scholarly journals A bioinformatics WGS workflow for clinical Mycobacterium tuberculosis complex isolate analysis, validated using a reference collection extensively characterized with conventional methods and in silico approaches

2021 ◽  
Author(s):  
Bert Bogaerts ◽  
Thomas Delcourt ◽  
Karine Soetaert ◽  
Samira Boarbi ◽  
Pieter-Jan Ceyssens ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
In Silico ◽  
High Performance ◽  
Performance Metrics ◽  
Complete Characterization ◽  
Non Profit ◽  
Public Data ◽  
The Galaxy ◽  
Phenotypic Methods ◽  
Bioinformatics Workflow

The use of whole genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB Complex (MTBC) member isolates allowing complete characterization including (sub)species confirmation and identification (16S, csb/RD, hsp65), Single Nucleotide Polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome MultiLocus Sequence Typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified datasets allowing to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics >99% for all assays, except for spoligotyping where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and non-profit usage through the Galaxy instance of our institute at https://galaxy.sciensano.be.

scholarly journals The COMBAT-TB Workbench: Making powerful M. tuberculosis bioinformatics accessible

2021 ◽  
Author(s):  
Peter van Heusden ◽  
Ziphozahe Mashologu ◽  
Thoba Lose ◽  
Robin Warren ◽  
Alan Christoffels
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Software Components ◽  
Web Interface ◽  
Sample Analysis ◽  
Web Based ◽  
Workflow Execution ◽  
The Galaxy ◽  
User Friendly ◽  
Management Capabilities ◽  
Bioinformatics Workflow

Whole Genome Sequencing (WGS) is a powerful method for detecting drug resistance, genetic diversity and transmission dynamics of Mycobacterium tuberculosis. Implementation of WGS in public health microbiology laboratories is impeded by a lack of user-friendly, automated and semi-automated pipelines. We present the COMBAT-TB workbench, a modular, easy to install application that provides a web based environment for Mycobacterium tuberculosis bioinformatics. The COMBAT-TB Workbench is built using two main software components: the IRIDA Platform for its web-based user interface and data management capabilities and the Galaxy bioinformatics workflow platform for workflow execution. These components are combined into a single easy to install application using Docker container technology. We implemented two workflows, for M. tuberculosis sample analysis and phylogeny, in Galaxy. Building our workflows involved updating some Galaxy tools (Trimmomatic, snippy and snp-sites) and writing new Galaxy tools (snp-dists, TB-Profiler, tb_variant_filter and TB Variant Report). The irida-wf-ga2xml tool was updated to be able to work with recent versions of Galaxy and was further developed into IRIDA plugins for both workflows. In the case of the M. tuberculosis sample analysis an interface was added to update the metadata stored for each sequence sample with results gleaned from the Galaxy workflow output. Data can be loaded into the COMBAT-TB Workbench via the web interface or via the command line IRIDA uploader tool. The COMBAT-TB Workbench application deploys IRIDA, the COMBAT-TB IRIDA plugins, the MariaDB database and Galaxy using Docker containers (https://github.com/COMBAT-TB/irida-galaxy-deploy).

Arylquinolinecarboxamides: Synthesis, in vitro and in silico studies against Mycobacterium tuberculosis

2021 ◽  
Author(s):  
Fostino R. B. Bokosi ◽  
Richard M. Beteck ◽  
Audrey Jordaan ◽  
Ronnet Seldon ◽  
Digby F. Warner ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
In Silico ◽  
In Silico Studies

Persistent memory hash indexes

2021 ◽  
Vol 14 (5) ◽  
pp. 785-798
Author(s):  
Daokun Hu ◽  
Zhiwen Chen ◽  
Jianbing Wu ◽  
Jianhua Sun ◽  
Hao Chen
Keyword(s):  
Future Development ◽  
High Performance ◽  
Performance Metrics ◽  
Comprehensive Evaluation ◽  
State Of The Art ◽  
Hash Tables ◽  
Trade Offs ◽  
Depth Analysis ◽  
Persistent Memory ◽  
Memory Modules

Persistent memory (PM) is increasingly being leveraged to build hash-based indexing structures featuring cheap persistence, high performance, and instant recovery, especially with the recent release of Intel Optane DC Persistent Memory Modules. However, most of them are evaluated on DRAM-based emulators with unreal assumptions, or focus on the evaluation of specific metrics with important properties sidestepped. Thus, it is essential to understand how well the proposed hash indexes perform on real PM and how they differentiate from each other if a wider range of performance metrics are considered. To this end, this paper provides a comprehensive evaluation of persistent hash tables. In particular, we focus on the evaluation of six state-of-the-art hash tables including Level hashing, CCEH, Dash, PCLHT, Clevel, and SOFT, with real PM hardware. Our evaluation was conducted using a unified benchmarking framework and representative workloads. Besides characterizing common performance properties, we also explore how hardware configurations (such as PM bandwidth, CPU instructions, and NUMA) affect the performance of PM-based hash tables. With our in-depth analysis, we identify design trade-offs and good paradigms in prior arts, and suggest desirable optimizations and directions for the future development of PM-based hash tables.

In Silico Modelling of Acceptor Materials by End-capped and π-linker modifications for High-Performance Organic Solar Cells: Estimated PCE > 18%

2021 ◽  
pp. 113555
Author(s):  
Muhammad Yasir Mehboob ◽  
Rania Zaier ◽  
Riaz Hussain ◽  
Muhammad Adnan ◽  
Malik Muhammad Asif Iqbal ◽  
...  
Keyword(s):  
Solar Cells ◽  
Organic Solar Cells ◽  
In Silico ◽  
High Performance ◽  
In Silico Modelling

Estimation of Design Parameters and Performance for a State-of-the-Art Turbofan

2021 ◽  
Author(s):  
Oliver Sjögren ◽  
Carlos Xisto ◽  
Tomas Grönstedt
Keyword(s):  
Performance Metrics ◽  
State Of The Art ◽  
Low Pressure ◽  
Performance Model ◽  
Cycle Performance ◽  
Civil Aviation ◽  
Design Parameters ◽  
Pressure System ◽  
Public Data ◽  
Low Pressure System

Abstract The aim of this study is to explore the possibility of matching a cycle performance model to public data on a state-of-the-art commercial aircraft engine (GEnx-1B). The study is focused on obtaining valuable information on figure of merits for the technology level of the low-pressure system and associated uncertainties. It is therefore directed more specifically towards the fan and low-pressure turbine efficiencies, the Mach number at the fan-face, the distribution of power between the core and the bypass stream as well as the fan pressure ratio. Available cycle performance data have been extracted from the engine emission databank provided by the International Civil Aviation Organization (ICAO), type certificate datasheets from the European Union Aviation Safety Agency (EASA) and the Federal Aviation Administration (FAA), as well as publicly available data from engine manufacturer. Uncertainties in the available source data are estimated and randomly sampled to generate inputs for a model matching procedure. The results show that fuel performance can be estimated with some degree of confidence. However, the study also indicates that a high degree of uncertainty is expected in the prediction of key low-pressure system performance metrics, when relying solely on publicly available data. This outcome highlights the importance of statistic-based methods as a support tool for the inverse design procedures. It also provides a better understanding on the limitations of conventional thermodynamic matching procedures, and the need to complement with methods that take into account conceptual design, cost and fuel burn.

scholarly journals Biosensing with optical fiber gratings

Nanophotonics ◽  
2017 ◽  
Vol 6 (4) ◽  
pp. 663-679 ◽  
Author(s):  
Francesco Chiavaioli ◽  
Francesco Baldini ◽  
Sara Tombelli ◽  
Cosimo Trono ◽  
Ambra Giannetti
Keyword(s):  
Optical Fiber ◽  
Single Molecule ◽  
High Performance ◽  
Performance Metrics ◽  
Surrounding Medium ◽  
Remote Measurement ◽  
Fiber Gratings ◽  
Practical Applications ◽  
Technology Platforms ◽  
Optical Fiber Gratings

AbstractOptical fiber gratings (OFGs), especially long-period gratings (LPGs) and etched or tilted fiber Bragg gratings (FBGs), are playing an increasing role in the chemical and biochemical sensing based on the measurement of a surface refractive index (RI) change through a label-free configuration. In these devices, the electric field evanescent wave at the fiber/surrounding medium interface changes its optical properties (i.e. intensity and wavelength) as a result of the RI variation due to the interaction between a biological recognition layer deposited over the fiber and the analyte under investigation. The use of OFG-based technology platforms takes the advantages of optical fiber peculiarities, which are hardly offered by the other sensing systems, such as compactness, lightness, high compatibility with optoelectronic devices (both sources and detectors), and multiplexing and remote measurement capability as the signal is spectrally modulated. During the last decade, the growing request in practical applications pushed the technology behind the OFG-based sensors over its limits by means of the deposition of thin film overlays, nanocoatings, and nanostructures, in general. Here, we review efforts toward utilizing these nanomaterials as coatings for high-performance and low-detection limit devices. Moreover, we review the recent development in OFG-based biosensing and identify some of the key challenges for practical applications. While high-performance metrics are starting to be achieved experimentally, there are still open questions pertaining to an effective and reliable detection of small molecules, possibly up to single molecule, sensing in vivo and multi-target detection using OFG-based technology platforms.

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