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BACKGROUND: Chemical space is virtual space occupied by all chemically meaningful organic compounds. It is an important concept in contemporary chemoinformatics research, and its systematic exploration is vital to the discovery of either novel drugs or new tools for chemical biology. RESULTS: In this paper, we describe Molpher, an open-source framework for the systematic exploration of chemical space. Through a process we term 'molecular morphing', Molpher produces a path of structurally-related compounds. This path is generated by the iterative application of so-called 'morphing operators' that represent simple structural changes, such as the addition or removal of an atom or a bond. Molpher incorporates an optimized parallel exploration algorithm, compound logging and a two-dimensional visualization of the exploration process. Its feature set can be easily extended by implementing additional morphing operators, chemical fingerprints, similarity measures and visualization methods. Molpher not only offers an intuitive graphical user interface, but also can be run in batch mode. This enables users to easily incorporate molecular morphing into their existing drug discovery pipelines. CONCLUSIONS: Molpher is an open-source software framework for the design of virtual chemical libraries focused on a particular mechanistic class of compounds. These libraries, represented by a morphing path and its surroundings, provide valuable starting data for future in silico and in vitro experiments. Molpher is highly extensible and can be easily incorporated into any existing computational drug design pipeline.
- Publikační typ
- časopisecké články MeSH
Cuby is a computational chemistry framework written in the Ruby programming language. It provides unified access to a wide range of computational methods by interfacing external software and it implements various protocols that operate on their results. Using structured input files, elementary calculations can be combined into complex workflows. For users, Cuby provides a unified and userfriendly way to automate their work, seamlessly integrating calculations carried out in different computational chemistry programs. For example, the QM/MM module allows combining methods across the interfaced programs and the builtin molecular dynamics engine makes it possible to run a simulation on the resulting potential. For programmers, it provides high-level, object-oriented environment that allows rapid development and testing of new methods and computational protocols. The Cuby framework is available for download at http://cuby4.molecular.cz. © 2016 Wiley Periodicals, Inc.
- Klíčová slova
- QM/MM, Ruby, datasets, software framework, workflow automation,
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.
- Klíčová slova
- cryo-EM, extensible, integration, multidomain, software-framework, workflows,
- Publikační typ
- časopisecké články MeSH
The authors give an account of different types of commercially supplied programmes which can be used also in the health services. They discuss the properties and types of different software - data base programmes, text processors, graphic and statistical programmes and finally so-called integrated software along with data on possible mutual combinations. At the same time also general conditions for the application of these programmes within the framework of clinical informations systems are discussed incl. their advantages and short-comings.
- MeSH
- lékařská informatika * MeSH
- software * MeSH
- Publikační typ
- anglický abstrakt MeSH
- časopisecké články MeSH
This article focuses on the area of software development for microcontrollers and details the implementation of modern programming practices and principles in embedded systems and IoT applications. This article explains how we implemented previously unimplemented principles and applied design patterns for quality software design on microcontrollers, which are currently only used for developing applications on the higher layers of the IoT reference model. A custom modular framework for microcontrollers is presented, based on applying SOLID principles and adapting design patterns specific to the microcontrollers' application development needs. The implemented framework enables independent communication between modules and flexible integration of hardware components. It is designed with platform independence in mind, contributing to its wide adaptability and ease of use in diverse development environments. By applying these technological approaches, we can create applications that are not only testable and extensible in terms of application logic but also allow for easy adaptation to changes in these hardware resources. Utilizing these capabilities represents an innovative approach to development for microcontrollers that fundamentally improves the long-term sustainability and scalability of applications.
- Klíčová slova
- IoT, SOLID, design pattern, framework, microcontroller, programming,
- Publikační typ
- časopisecké články MeSH
As part of our research for microcontroller software support, we have developed a modular framework that utilizes previously unimplemented architectural principles for developing applications on microcontrollers. These principles are still a privilege of enterprise and server applications. The paper describes the benefits of a new architectural approach to developing applications on microcontrollers and describes the most common application scenarios along with examples of IoT application development using a framework with design pattern architecture and SOLID principles. As a result, our framework supports developers in creating robust, adaptive, and scalable applications. It emphasizes a modular and clean design that increases development efficiency and enables easy deployment of new features or integration of new technologies, such as new types of sensors, upgraded development boards, or improved development tools and frameworks. The architectural concepts offered useful guidance for creating applications ready for future challenges and changing technology environments, especially in the IoT area.
- Klíčová slova
- ESP32, IoT, SOLID, design pattern, framework, microcontroller, programming, sensor,
- Publikační typ
- časopisecké články MeSH
We present a novel software package for the problem "reconstruction from projections" in electron microscopy. The Ettention framework consists of a set of modular building-blocks for tomographic reconstruction algorithms. The well-known block iterative reconstruction method based on Kaczmarz algorithm is implemented using these building-blocks, including adaptations specific to electron tomography. Ettention simultaneously features (1) a modular, object-oriented software design, (2) optimized access to high-performance computing (HPC) platforms such as graphic processing units (GPU) or many-core architectures like Xeon Phi, and (3) accessibility to microscopy end-users via integration in the IMOD package and eTomo user interface. We also provide developers with a clean and well-structured application programming interface (API) that allows for extending the software easily and thus makes it an ideal platform for algorithmic research while hiding most of the technical details of high-performance computing.
- Klíčová slova
- Block iterative methods, Electron tomography, GPU, High performance computing, OpenCL, Software architecture, Tomographic reconstruction,
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline. The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project. The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.
PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.
- Klíčová slova
- DCE-MRI, challenge, data analysis, glioblastoma, open-science, perfusion,
- MeSH
- algoritmy MeSH
- kontrastní látky * MeSH
- lidé MeSH
- magnetická rezonanční tomografie * metody MeSH
- reprodukovatelnost výsledků MeSH
- software MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- kontrastní látky * MeSH
MOTIVATION: Upgrade and integration of triplex software into the R/Bioconductor framework. RESULTS: We combined a previously published implementation of a triplex DNA search algorithm with visualization to create a versatile R/Bioconductor package 'triplex'. The new package provides functions that can be used to search Bioconductor genomes and other DNA sequence data for occurrence of nucleotide patterns capable of forming intramolecular triplexes (H-DNA). Functions producing 2D and 3D diagrams of the identified triplexes allow instant visualization of the search results. Leveraging the power of Biostrings and GRanges classes, the results get fully integrated into the existing Bioconductor framework, allowing their passage to other Genome visualization and annotation packages, such as GenomeGraphs, rtracklayer or Gviz. AVAILABILITY: R package 'triplex' is available from Bioconductor (bioconductor.org). CONTACT: lexa@fi.muni.cz SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
- MeSH
- algoritmy MeSH
- DNA chemie MeSH
- genomika MeSH
- počítačová grafika MeSH
- sekvenční analýza DNA MeSH
- software * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- DNA MeSH
- triplex DNA MeSH Prohlížeč
