread of e-commerce and web applications has fostered the integration of cross-domain business activities. To efficiently retrieve products and services, web directories allow customers to browse multiple-level taxonomies to find specific products or services according to a predefined categorization. Providers need to periodically update web directory lists by aligning in-house taxonomies to domain-specific hierarchies coming from external sources. However, such taxonomy mapping procedures are often semi-automatic and rely on traditional word disambiguation techniques to capture the semantics behind categories and products descriptions. Hence, the flexibility and explainability of the underlying models are quite limited. This paper proposes an automated, explainable approach to web directory taxonomy mapping based on text categorization. It exploits two complementary word-based text representations: a frequency-based representation, which captures syntactic text similarities, and an embedding one, which highlights the underlying semantic relationships among words. Since the proposed solution is purely data-driven, it can be successfully applied to business domains where there is a lack of semantic models. The frequency-based text representation has shown to be particularly suitable for driving the automated taxonomy mapping procedure, whereas the embedding space has been profitably used to provide local explanations of the category assignments.

GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis.

Introduced in 2017, the GEPIA (Gene Expression Profiling Interactive Analysis) web server has been a valuable and highly cited resource for gene expression analysis based on tumor and normal samples from the TCGA and the GTEx databases. Here, we present GEPIA2, an updated and enhanced version to provide insights with higher resolution and more functionalities. Featuring 198 619 isoforms and 84 cancer subtypes, GEPIA2 has extended gene expression quantification from the gene level to the transcript level, and supports analysis of a specific cancer subtype, and comparison between subtypes. In addition, GEPIA2 has adopted new analysis techniques of gene signature quantification inspired by single-cell sequencing studies, and provides customized analysis where users can upload their own RNA-seq data and compare them with TCGA and GTEx samples. We also offer an API for batch process and easy retrieval of the analysis results. The updated web server is publicly accessible at http://gepia2.cancer-pku.cn/.

MISIM v2.0: a web server for inferring microRNA functional similarity based on microRNA-disease associations.

MicroRNAs (miRNAs) are one class of important small non-coding RNA molecules and play critical roles in health and disease. Therefore, it is important and necessary to evaluate the functional relationship of miRNAs and then predict novel miRNA-disease associations. For this purpose, here we developed the updated web server MISIM (miRNA similarity) v2.0. Besides a 3-fold increase in data content compared with MISIM v1.0, MISIM v2.0 improved the original MISIM algorithm by implementing both positive and negative miRNA-disease associations. That is, the MISIM v2.0 scores could be positive or negative, whereas MISIM v1.0 only produced positive scores. Moreover, MISIM v2.0 achieved an algorithm for novel miRNA-disease prediction based on MISIM v2.0 scores. Finally, MISIM v2.0 provided network visualization and functional enrichment analysis for functionally paired miRNAs. The MISIM v2.0 web server is freely accessible at http://www.lirmed.com/misim/.

The Cornwall a-book: An Augmented Travel Guide Using Next Generation Paper

Electronic publishing usually presents readers with book or e-book options for reading on paper or screen. In this paper, we introduce a third method of reading on paper-and-screen through the use of an augmented book (‘a-book’) with printed hotlinks than can be viewed on a nearby smartphone or other device. Two experimental versions of an augmented guide to Cornwall are shown using either optically recognised pages or embedded electronics making the book sensitive to light and touch. We refer to these as second generation (2G) and third generation (3G) paper respectively. A common architectural framework, authoring workflow and interaction model is used for both technologies, enabling the creation of two future generations of augmented books with interactive features and content. In the travel domain we use these features creatively to illustrate the printed book with local multimedia and updatable web media, to point to the printed pages from the digital content, and to record personal and web media into the book.

Exploring Data with CODAP

Concord Consortium's Common Online Data Analysis Platform (CODAP), a free Web-based data tool designed for students in grades 6-12 and higher, is continuously being updated and developed for diverse projects in data science, science education, and mathematics/statistics education (https://codap.concord.org/). Teachers and students can access CODAP without downloading software or registering for accounts. Although some Web-based technology tools provide certain features for free and require users to pay a fee to use additional features, CODAP has no hidden costs. Devices need only be connected to the Internet using an updated Web browser (Chrome is preferred). CODAP is not optimized (yet) for use on such touchscreen devices as tablets or iPads®.

Drug‐induced thrombocytopenia: 2019 Update of clinical and laboratory data

Drug‐induced thrombocytopenia: 2019 Update of clinical and laboratory data

A virtual thematic research environment for analysis of climate change and its consequences for Northern Eurasia: the current state of the art and perspectives

A virtual research environment aimed at analysis of climate change and its impact on Northern Eurasia based on climatic data archives and dedicated analytics embedded into a web-GIS called “Climate” is presented. An extended set of analytical procedures related to the analysis of climatic and meteorological extremes is described. An updated web portal structure is described to facilitate the system use by the general public, regional stakeholders, and decision makers and get the required information without using a tedious registration procedure.

IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding.

The structural states of proteins include ordered globular domains as well as intrinsically disordered protein regions that exist as highly flexible conformational ensembles in isolation. Various computational tools have been developed to discriminate ordered and disordered segments based on the amino acid sequence. However, properties of IDRs can also depend on various conditions, including binding to globular protein partners or environmental factors, such as redox potential. These cases provide further challenges for the computational characterization of disordered segments. In this work we present IUPred2A, a combined web interface that allows to generate energy estimation based predictions for ordered and disordered residues by IUPred2 and for disordered binding regions by ANCHOR2. The updated web server retains the robustness of the original programs but offers several new features. While only minor bug fixes are implemented for IUPred, the next version of ANCHOR is significantly improved through a new architecture and parameters optimized on novel datasets. In addition, redox-sensitive regions can also be highlighted through a novel experimental feature. The web server offers graphical and text outputs, a RESTful interface, access to software download and extensive help, and can be accessed at a new location: http://iupred2a.elte.hu.

GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits.

Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet for most of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of non-coding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d or http://mulinlab.org/gwas4d), that systematically evaluates GWAS signals and identifies context-specific regulatory variants. The updated web server includes six major features: (i) updates the regulatory variant prioritization method with our new algorithm; (ii) incorporates 127 tissue/cell type-specific epigenomes data; (iii) integrates motifs of 1480 transcriptional regulators from 13 public resources; (iv) uniformly processes Hi-C data and generates significant interactions at 5 kb resolution across 60 tissues/cell types; (v) adds comprehensive non-coding variant functional annotations; (vi) equips a highly interactive visualization function for SNP-target interaction. Using a GWAS fine-mapped set for 161 coronary artery disease risk loci, we demonstrate that GWAS4D is able to efficiently prioritize disease-causal regulatory variants.

Maintaining accurate web usage models using updates from activity diagrams

ContextMarkov operational profile (Markov OP) is a type of usage models for large applications involving state transitions. Such usage models not only help us ensure and maximize product reliability, but can also be used to understand user behavior, and fine-tune system performance and usability. Web usage models can be constructed based on actual usage of the application by target users recorded in existing web logs. Such models constructed before maintenance and evolution may not reflect actual usage of the updated application accurately. At this point, the updated web application has not been deployed yet, so that its actual usage data could not be collected to construct a new Markov OP needed to test the newly updated web application. ObjectiveThis paper aims at maintaining accurate Markov OP using updates derived from activity diagrams used in web application maintenance and evolution. MethodMarkov OP shares some common characteristics with activity diagrams which describe the application in terms of user activities. We develop a method to update the initial Markov OP by analyzing its differences with the activity diagrams. ResultsWe have applied our method in a web application to provide an initial validation of its applicability and effectiveness. After the deployment of the updated web application and new usage data became available, a new Markov OP was constructed. We quantified inaccuracies of the initial Markov OP and the updated Markov OP using the new Markov OP as the reference standard, and quantitatively demonstrated that our method improves the accuracy of the initial Markov OP for the updated web application. ConclusionOur new method provides an effective and practical way to maintain accurate Markov OP over web application maintenance and evolution using existing activity diagrams.

MoonProt 2.0: an expansion and update of the moonlighting proteins database.

MoonProt 2.0 (http://moonlightingproteins.org) is an updated, comprehensive and open-access database storing expert-curated annotations for moonlighting proteins. Moonlighting proteins contain two or more physiologically relevant distinct functions performed by a single polypeptide chain. Here, we describe developments in the MoonProt website and database since our previous report in the Database Issue of Nucleic Acids Research. For this V 2.0 release, we expanded the number of proteins annotated to 370 and modified several dozen protein annotations with additional or updated information, including more links to protein structures in the Protein Data Bank, compared with the previous release. The new entries include more examples from humans and several model organisms, more proteins involved in disease, and proteins with different combinations of functions. The updated web interface includes a search function using BLAST to enable users to search the database for proteins that share amino acid sequence similarity with a protein of interest. The updated website also includes additional background information about moonlighting proteins and an expanded list of links to published articles about moonlighting proteins.