Flame: an open source framework for model development, hosting, and usage in production environments.
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ABSTRACT:
SUBMITTER: Pastor M
PROVIDER: S-EPMC8054391 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Observational and experimental studies of rodent voiding behaviors have greatly contributed to our understanding of lower urinary tract function including the complex social, environmental, and internal stimuli that affect voiding in health and models of disease. Void spot assays (VSA), cystometry (awake or anesthetized), and uroflowmetry are techniques commonly used in rodent models to assess voiding. Uroflowmetry is non-invasive and can be performed multiple times in the same freely moving animals and can be used to generate synchronized video corresponding to each void to characterize micturition patterns (e.g., droplets versus solid stream). However, approaches to evaluate uroflowmetry in rodent models vary widely across laboratories. Most importantly, an open access software to run these tests is not freely available (although complete systems are commercially available), limiting use of this important assay. We developed the Void Sorcerer, an uroflowmetry system for mice for reliable determination of frequency, voided volume, voiding duration, interval times between micturitions, and flow rate. This report provides a detailed description of how to build this system and includes open access software for developing uroflowmetry capability in their laboratories and improve upon it in a cost-effective manner. Our goals are to improve access, increase reproducibility among laboratories, and facilitate standardizing testing procedures.
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Project description:Advances in microscopy technology have led to the creation of high-throughput microscopes that are capable of generating several hundred gigabytes of images in a few days. Analyzing such wealth of data manually is nearly impossible and requires an automated approach. There are at present a number of open-source and commercial software packages that allow the user to apply algorithms of different degrees of sophistication to the images and extract desired metrics. However, the types of metrics that can be extracted are severely limited by the specific image processing algorithms that the application implements, and by the expertise of the user. In most commercial software, code unavailability prevents implementation by the end user of newly developed algorithms better suited for a particular type of imaging assay. While it is possible to implement new algorithms in open-source software, rewiring an image processing application requires a high degree of expertise. To obviate these limitations, we have developed an open-source high-throughput application that allows implementation of different biological assays such as cell tracking or ancestry recording, through the use of small, relatively simple image processing modules connected into sophisticated imaging pipelines. By connecting modules, non-expert users can apply the particular combination of well-established and novel algorithms developed by us and others that are best suited for each individual assay type. In addition, our data exploration and visualization modules make it easy to discover or select specific cell phenotypes from a heterogeneous population.CellAnimation is distributed under the Creative Commons Attribution-NonCommercial 3.0 Unported license (http://creativecommons.org/licenses/by-nc/3.0/). CellAnimationsource code and documentation may be downloaded from www.vanderbilt.edu/viibre/software/documents/CellAnimation.zip. Sample data are available at www.vanderbilt.edu/viibre/software/documents/movies.zip.walter.georgescu@vanderbilt.eduSupplementary data available at Bioinformatics online.
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Project description:UnlabelledBioJava is an open-source project for processing of biological data in the Java programming language. We have recently released a new version (3.0.5), which is a major update to the code base that greatly extends its functionality.ResultsBioJava now consists of several independent modules that provide state-of-the-art tools for protein structure comparison, pairwise and multiple sequence alignments, working with DNA and protein sequences, analysis of amino acid properties, detection of protein modifications and prediction of disordered regions in proteins as well as parsers for common file formats using a biologically meaningful data model.AvailabilityBioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website (http://www.biojava.org). BioJava requires Java 1.6 or higher. All inquiries should be directed to the BioJava mailing lists. Details are available at http://biojava.org/wiki/BioJava:MailingLists.
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Project description:BACKGROUND:As molecular biology is creating an increasing amount of sequence and structure data, the multitude of software to analyze this data is also rising. Most of the programs are made for a specific task, hence the user often needs to combine multiple programs in order to reach a goal. This can make the data processing unhandy, inflexible and even inefficient due to an overhead of read/write operations. Therefore, it is crucial to have a comprehensive, accessible and efficient computational biology framework in a scripting language to overcome these limitations. RESULTS:We have developed the Python package Biotite: a general computational biology framework, that represents sequence and structure data based on NumPyndarrays. Furthermore the package contains seamless interfaces to biological databases and external software. The source code is freely accessible at https://github.com/biotite-dev/biotite . CONCLUSIONS:Biotite is unifying in two ways: At first it bundles popular tasks in sequence analysis and structural bioinformatics in a consistently structured package. Secondly it adresses two groups of users: novice programmers get an easy access to Biotite due to its simplicity and the comprehensive documentation. On the other hand, advanced users can profit from its high performance and extensibility. They can implement their algorithms upon Biotite, so they can skip writing code for general functionality (like file parsers) and can focus on what their software makes unique.
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Project description:The Java BioWareHouse (JBioWH) project is an open-source platform-independent programming framework that allows a user to build his/her own integrated database from the most popular data sources. JBioWH can be used for intensive querying of multiple data sources and the creation of streamlined task-specific data sets on local PCs. JBioWH is based on a MySQL relational database scheme and includes JAVA API parser functions for retrieving data from 20 public databases (e.g. NCBI, KEGG, etc.). It also includes a client desktop application for (non-programmer) users to query data. In addition, JBioWH can be tailored for use in specific circumstances, including the handling of massive queries for high-throughput analyses or CPU intensive calculations. The framework is provided with complete documentation and application examples and it can be downloaded from the Project Web site at http://code.google.com/p/jbiowh. A MySQL server is available for demonstration purposes at hydrax.icgeb.trieste.it:3307. Database URL: http://code.google.com/p/jbiowh.
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Project description:The concept of complex acoustic environments has appeared in several unrelated research areas within acoustics in different variations. Based on a review of the usage and evolution of this concept in the literature, a relevant framework was developed, which includes nine broad characteristics that are thought to drive the complexity of acoustic scenes. The framework was then used to study the most relevant characteristics for stimuli of realistic, everyday, acoustic scenes: multiple sources, source diversity, reverberation, and the listener's task. The effect of these characteristics on perceived scene complexity was then evaluated in an exploratory study that reproduced the same stimuli with a three-dimensional loudspeaker array inside an anechoic chamber. Sixty-five subjects listened to the scenes and for each one had to rate 29 attributes, including complexity, both with and without target speech in the scenes. The data were analyzed using three-way principal component analysis with a (2 3 2) Tucker3 model in the dimensions of scales (or ratings), scenes, and subjects, explaining 42% of variation in the data. "Comfort" and "variability" were the dominant scale components, which span the perceived complexity. Interaction effects were observed, including the additional task of attending to target speech that shifted the complexity rating closer to the comfort scale. Also, speech contained in the background scenes introduced a second subject component, which suggests that some subjects are more distracted than others by background speech when listening to target speech. The results are interpreted in light of the proposed framework.
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Project description:SummaryThe Python-based, open-source eMZed framework was developed for mass spectrometry (MS) users to create tailored workflows for liquid chromatography (LC)/MS data analysis. The goal was to establish a unique framework with comprehensive basic functionalities that are easy to apply and allow for the extension and modification of the framework in a straightforward manner. eMZed supports the iterative development and prototyping of individual evaluation strategies by providing a computing environment and tools for inspecting and modifying underlying LC/MS data. The framework specifically addresses non-expert programmers, as it requires only basic knowledge of Python and relies largely on existing successful open-source software, e.g. OpenMS.AvailabilityThe framework eMZed and its documentation are freely available at http://emzed.biol.ethz.ch/. eMZed is published under the GPL 3.0 license, and an online discussion group is available at https://groups.google.com/group/emzed-users.Supplementary informationSupplementary data are available at Bioinformatics online.
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