PURPOSE: Multiple data formats in the MRS community currently hinder data sharing and integration. NIfTI-MRS is proposed as a standard spectroscopy data format, implemented as an extension to the Neuroimaging informatics technology initiative (NIfTI) format. This standardized format can facilitate data sharing and algorithm development as well as ease integration of MRS analysis alongside other imaging modalities. METHODS: A file format using the NIfTI header extension framework incorporates essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to convert single-voxel and spectroscopic imaging data to NIfTI-MRS. Visualization of data in NIfTI-MRS is provided by development of a dedicated plugin for FSLeyes, the FMRIB Software Library (FSL) image viewer. RESULTS: Online documentation and 10 example datasets in the proposed format are provided. Code examples of NIfTI-MRS readers are implemented in common programming languages. Conversion software, spec2nii, currently converts 14 formats where data is stored in image-space to NIfTI-MRS, including Digital Imaging and Communications in Medicine (DICOM) and vendor proprietary formats. CONCLUSION: NIfTI-MRS aims to solve issues arising from multiple data formats being used in the MRS community. Through a single conversion point, processing and analysis of MRS data are simplified, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. Greater standardization and harmonization become possible. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, for visualization.
- Keywords
- MRS, MRSI, open data format, spectroscopy, visualization,
- MeSH
- Informatics MeSH
- Magnetic Resonance Spectroscopy MeSH
- Magnetic Resonance Imaging * MeSH
- Neuroimaging * MeSH
- Software MeSH
- Technology MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
3D imaging approaches based on X-ray microcomputed tomography (microCT) have become increasingly accessible with advancements in methods, instruments and expertise. The synergy of material and life sciences has impacted biomedical research by proposing new tools for investigation. However, data sharing remains challenging as microCT files are usually in the range of gigabytes and require specific and expensive software for rendering and interpretation. Here, we provide an advanced method for visualisation and interpretation of microCT data with small file formats, readable on all operating systems, using freely available Portable Document Format (PDF) software. Our method is based on the conversion of volumetric data into interactive 3D PDF, allowing rotation, movement, magnification and setting modifications of objects, thus providing an intuitive approach to analyse structures in a 3D context. We describe the complete pipeline from data acquisition, data processing and compression, to 3D PDF formatting on an example of craniofacial anatomical morphology in the mouse embryo. Our procedure is widely applicable in biological research and can be used as a framework to analyse volumetric data from any research field relying on 3D rendering and CT-biomedical imaging.
- MeSH
- Models, Anatomic MeSH
- Electronic Data Processing MeSH
- Data Compression statistics & numerical data MeSH
- Skull anatomy & histology embryology MeSH
- Mice MeSH
- Facial Bones anatomy & histology embryology MeSH
- X-Ray Microtomography statistics & numerical data MeSH
- Radiographic Image Interpretation, Computer-Assisted MeSH
- Information Dissemination methods MeSH
- Software * MeSH
- Imaging, Three-Dimensional statistics & numerical data MeSH
- Animals MeSH
- Check Tag
- Mice MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Opportunistic sensors are increasingly used for rainfall measurement. However, their raw data are collected by a variety of systems that are often not primarily intended for rainfall monitoring, resulting in a plethora of different data formats and a lack of common standards. This hinders the sharing of opportunistic sensing (OS) data, their automated processing, and, at the end, their practical usage and integration into standard observation systems. This paper summarises the experiences of the more than 100 members of the OpenSense Cost Action involved in the OS of rainfall. We review the current practice of collecting and storing precipitation OS data and corresponding metadata, and propose new common guidelines describing the requirements on data and metadata collection, harmonising naming conventions, and defining human-readable and machine readable file formats for data and metadata storage. We focus on three sensors identified by the OpenSense community as prominent representatives of the OS of precipitation: Commercial microwave links (CML): fixed point-to-point radio links mainly used as backhauling connections in telecommunication networks Satellite microwave links (SML): radio links between geostationary Earth orbit (GEO) satellites and ground user terminals. Personal weather stations (PWS): non-professional meteorological sensors owned by citizens. The conventions presented in this paper are primarily designed for storing, handling, and sharing historical time series and do not consider specific requirements for using OS data in real time for operational purposes. The conventions are already now accepted by the ever growing OpenSense community and represent an important step towards automated processing of OS raw data and community development of joint OS software packages.
Opportunistic sensors, devices primarily intended not intended for sensing, are increasingly used for rainfall measurement. The lack of conventions defining which data should be stored and how, makes it difficult to automatically process the data and integrate these observations into standard monitoring networks. This paper reviews current practice of collecting and storing precipitation opportunistic sensing (OS) data based on the experience of more than 100 members of the OpenSense Cost Action and suggest common data format standards. We focus on three sensors identified by the OpenSense community as prominent representatives of the OS of precipitation: Commercial microwave links (CML), Satellite Microwave Links (SML), and Personal Weather Stations (PWS). The conventions are already now accepted by the ever growing OpenSense community and represent an important step towards automated processing of OS raw data and community development of joint OS software packages.
The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.
- Keywords
- conversion, data format, molecular network, network layout, systems biology,
- MeSH
- Algorithms MeSH
- Humans MeSH
- Software MeSH
- Systems Biology * MeSH
- Information Storage and Retrieval MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: Magnetic resonance spectroscopy provides metabolic information about living tissues in a non-invasive way. However, there are only few multi-centre clinical studies, mostly performed on a single scanner model or data format, as there is no flexible way of documenting and exchanging processed magnetic resonance spectroscopy data in digital format. This is because the DICOM standard for spectroscopy deals with unprocessed data. This paper proposes a plugin tool developed for jMRUI, namely jMRUI2XML, to tackle the latter limitation. jMRUI is a software tool for magnetic resonance spectroscopy data processing that is widely used in the magnetic resonance spectroscopy community and has evolved into a plugin platform allowing for implementation of novel features. RESULTS: jMRUI2XML is a Java solution that facilitates common preprocessing of magnetic resonance spectroscopy data across multiple scanners. Its main characteristics are: 1) it automates magnetic resonance spectroscopy preprocessing, and 2) it can be a platform for outputting exchangeable magnetic resonance spectroscopy data. The plugin works with any kind of data that can be opened by jMRUI and outputs in extensible markup language format. Data processing templates can be generated and saved for later use. The output format opens the way for easy data sharing- due to the documentation of the preprocessing parameters and the intrinsic anonymization--for example for performing pattern recognition analysis on multicentre/multi-manufacturer magnetic resonance spectroscopy data. CONCLUSIONS: jMRUI2XML provides a self-contained and self-descriptive format accounting for the most relevant information needed for exchanging magnetic resonance spectroscopy data in digital form, as well as for automating its processing. This allows for tracking the procedures the data has undergone, which makes the proposed tool especially useful when performing pattern recognition analysis. Moreover, this work constitutes a first proposal for a minimum amount of information that should accompany any magnetic resonance processed spectrum, towards the goal of achieving better transferability of magnetic resonance spectroscopy studies.
- MeSH
- Algorithms * MeSH
- Electronic Data Processing statistics & numerical data MeSH
- Humans MeSH
- Magnetic Resonance Spectroscopy methods MeSH
- Magnetic Resonance Imaging methods MeSH
- Image Processing, Computer-Assisted methods MeSH
- Software * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
3D macromolecular structural data is growing ever more complex and plentiful in the wake of substantive advances in experimental and computational structure determination methods including macromolecular crystallography, cryo-electron microscopy, and integrative methods. Efficient means of working with 3D macromolecular structural data for archiving, analyses, and visualization are central to facilitating interoperability and reusability in compliance with the FAIR Principles. We address two challenges posed by growth in data size and complexity. First, data size is reduced by bespoke compression techniques. Second, complexity is managed through improved software tooling and fully leveraging available data dictionary schemas. To this end, we introduce BinaryCIF, a serialization of Crystallographic Information File (CIF) format files that maintains full compatibility to related data schemas, such as PDBx/mmCIF, while reducing file sizes by more than a factor of two versus gzip compressed CIF files. Moreover, for the largest structures, BinaryCIF provides even better compression-factor ten and four versus CIF files and gzipped CIF files, respectively. Herein, we describe CIFTools, a set of libraries in Java and TypeScript for generic and typed handling of CIF and BinaryCIF files. Together, BinaryCIF and CIFTools enable lightweight, efficient, and extensible handling of 3D macromolecular structural data.
- MeSH
- Databases, Chemical MeSH
- Data Compression methods MeSH
- Crystallography methods MeSH
- Macromolecular Substances chemistry ultrastructure MeSH
- Models, Molecular * MeSH
- Software * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- Names of Substances
- Macromolecular Substances MeSH
The inherent diversity of approaches in proteomics research has led to a wide range of software solutions for data analysis. These software solutions encompass multiple tools, each employing different algorithms for various tasks such as peptide-spectrum matching, protein inference, quantification, statistical analysis, and visualization. To enable an unbiased comparison of commonly used bottom-up label-free proteomics workflows, we introduce WOMBAT-P, a versatile platform designed for automated benchmarking and comparison. WOMBAT-P simplifies the processing of public data by utilizing the sample and data relationship format for proteomics (SDRF-Proteomics) as input. This feature streamlines the analysis of annotated local or public ProteomeXchange data sets, promoting efficient comparisons among diverse outputs. Through an evaluation using experimental ground truth data and a realistic biological data set, we uncover significant disparities and a limited overlap in the quantified proteins. WOMBAT-P not only enables rapid execution and seamless comparison of workflows but also provides valuable insights into the capabilities of different software solutions. These benchmarking metrics are a valuable resource for researchers in selecting the most suitable workflow for their specific data sets. The modular architecture of WOMBAT-P promotes extensibility and customization. The software is available at https://github.com/wombat-p/WOMBAT-Pipelines.
- Keywords
- benchmarking, data analysis, label-free proteomics, quality metrics, workflow,
- MeSH
- Data Analysis MeSH
- Proteins MeSH
- Proteomics * MeSH
- Workflow MeSH
- Software MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Proteins MeSH
Ever-increasing availability of experimental volumetric data (e.g., in .ccp4, .mrc, .map, .rec, .zarr, .ome.tif formats) and advances in segmentation software (e.g., Amira, Segger, IMOD) and formats (e.g., .am, .seg, .mod, etc.) have led to a demand for efficient web-based visualization tools. Despite this, current solutions remain scarce, hindering data interpretation and dissemination. Previously, we introduced Mol* Volumes & Segmentations (Mol* VS), a web application for the visualization of volumetric, segmentation, and annotation data (e.g., semantically relevant information on biological entities corresponding to individual segmentations such as Gene Ontology terms or PDB IDs). However, this lacked important features such as the ability to edit annotations (e.g., assigning user-defined descriptions of a segment) and seamlessly share visualizations. Additionally, setting up Mol* VS required a substantial programming background. This article presents an updated version, Mol* VS 2.0, that addresses these limitations. As part of Mol* VS 2.0, we introduce the Annotation Editor, a user-friendly graphical interface for editing annotations, and the Volumes & Segmentations Toolkit (VSToolkit) for generating shareable files with visualization data. The outlined protocols illustrate the utilization of Mol* VS 2.0 for visualization of volumetric and segmentation data across various scales, showcasing the progress in the field of molecular complex visualization. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: VSToolkit-setting up and visualizing a user-constructed Mol* VS 2.0 database entry Basic Protocol 2: VSToolkit-visualizing multiple time frames and volume channels Support Protocol 1: Example: Adding database entry idr-13457537 Alternate Protocol 1: Local-server-and-viewer-visualizing multiple time frames and volume channels Support Protocol 2: Addition of database entry custom-tubhiswt Basic Protocol 3: VSToolkit-visualizing a specific channel and time frame Basic Protocol 4: VSToolkit-visualizing geometric segmentation Basic Protocol 5: VSToolkit-visualizing lattice segmentations Alternate Protocol 2: "Local-server-and-viewer"-visualizing lattice segmentations Basic Protocol 6: "Local-server-and-viewer"-visualizing multiple volume channels Support Protocol 3: Deploying a server API Support Protocol 4: Hosting Mol* viewer with VS extension 2.0 Support Protocol 5: Example: Addition of database entry empiar-11756 Support Protocol 6: Example: Addition of database entry emd-1273 Support Protocol 7: Editing annotations Support Protocol 8: Addition of database entry idr-5025553.
- Keywords
- 3D visualization tools, annotation data, large‐scale datasets, segmentation data, volumetric data,
- MeSH
- Internet MeSH
- Computer Graphics MeSH
- Software * MeSH
- User-Computer Interface MeSH
- Data Visualization MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: Structural biomolecular data are commonly stored in the PDB format. The PDB format is widely supported by software vendors because of its simplicity and readability. However, the PDB format cannot fully address many informatics challenges related to the growing amount of structural data. To overcome the limitations of the PDB format, a new textual format mmCIF was released in June 1997 in its version 1.0. mmCIF provides extra information which has the advantage of being in a computer readable form. However, this advantage becomes a disadvantage if a human must read and understand the stored data. While software tools exist to help to prepare mmCIF files, the number of available systems simplifying the comprehension and interpretation of the mmCIF files is limited. FINDINGS: In this paper we present mmView - a cross-platform web-based application that allows to explore comfortably the structural data of biomacromolecules stored in the mmCIF format. The mmCIF categories can be easily browsed in a tree-like structure, and the corresponding data are presented in a well arranged tabular form. The application also allows to display and investigate biomolecular structures via an integrated Java application Jmol. CONCLUSIONS: The mmView software system is primarily intended for educational purposes, but it can also serve as a useful research tool. The mmView application is offered in two flavors: as an open-source stand-alone application (available from http://sourceforge.net/projects/mmview) that can be installed on the user's computer, and as a publicly available web server.
- Publication type
- Journal Article MeSH
BACKGROUND: Developmental coordination disorder (DCD) is described as a motor skill disorder characterized by a marked impairment in the development of motor coordination abilities that significantly interferes with performance of daily activities and/or academic achievement. Since some electrophysiological studies suggest differences between children with/without motor development problems, we prepared an experimental protocol and performed electrophysiological experiments with the aim of making a step toward a possible diagnosis of this disorder using the event-related potentials (ERP) technique. The second aim is to properly annotate the obtained raw data with relevant metadata and promote their long-term sustainability. RESULTS: The data from 32 school children (16 with possible DCD and 16 in the control group) were collected. Each dataset contains raw electroencephalography (EEG) data in the BrainVision format and provides sufficient metadata (such as age, gender, results of the motor test, and hearing thresholds) to allow other researchers to perform analysis. For each experiment, the percentage of ERP trials damaged by blinking artifacts was estimated. Furthermore, ERP trials were averaged across different participants and conditions, and the resulting plots are included in the manuscript. This should help researchers to estimate the usability of individual datasets for analysis. CONCLUSIONS: The aim of the whole project is to find out if it is possible to make any conclusions about DCD from EEG data obtained. For the purpose of further analysis, the data were collected and annotated respecting the current outcomes of the International Neuroinformatics Coordinating Facility Program on Standards for Data Sharing, the Task Force on Electrophysiology, and the group developing the Ontology for Experimental Neurophysiology. The data with metadata are stored in the EEG/ERP Portal.
- Keywords
- developmental coordination disorder, electroencephalography, event-related potentials, reaction time, visual and audio stimulation,
- MeSH
- Acoustic Stimulation MeSH
- Data Curation MeSH
- Child MeSH
- Electroencephalography MeSH
- Evoked Potentials MeSH
- Comorbidity MeSH
- Quantitative Trait, Heritable MeSH
- Humans MeSH
- Computer Simulation MeSH
- Motor Skills Disorders diagnosis MeSH
- Reaction Time MeSH
- Reproducibility of Results MeSH
- Software MeSH
- Photic Stimulation MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
