scholarly journals BrainQuake: An Open-Source Python Toolbox for the Stereoelectroencephalography Spatiotemporal Analysis

2022 ◽  
Vol 15 ◽  
Author(s):  
Fang Cai ◽  
Kang Wang ◽  
Tong Zhao ◽  
Haixiang Wang ◽  
Wenjing Zhou ◽  
...  
Keyword(s):  
Open Source ◽  
Surface Reconstruction ◽  
High Performance ◽  
Intractable Epilepsy ◽  
Spatiotemporal Analysis ◽  
High Temporal Resolution ◽  
Time Saving ◽  
Brain Surface ◽  
Seizure Onset Zone ◽  
User Friendly

Intracranial stereoelectroencephalography (SEEG) is broadly used in the presurgical evaluation of intractable epilepsy, due to its high temporal resolution in neural activity recording and high spatial resolution within suspected epileptogenic zones. Neurosurgeons or technicians face the challenge of conducting a workflow of post-processing operations with the multimodal data (e.g., MRI, CT, and EEG) after the implantation surgery, such as brain surface reconstruction, electrode contact localization, and SEEG data analysis. Several software or toolboxes have been developed to take one or more steps in the workflow but without an end-to-end solution. In this study, we introduced BrainQuake, an open-source Python software for the SEEG spatiotemporal analysis, integrating modules and pipelines in surface reconstruction, electrode localization, seizure onset zone (SOZ) prediction based on ictal and interictal SEEG analysis, and final visualizations, each of which is highly automated with a user-friendly graphical user interface (GUI). BrainQuake also supports remote communications with a public server, which is facilitated with automated and standardized preprocessing pipelines, high-performance computing power, and data curation management to provide a time-saving and compatible platform for neurosurgeons and researchers.

scholarly journals BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis

2019 ◽  
Author(s):  
Manoj Kumar ◽  
Cameron Thomas Ellis ◽  
Qihong Lu ◽  
Hejia Zhang ◽  
Mihai Capota ◽  
...  
Keyword(s):  
Machine Learning ◽  
Functional Connectivity ◽  
Open Source ◽  
Programming Languages ◽  
High Performance ◽  
Large Scale ◽  
Markov Models ◽  
Matrix Analysis ◽  
Fmri Analysis ◽  
User Friendly

Advanced brain imaging analysis methods, including multivariate pattern analysis (MVPA), functional connectivity, and functional alignment, have become powerful tools in cognitive neuroscience over the past decade. These tools are implemented in custom code and separate packages, often requiring different software and language proficiencies. Although usable by expert researchers, novice users face a steep learning curve. These difficulties stem from the use of new programming languages (e.g., Python), learning how to apply machine-learning methods to high-dimensional fMRI data, and minimal documentation and training materials. Furthermore, most standard fMRI analysis packages (e.g., AFNI, FSL, SPM) focus on preprocessing and univariate analyses, leaving a gap in how to integrate with advanced tools. To address these needs, we developed BrainIAK (brainiak.org), an open-source Python software package that seamlessly integrates several cutting-edge, computationally efficient techniques with other Python packages (e.g., Nilearn, Scikit-learn) for file handling, visualization, and machine learning. To disseminate these powerful tools, we developed user-friendly tutorials (in Jupyter format; https://brainiak.org/tutorials/) for learning BrainIAK and advanced fMRI analysis in Python more generally. These materials cover techniques including: MVPA (pattern classification and representational similarity analysis); parallelized searchlight analysis; background connectivity; full correlation matrix analysis; inter-subject correlation; inter-subject functional connectivity; shared response modeling; event segmentation using hidden Markov models; and real-time fMRI. For long-running jobs or large memory needs we provide detailed guidance on high-performance computing clusters. These notebooks were successfully tested at multiple sites, including as problem sets for courses at Yale and Princeton universities and at various workshops and hackathons. These materials are freely shared, with the hope that they become part of a pool of open-source software and educational materials for large-scale, reproducible fMRI analysis and accelerated discovery.

scholarly journals Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science

2021 ◽  
Vol 6 ◽  
pp. 76
Author(s):  
Mick A. Phillips ◽  
David Miguel Susano Pinto ◽  
Nicholas Hall ◽  
Julio Mateos-Langerak ◽  
Richard M. Parton ◽  
...  
Keyword(s):  
Open Source ◽  
Adaptive Optics ◽  
High Performance ◽  
Medical Science ◽  
Machine Learning Algorithms ◽  
Spatial Light Modulators ◽  
Structured Illumination ◽  
Light Modulators ◽  
Wide Range ◽  
User Friendly

We have developed “Microscope-Cockpit” (Cockpit), a highly adaptable open source user-friendly Python-based Graphical User Interface (GUI) environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses “Python-Microscope” (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.

scholarly journals SPECTRE: a Suite of PhylogEnetiC Tools for Reticulate Evolution

2017 ◽  
Author(s):  
Sarah Bastkowski ◽  
Daniel Mapleson ◽  
Andreas Spillner ◽  
Taoyang Wu ◽  
Monika Balvočiūtė ◽  
...  
Keyword(s):  
Open Source ◽  
Data Structures ◽  
Phylogenetic Trees ◽  
High Performance ◽  
Reticulate Evolution ◽  
Supplementary Information ◽  
Link Type ◽  
Data Structures And Algorithms ◽  
User Friendly ◽  
Split Networks

ABSTRACTSummarySplit-networks are a generalization of phylogenetic trees that have proven to be a powerful tool in phylogenetics. Various ways have been developed for computing such networks, including split-decomposition, NeighborNet, QNet and FlatNJ. Some of these approaches are implemented in the user-friendly SplitsTree software package. However, to give the user the option to adjust and extend these approaches and to facilitate their integration into analysis pipelines, there is a need for robust, open-source implementations of associated data structures and algorithms. Here we present SPECTRE, a readily available, open-source library of data structures written in Java, that comes complete with new implementations of several pre-published algorithms and a basic interactive graphical interface for visualizing planar split networks. SPECTRE also supports the use of longer running algorithms by providing command line interfaces, which can be executed on servers or in High Performance Computing (HPC) environments.AvailabilityFull source code is available under the GPLv3 license at: https://github.com/maplesond/SPECTRESPECTRE’s core library is available from Maven Central at: https://mvnrepository.com/artifactuk.ac.uea.cmp.spectre/coreDocumentation is available at: http://spectre-suite-of-phylogenetic-tools-for-reticulate-evolution.readthedocs.io/en/latest/[email protected] Information (SI)Supplementary information is available at Bioinformatics online.

scholarly journals GIANI: open-source software for automated analysis of 3D microscopy images

2020 ◽  
Author(s):  
David J. Barry ◽  
Claudia Gerri ◽  
Donald M. Bell ◽  
Rocco D’Antuono ◽  
Kathy K. Niakan
Keyword(s):  
Protein Expression ◽  
Open Source ◽  
Cell Fate ◽  
Open Source Software ◽  
High Performance ◽  
Three Dimensional ◽  
Automated Analysis ◽  
Large Numbers ◽  
User Friendly ◽  
High Performance Computing Cluster

AbstractThe study of cellular and developmental processes in physiologically relevant three-dimensional (3D) systems facilitates an understanding of mechanisms underlying cell fate, disease and injury. While cutting-edge microscopy technologies permit the routine acquisition of 3D datasets, there is currently a lack of user-friendly, open-source software to analyse such images. Here we describe GIANI (djpbarry.github.io/Giani), new software for the analysis of 3D images, implemented as a plugin for the popular FIJI platform. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. GIANI enables routine and reproducible batch-processing of large numbers of images and also comes with scripting and command line tools, such that users can incorporate its functionality into their own scripts and easily run GIANI on a high-performance computing cluster. We demonstrate the utility of GIANI by quantifying cell morphology and protein expression in mouse early embryos. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields.

Clin-mNGS: Automated Pipeline for Pathogen Detection from Clinical Metagenomic Data

2020 ◽  
Vol 15 ◽  
Author(s):  
Akshatha Prasanna ◽  
Vidya Niranjan
Keyword(s):  
Antimicrobial Resistance ◽  
High Performance ◽  
Pathogen Detection ◽  
Bacterial Species ◽  
Workflow Management ◽  
Metagenomic Data ◽  
Antimicrobial Resistance Genes ◽  
Culture Independent ◽  
Automated Pipeline ◽  
User Friendly

Background: Since bacteria are the earliest known organisms, there has been significant interest in their variety and biology, most certainly concerning human health. Recent advances in Metagenomics sequencing (mNGS), a culture-independent sequencing technology have facilitated an accelerated development in clinical microbiology and our understanding of pathogens. Objective: For the implementation of mNGS in routine clinical practice to become feasible, a practical and scalable strategy for the study of mNGS data is essential. This study presents a robust automated pipeline to analyze clinical metagenomic data for pathogen identification and classification. Method: The proposed Clin-mNGS pipeline is an integrated, open-source, scalable, reproducible, and user-friendly framework scripted using the Snakemake workflow management software. The implementation avoids the hassle of manual installation and configuration of the multiple command-line tools and dependencies. The approach directly screens pathogens from clinical raw reads and generates consolidated reports for each sample. Results: The pipeline is demonstrated using publicly available data and is tested on a desktop Linux system and a High-performance cluster. The study compares variability in results from different tools and versions. The versions of the tools are made user modifiable. The pipeline results in quality check, filtered reads, host subtraction, assembled contigs, assembly metrics, relative abundances of bacterial species, antimicrobial resistance genes, plasmid finding, and virulence factors identification. The results obtained from the pipeline are evaluated based on sensitivity and positive predictive value. Conclusion: Clin-mNGS is an automated Snakemake pipeline validated for the analysis of microbial clinical metagenomics reads to perform taxonomic classification and antimicrobial resistance prediction.

MackDroid - An Android based Application to monitor devices

2016 ◽  
Vol 9 ◽  
pp. 1
Author(s):  
Maaz Sirkhot ◽  
Ekta Sirwani ◽  
Aishwarya Kourani ◽  
Akshit Batheja ◽  
Kajal Jethanand Jewani
Keyword(s):  
Operating System ◽  
Open Source ◽  
Vital Role ◽  
Mobile Users ◽  
Android Application ◽  
Web Page ◽  
Technological World ◽  
Monitoring Service ◽  
User Friendly

In this technological world, smartphones can be considered as one of the most far-reaching inventions. It plays a vital role in connecting people socially. The number of mobile users using an Android based smartphone has increased rapidly since last few years resulting in organizations, cyber cell departments, government authorities feeling the need to monitor the activities on certain targeted devices in order to maintain proper functionality of their respective jobs. Also with the advent of smartphones, Android became one of the most popular and widely used Operating System. Its highlighting features are that it is user friendly, smartly designed, flexible, highly customizable and supports latest technologies like IoT. One of the features that makes it exclusive is that it is based on Linux and is Open Source for all the developers. This is the reason why our project Mackdroid is an Android based application that collects data from the remote device, stores it and displays on a PHP based web page. It is primarily a monitoring service that analyzes the contents and distributes it in various categories like Call Logs, Chats, Key logs, etc. Our project aims at developing an Android application that can be used to track, monitor, store and grab data from the device and store it on a server which can be accessed by the handler of the application.

scholarly journals Pocket MUSE: an affordable, versatile and high-performance fluorescence microscope using a smartphone

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yehe Liu ◽  
Andrew M. Rollins ◽  
Richard M. Levenson ◽  
Farzad Fereidouni ◽  
Michael W. Jenkins
Keyword(s):  
High Performance ◽  
Point Of Care ◽  
Low Cost ◽  
Consumer Electronics ◽  
Practical Implementation ◽  
The Novel ◽  
Point Of Care Diagnostics ◽  
Optical Module ◽  
Optical Configuration ◽  
User Friendly

AbstractSmartphone microscopes can be useful tools for a broad range of imaging applications. This manuscript demonstrates the first practical implementation of Microscopy with Ultraviolet Surface Excitation (MUSE) in a compact smartphone microscope called Pocket MUSE, resulting in a remarkably effective design. Fabricated with parts from consumer electronics that are readily available at low cost, the small optical module attaches directly over the rear lens in a smartphone. It enables high-quality multichannel fluorescence microscopy with submicron resolution over a 10× equivalent field of view. In addition to the novel optical configuration, Pocket MUSE is compatible with a series of simple, portable, and user-friendly sample preparation strategies that can be directly implemented for various microscopy applications for point-of-care diagnostics, at-home health monitoring, plant biology, STEM education, environmental studies, etc.

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

2017 ◽  
Vol 45 (4) ◽  
pp. 319-328 ◽  
Author(s):  
Lawrence V. Stanislawski ◽  
Kornelijus Survila ◽  
Jeffrey Wendel ◽  
Yan Liu ◽  
Barbara P. Buttenfield
Keyword(s):  
Surface Water ◽  
Open Source ◽  
High Performance ◽  
Water Drainage ◽  
Drainage Networks

scholarly journals An Interactive WebGIS Framework for Coastal Erosion Risk Management

2021 ◽  
Vol 9 (6) ◽  
pp. 567
Author(s):  
Alessandra Capolupo ◽  
Cristina Monterisi ◽  
Alessandra Saponieri ◽  
Fabio Addona ◽  
Leonardo Damiani ◽  
...  
Keyword(s):  
Open Source ◽  
3D Visualization ◽  
Erosion Risk ◽  
Innovative Strategies ◽  
Web Mapping ◽  
Natural Processes ◽  
Multi Scale ◽  
Interactive Interface ◽  
Multi Temporal ◽  
User Friendly

The Italian coastline stretches over about 8350 km, with 3600 km of beaches, representing a significant resource for the country. Natural processes and anthropic interventions keep threatening its morphology, moulding its shape and triggering soil erosion phenomena. Thus, many scholars have been focusing their work on investigating and monitoring shoreline instability. Outcomes of such activities can be largely widespread and shared with expert and non-expert users through Web mapping. This paper describes the performances of a WebGIS prototype designed to disseminate the results of the Italian project Innovative Strategies for the Monitoring and Analysis of Erosion Risk, known as the STIMARE project. While aiming to include the entire national coastline, three study areas along the regional coasts of Puglia and Emilia Romagna have already been implemented as pilot cases. This WebGIS was generated using Free and Open-Source Software for Geographic information systems (FOSS4G). The platform was designed by combining Apache http server, Geoserver, as open-source server and PostgreSQL (with PostGIS extension) as database. Pure javascript libraries OpenLayers and Cesium were implemented to obtain a hybrid 2D and 3D visualization. A user-friendly interactive interface was programmed to help users visualize and download geospatial data in several formats (pdf, kml and shp), in accordance with the European INSPIRE directives, satisfying both multi-temporal and multi-scale perspectives.

Sign in / Sign up

Export Citation Format

Share Document