Expanding access to magnetic resonance education through open-source web tutorials

This study presents a tool that introduces the fundamental concepts of magnetic resonance (MR) by integrating related science, technology, engineering, arts, and mathematical (STEAM) topics in the form of games to improve the access to MR education.

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning

BACKGROUND

Literature about SARS-CoV-2 widely discusses the effects of variations that have spread in the past 3 years. Such information is dispersed in the texts of several research articles, hindering the possibility of practically integrating it with related datasets (e.g., millions of SARS-CoV-2 sequences available to the community). We aim to fill this gap, by mining literature abstracts to extract-for each variant/mutation-its related effects (in epidemiological, immunological, clinical, or viral kinetics terms) with labeled higher/lower levels in relation to the nonmutated virus.

RESULTS

The proposed framework comprises (i) the provisioning of abstracts from a COVID-19-related big data corpus (CORD-19) and (ii) the identification of mutation/variant effects in abstracts using a GPT2-based prediction model. The above techniques enable the prediction of mutations/variants with their effects and levels in 2 distinct scenarios: (i) the batch annotation of the most relevant CORD-19 abstracts and (ii) the on-demand annotation of any user-selected CORD-19 abstract through the CoVEffect web application (http://gmql.eu/coveffect), which assists expert users with semiautomated data labeling. On the interface, users can inspect the predictions and correct them; user inputs can then extend the training dataset used by the prediction model. Our prototype model was trained through a carefully designed process, using a minimal and highly diversified pool of samples.

CONCLUSIONS

The CoVEffect interface serves for the assisted annotation of abstracts, allowing the download of curated datasets for further use in data integration or analysis pipelines. The overall framework can be adapted to resolve similar unstructured-to-structured text translation tasks, which are typical of biomedical domains.

WebMaBoSS: A Web Interface for Simulating Boolean Models Stochastically

WebMaBoSS is an easy-to-use web interface for conversion, storage, simulation and analysis of Boolean models that allows to get insight from these models without any specific knowledge of modeling or coding. It relies on an existing software, MaBoSS, which simulates Boolean models using a stochastic approach: it applies continuous time Markov processes over the Boolean network. It was initially built to fill the gap between Boolean and continuous formalisms, i.e., providing semi-quantitative results using a simple representation with a minimum number of parameters to fit. The goal of WebMaBoSS is to simplify the use and the analysis of Boolean models coping with two main issues: 1) the simulation of Boolean models of intracellular processes with MaBoSS, or any modeling tool, may appear as non-intuitive for non-experts; 2) the simulation of already-published models available in current model databases (e.g., Cell Collective, BioModels) may require some extra steps to ensure compatibility with modeling tools such as MaBoSS. With WebMaBoSS, new models can be created or imported directly from existing databases. They can then be simulated, modified and stored in personal folders. Model simulations are performed easily, results visualized interactively, and figures can be exported in a preferred format. Extensive model analyses such as mutant screening or parameter sensitivity can also be performed. For all these tasks, results are stored and can be subsequently filtered to look for specific outputs. This web interface can be accessed at the address: https://maboss.curie.fr/webmaboss/ and deployed locally using docker. This application is open-source under LGPL license, and available at https://github.com/sysbio-curie/WebMaBoSS.

AptaBlocks Online: A Web-Based Toolkit for the In Silico Design of Oligonucleotide Sticky Bridges

The AptaBlocks Web Interface is focused on providing graphical, intuitive, and platform-independent access to AptaBlocks, an experimentally validated algorithmic approach for the in silico design of oligonucleotide sticky bridges. The availability of AptaBlocks online to the nucleic acid research community at large makes this software a highly effective tool for accelerating the design and development of novel oligonucleotide-based drugs and other biotechnologies.

PhageWeb - Web Interface for Rapid Identification and Characterization of Prophages in Bacterial Genomes

This study developed a computational tool with a graphical interface and a web-service that allows the identification of phage regions through homology search and gene clustering. It uses G+C content variation evaluation and tRNA prediction sites as evidence to reinforce the presence of prophages in indeterminate regions. Also, it performs the functional characterization of the prophages regions through data integration of biological databases. The performance of PhageWeb was compared to other available tools (PHASTER, Prophinder, and PhiSpy) using Sensitivity (Sn) and Positive Predictive Value (PPV) tests. As a reference for the tests, more than 80 manually annotated genomes were used. In the PhageWeb analysis, the Sn index was 86.1% and the PPV was approximately 87%, while the second best tool presented Sn and PPV values of 83.3 and 86.5%, respectively. These numbers allowed us to observe a greater precision in the regions identified by PhageWeb while compared to other prediction tools submitted to the same tests. Additionally, PhageWeb was much faster than the other computational alternatives, decreasing the processing time to approximately one-ninth of the time required by the second best software. PhageWeb is freely available at http://computationalbiology.ufpa.br/phageweb.

Samasy: an automated system for sample selection and robotic transfer

Sample automation and management is increasingly important as the number and size of population-scale and high-throughput projects grow. This is particularly the case in large-scale population studies where sample size is far outpacing the commonly used 96-well plate format. To facilitate management and transfer of samples in this format, we present Samasy, a web-based application for the construction of a sample database, intuitive display of sample and batch information, and facilitation of automated sample transfer or subset. Samasy is designed with ease-of-use in mind, can be quickly set up, and runs in any web browser.

ClusterEnG: an interactive educational web resource for clustering and visualizing high-dimensional data

SUMMARY

Clustering is one of the most common techniques used in data analysis to discover hidden structures by grouping together data points that are similar in some measure into clusters. Although there are many programs available for performing clustering, a single web resource that provides both state-of-the-art clustering methods and interactive visualizations is lacking. ClusterEnG (acronym for Clustering Engine for Genomics) provides an interface for clustering big data and interactive visualizations including 3D views, cluster selection and zoom features. ClusterEnG also aims at educating the user about the similarities and differences between various clustering algorithms and provides clustering tutorials that demonstrate potential pitfalls of each algorithm. The web resource will be particularly useful to scientists who are not conversant with computing but want to understand the structure of their data in an intuitive manner.

AVAILABILITY

ClusterEnG is part of a bigger project called KnowEnG (Knowledge Engine for Genomics) and is available at http://education.knoweng.org/clustereng.

CONTACT

songi@illinois.edu.

BURRITO: An Interactive Multi-Omic Tool for Visualizing Taxa-Function Relationships in Microbiome Data

The abundance of both taxonomic groups and gene categories in microbiome samples can now be easily assayed via various sequencing technologies, and visualized using a variety of software tools. However, the assemblage of taxa in the microbiome and its gene content are clearly linked, and tools for visualizing the relationship between these two facets of microbiome composition and for facilitating exploratory analysis of their co-variation are lacking. Here we introduce BURRITO, a web tool for interactive visualization of microbiome multi-omic data with paired taxonomic and functional information. BURRITO simultaneously visualizes the taxonomic and functional compositions of multiple samples and dynamically highlights relationships between taxa and functions to capture the underlying structure of these data. Users can browse for taxa and functions of interest and interactively explore the share of each function attributed to each taxon across samples. BURRITO supports multiple input formats for taxonomic and metagenomic data, allows adjustment of data granularity, and can export generated visualizations as static publication-ready formatted figures. In this paper, we describe the functionality of BURRITO, and provide illustrative examples of its utility for visualizing various trends in the relationship between the composition of taxa and functions in complex microbiomes.

EMEN2: an object oriented database and electronic lab notebook

Transmission electron microscopy and associated methods, such as single particle analysis, two-dimensional crystallography, helical reconstruction, and tomography, are highly data-intensive experimental sciences, which also have substantial variability in experimental technique. Object-oriented databases present an attractive alternative to traditional relational databases for situations where the experiments themselves are continually evolving. We present EMEN2, an easy to use object-oriented database with a highly flexible infrastructure originally targeted for transmission electron microscopy and tomography, which has been extended to be adaptable for use in virtually any experimental science. It is a pure object-oriented database designed for easy adoption in diverse laboratory environments and does not require professional database administration. It includes a full featured, dynamic web interface in addition to APIs for programmatic access. EMEN2 installations currently support roughly 800 scientists worldwide with over 1/2 million experimental records and over 20 TB of experimental data. The software is freely available with complete source.

The fibril_one on-line database: mutations, experimental conditions, and trends associated with amyloid fibril formation

The association of amyloid fibril formation with a number of important diseases, and the extensive study of this process in vitro, has resulted in a large literature containing a vast amount of information about the fibril formation process. This includes mutations and experimental conditions that promote or protect against fibril formation. A database (fibril_one) was designed to hold information relating to the formation of fibrils. It was populated by extensive searches of the literature and other databases. A powerful World Wide Web query interface to the database was developed, enabling a simple and effective method to view amyloidogenic mutations associated with specific proteins. The Web interface was used to identify trends in the data. This revealed that mutations promoting fibril formation through altered folding tend to be associated with destabilization of the native fold. In particular, tendencies of mutations to disrupt the native secondary structure and packing in the hydrophobic core were discovered to be significant. Query access to the database is available freely on the World Wide Web at http://www.bioinformatics.leeds.ac.uk/group/online/fibril_one.