Visualization analysis plays an important role in metagenomics research. Proper and clear visualization can help researchers get their first insights into data and by selecting different features, also revealing and highlighting hidden relationships and drawing conclusions. To prevent the resulting presentations from becoming chaotic, visualization techniques have to properly tackle the high dimensionality of microbiome data. Although a number of different methods based on dimensionality reduction, correlations, Venn diagrams, and network representations have already been published, there is still room for further improvement, especially in the techniques that allow visual comparison of several environments or developmental stages in one environment. In this article, we represent microbiome data by bipartite graphs, where one partition stands for taxa and the other stands for samples. We demonstrated that community detection is independent of taxonomical level. Moreover, focusing on higher taxonomical levels and the appropriate merging of samples greatly helps improving graph organization and makes our presentations clearer than other graph and network visualizations. Capturing labels in the vertices also brings the possibility of clearly comparing two or more microbial communities by showing their common and unique parts.
- Keywords
- 16S rRNA, OTU table, bipartite graph, graph modularity, metagenomics, visualization analysis,
- Publication type
- Journal Article MeSH
BACKGROUND: Visualization of large molecular datasets is a challenging yet important topic utilised in diverse fields of chemistry ranging from material engineering to drug design. Especially in drug design, modern methods of high-throughput screening generate large amounts of molecular data that call for methods enabling their analysis. One such method is classification of compounds based on their molecular scaffolds, a concept widely used by medicinal chemists to group molecules of similar properties. This classification can then be utilized for intuitive visualization of compounds. RESULTS: In this paper, we propose a scaffold hierarchy as a result of large-scale analysis of the PubChem Compound database. The analysis not only provided insights into scaffold diversity of the PubChem Compound database, but also enables scaffold-based hierarchical visualization of user compound data sets on the background of empirical chemical space, as defined by the PubChem data, or on the background of any other user-defined data set. The visualization is performed by a web based client-server application called Scaffvis. It provides an interactive zoomable tree map visualization of data sets up to hundreds of thousands molecules. Scaffvis is free to use and its source codes have been published under an open source license.Graphical abstract.
- Keywords
- Chemical space, Pubchem, Scaffold, Treemap, Visualization,
- Publication type
- Journal Article MeSH
Angiogenesis is the process of new blood vessels growing from existing vasculature. Visualizing them as a three-dimensional (3D) model is a challenging, yet relevant, task as it would be of great help to researchers, pathologists, and medical doctors. A branching analysis on the 3D model would further facilitate research and diagnostic purposes. In this paper, a pipeline of vision algorithms is elaborated to visualize and analyze blood vessels in 3D from formalin-fixed paraffin-embedded (FFPE) granulation tissue sections with two different staining methods. First, a U-net neural network is used to segment blood vessels from the tissues. Second, image registration is used to align the consecutive images. Coarse registration using an image-intensity optimization technique, followed by finetuning using a neural network based on Spatial Transformers, results in an excellent alignment of images. Lastly, the corresponding segmented masks depicting the blood vessels are aligned and interpolated using the results of the image registration, resulting in a visualized 3D model. Additionally, a skeletonization algorithm is used to analyze the branching characteristics of the 3D vascular model. In summary, computer vision and deep learning is used to reconstruct, visualize and analyze a 3D vascular model from a set of parallel tissue samples. Our technique opens innovative perspectives in the pathophysiological understanding of vascular morphogenesis under different pathophysiological conditions and its potential diagnostic role.
- Keywords
- 3D visualization, angiogenesis, artificial intelligence, biobanking, digital pathology, image registration and segmentation, neural networks,
- MeSH
- Algorithms MeSH
- Cardiovascular Physiological Phenomena MeSH
- Morphogenesis MeSH
- Neural Networks, Computer * MeSH
- Image Processing, Computer-Assisted MeSH
- Imaging, Three-Dimensional * methods MeSH
- Publication type
- Journal Article MeSH
LiteMol suite is an innovative solution that enables near-instant delivery of model and experimental biomacromolecular structural data, providing users with an interactive and responsive experience in all modern web browsers and mobile devices. LiteMol suite is a combination of data delivery services (CoordinateServer and DensityServer), compression format (BinaryCIF), and a molecular viewer (LiteMol Viewer). The LiteMol suite is integrated into Protein Data Bank in Europe (PDBe) and other life science web applications (e.g., UniProt, Ensemble, SIB, and CNRS services), it is freely available at https://litemol.org , and its source code is available via GitHub. LiteMol suite provides advanced functionality (annotations and their visualization, powerful selection features), and this chapter will describe their use for visual inspection of protein structures.
- Keywords
- Atom selection, Electron density, Ligand representation, Protein visualization, Validation report,
- MeSH
- Databases, Protein MeSH
- Internet MeSH
- Web Browser MeSH
- Protein Conformation * MeSH
- Proteins chemistry MeSH
- Software MeSH
- User-Computer Interface MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Europe MeSH
- Names of Substances
- Proteins MeSH
We provide a high-level survey of multiscale molecular visualization techniques, with a focus on application-domain questions, challenges, and tasks. We provide a general introduction to molecular visualization basics and describe a number of domain-specific tasks that drive this work. These tasks, in turn, serve as the general structure of the following survey. First, we discuss methods that support the visual analysis of molecular dynamics simulations. We discuss, in particular, visual abstraction and temporal aggregation. In the second part, we survey multiscale approaches that support the design, analysis, and manipulation of DNA nanostructures and related concepts for abstraction, scale transition, scale-dependent modeling, and navigation of the resulting abstraction spaces. In the third part of the survey, we showcase approaches that support interactive exploration within large structural biology assemblies up to the size of bacterial cells. We describe fundamental rendering techniques as well as approaches for element instantiation, visibility management, visual guidance, camera control, and support of depth perception. We close the survey with a brief listing of important tools that implement many of the discussed approaches and a conclusion that provides some research challenges in the field.
- Keywords
- DNA nanotechnology, modelitics, molecular dynamics, molecular visualization, visual abstraction,
- MeSH
- Bacteria MeSH
- DNA ultrastructure MeSH
- Humans MeSH
- Models, Molecular MeSH
- Nanostructures * MeSH
- Proteins chemistry MeSH
- Molecular Dynamics Simulation * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
- Names of Substances
- DNA MeSH
- Proteins MeSH
BACKGROUND: The knowledge of cancer burden in the population, its time trends, and the possibility of international comparison is an important starting point for cancer programs. A reliable interactive tool describing cancer epidemiology in children and adolescents has been nonexistent in the Czech Republic until recently. OBJECTIVE: The goal of this study is to develop a new web portal entitled the Czech Childhood Cancer Information System (CCCIS), which would provide information on childhood cancer epidemiology in the Czech Republic. METHODS: Data on childhood cancers have been obtained from the Czech National Cancer Registry. These data were validated using the clinical database of childhood cancer patients and subsequently combined with data from the National Register of Hospitalised Patients and with data from death certificates. These validated data were then used to determine the incidence and survival rates of childhood cancer patients aged 0 to 19 years who were diagnosed in the period 1994 to 2016 (N=9435). Data from death certificates were used to monitor long-term mortality trends. The technical solution is based on the robust PHP development Symfony framework, with the PostgreSQL system used to accommodate the data basis. RESULTS: The web portal has been available for anyone since November 2019, providing basic information for experts (ie, analyses and publications) on individual diagnostic groups of childhood cancers. It involves an interactive tool for analytical reporting, which provides information on the following basic topics in the form of graphs or tables: incidence, mortality, and overall survival. Feedback was obtained and the accuracy of outputs published on the CCCIS portal was verified using the following methods: the validation of the theoretical background and the user testing. CONCLUSIONS: We developed software capable of processing data from multiple sources, which is freely available to all users and makes it possible to carry out automated analyses even for users without mathematical background; a simple selection of a topic to be analyzed is required from the user.
- Keywords
- cancer epidemiology, children, data visualization, software development,
- MeSH
- Data Analysis * MeSH
- Child MeSH
- Incidence MeSH
- Information Systems MeSH
- Humans MeSH
- Adolescent MeSH
- Neoplasms * epidemiology MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Adolescent MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Czech Republic epidemiology MeSH
For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.
BACKGROUND: Protein function is determined by many factors, namely by its constitution, spatial arrangement, and dynamic behavior. Studying these factors helps the biochemists and biologists to better understand the protein behavior and to design proteins with modified properties. One of the most common approaches to these studies is to compare the protein structure with other molecules and to reveal similarities and differences in their polypeptide chains. RESULTS: We support the comparison process by proposing a new visualization technique that bridges the gap between traditionally used 1D and 3D representations. By introducing the information about mutual positions of protein chains into the 1D sequential representation the users are able to observe the spatial differences between the proteins without any occlusion commonly present in 3D view. Our representation is designed to serve namely for comparison of multiple proteins or a set of time steps of molecular dynamics simulation. CONCLUSIONS: The novel representation is demonstrated on two usage scenarios. The first scenario aims to compare a set of proteins from the family of cytochromes P450 where the position of the secondary structures has a significant impact on the substrate channeling. The second scenario focuses on the protein flexibility when by comparing a set of time steps our representation helps to reveal the most dynamically changing parts of the protein chain.
- Keywords
- Molecular sequence analysis, Molecular structure and function, Molecular visualization,
- MeSH
- Algorithms MeSH
- Models, Molecular MeSH
- Proteins chemistry MeSH
- Protein Structure, Secondary * MeSH
- Amino Acid Sequence MeSH
- Sequence Alignment MeSH
- Molecular Dynamics Simulation * MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Proteins MeSH
Channels, tunnels, and pores serve as pathways for the transport of molecules and ions through protein structures, thus participating to their functions. MOLEonline ( https://mole.upol.cz ) is an interactive web-based tool with enhanced capabilities for detecting and characterizing channels, tunnels, and pores within protein structures. MOLEonline has two distinct calculation modes for analysis of channel and tunnels or transmembrane pores. This application gives researchers rich analytical insights into channel detection, structural characterization, and physicochemical properties. ChannelsDB 2.0 ( https://channelsdb2.biodata.ceitec.cz/ ) is a comprehensive database that offers information on the location, geometry, and physicochemical characteristics of tunnels and pores within macromolecular structures deposited in Protein Data Bank and AlphaFill databases. These tunnels are sourced from manual deposition from literature and automatic detection using software tools MOLE and CAVER. MOLEonline and ChannelsDB visualization is powered by the LiteMol Viewer and Mol* viewer, ensuring a user-friendly workspace. This chapter provides an overview of user applications and usage.
- Keywords
- Biomacromolecule, PDB, Physicochemical properties, Pore, Protein, Residues, Tunnel, Visualization, Voronoi, mmCIF, Channel,
- MeSH
- Databases, Protein * MeSH
- Web Browser MeSH
- Ion Channels metabolism chemistry MeSH
- Protein Conformation MeSH
- Models, Molecular MeSH
- Proteins chemistry metabolism MeSH
- Software * MeSH
- User-Computer Interface MeSH
- Computational Biology methods MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Ion Channels MeSH
- Proteins MeSH
Species-specific sets of chromosomes-karyotypes-are traditionally depicted as linear ideograms with individual chromosomes represented by vertical bars. However, linear visualization has its limitations when the shared collinearity and/or chromosomal rearrangements differentiating two or more karyotypes need to be demonstrated. In these instances, circular visualization might provide easier comprehension and interpretation of inter-species chromosomal collinearity. The chromDraw graphical tool was developed as a user-friendly graphical tool for visualizing both linear and circular karyotypes based on the same input data matrix. The output graphics, saved in two different formats (EPS and SVG), can be easily imported to and modified in presentation and image-editing computer programs. The tool is freely distributed under GNU General Public License (GPL) and can be installed from Bioconductor or from the chromDraw home page.
- Keywords
- Chromosome, Karyotype, R, Visualization,
- MeSH
- Chromosome Aberrations MeSH
- Chromosomes * MeSH
- Karyotype * MeSH
- Karyotyping * MeSH
- Software * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
