An extension of the OMERO.web client that provides the ability to search for images by their content (e.g., subcellular patterns) rather than just by their annotations. It was developed by the Murphy group at Carnegie Mellon University. OMERO.searcher 1) finds images whose content, as reflected by subcellular location image features, is similar to one or more query images, 2) can use positive and/or negative examples 3) can be iterative, meaning it allows the user to refine the search results (a process referred to as relevance feedback).
Gathers various modular functions for analyzing plants images. PlantCV is an open and community-based software providing a library of Python scripts that can be used for various features such as quantitative processing, normalization or leaf segmentation as well as for the construction of processing pipelines. It aims to be a flexible platform that permits the analysis of data from several plant phenotyping systems.
Monitors bioluminescent reporter distributions. InVivoPLOT is a software composed of a body-conforming animal mold (BCAM), a multi-view mirror gantry, an organ probability map (OPM), and a luminescence source for reconstruction algorithm for whole-body BLt. It includes multiples features including the ability to quantitate in vivo bioluminescent targets across different animals and time points and to perform image data analysis without operator bias.
Aligns linearly correlated signals or images. The RASL solution builds on advances in rank minimization and formulates the batch alignment problem as the solution of a sequence of convex programs. The algorithm achieves pixelwise accuracy over a wide range of misalignments. This tool serves as a preprocessing step for a training set of images.
A manually curated database and software tool for planarian regenerative experiments, based on a mathematical graph formalism. Planform contains more than a thousand experiments from the main publications in the planarian literature. The software tool provides the user with a graphical interface to easily interact with and mine the database. The presented system is a valuable resource for the regeneration community and, more importantly, will pave the way for the application of novel artificial intelligence tools to extract knowledge from this dataset.
A Java library facilitating bi-directional interoperability between MATLAB and ImageJ applications. ImageJ-MATLAB provides an extensible and bidirectional bridge for mutual exchange of data between these two environments. The foundation of ImageJ-MATLAB consists of two Converter plugins: enabling ImageJ Datasets and MATLAB matrices to be freely exchanged within the SciJava framework. Both directions of conversion use the third-party MATLABControl library to manage interaction with a MATLAB instance.
Automatically tracks moving cells over longer period of time. CGE consists of two ImageJ plugins: (1) CGE_Preprocessor that precomputes all data required for the recording, and (2) CGE_Recorder that uses the data produced by the first plugin and interacts with the user to determine the trajectory and the outline of a nucleus. The software allows one to study the different features and changes of cells with significantly varying locations and protein expression levels imaged over a period of several days.
A software package for automatic phenotyping in C. elegans included in QuantWorm. WormGender is designed for accurate quantification of sex ratio in Caenorhabditis elegans. The software functions include, i) automatic recognition and counting of adult hermaphrodites and males, ii) a manual inspection feature that enables manual correction of errors, and iii) flexibility to use new training images to optimize the software for different imaging conditions. We evaluated the performance of our software by comparing manual and automated assessment of sex ratio. Our data showed that the WormGender software provided overall accurate sex ratio measurements.
Provides accurate scores of a colony size across a very wide range of sizes, including very small ones that might not be picked up at all by imaging-based approaches. PHENOS combines multiple output files from the microplate readers and automatically generates a variety of data visualizations, and output files containing various growth curve summary values. It also offers a viable approach to growth phenotyping.
Imputes missing values in large-scale high-dimensional phenome data. phenomeImpute contains four variations of K-nearest-neighbor (KNN) methods and was compared with two existing methods, multivariate imputation by chained equations and missForest. The four variations are imputation by variables (KNN-V), by subjects (KNN-S), their weighted hybrid (KNN-H) and an adaptively weighted hybrid (KNN-A). The results show that Imputation of missing values with low imputability measures increased imputation errors greatly and could potentially deteriorate downstream analyses.
Automates visualization, analysis and exploration of complex and highly resolved microbial growth data. PRECOG allows the user to quality control, interact with and evaluate microbial growth data with ease, speed and accuracy, also in cases of non-standard growth dynamics. It filters the raw optical densities in a three-step procedure to remove or reduce noise and bias. PREGOG’s data filtering has been tested by comparing its performance to a multi-layered neural networks noise reduction filter.
Automates the characterization of dye decolorization in fungal strains. DecoFungi is based on a transfer learning method that uses the output of a deep neural network to train a complete classifier for the target task. It allows to: analyze an image, analyze an image with its control image, analyze a zip file, and analyze a zip file containing a control image. This tool decreases the burden and subjectivity of visually classifying the dye decolorization level.
Analyses data in the context of dithionite scramblase assays. flippant allows to analyze data from statistical computing and graphics and arrives at publication-grade graphics that offer extensive facilities for individual optimization and adaptation. It provides a platform for review, dissemination and extension of the strategies it employs. The tool was tested by reanalyzing a subset of data. It shows identical trends and close matches of the results, supporting identical conclusions.
Enables analysis and visualization of collected spectral data. Specalyzer is a web browser that aims to aid in the quality control, pre-processing, estimation of vegetation indices (VIs) and visualization of the spectral reflectance data. Information about the replicates can be optionally included in the attribute file and various plots can be created by grouping the samples by the provided attributes.
Adjusts an image-based dataset so that brightness, contrast, and color profile is standardized. PhenotyperCV is an image standardization method that consists of a collection of linear models that adjusts pixel tuples based on a reference panel of colors. The software was developed for segmenting and measuring plants from the Bellweather Phenotyping Facility. It supplies a measure of deviation from an image to a reference and can be used to identify sources of variance in an image set.
Serves for large-scale plant species identification. DWSRC allows users to recognize plant species. It can generate discriminative sparse codes that can be used to represent the test sample by combining both linearity and locality information for improving recognition performance. It aims to exploit the locality and similarity of the original dataset and the test samples by sparsely representing the test samples.
Allows processing raw ratiometric biosensor images into fully corrected "ratio maps" or "activation maps” - images. Biosensor Processing includes, for quantitative widefield imaging of ratiometric biosensors, application of all necessary image corrections needed. This tool follows a 6-steps procedure: (i) shading correction; (ii) background subtraction; (iii) image masking; (iv) automated image registration; (v) image shear, rotation and scaling correction; and (vi) ratio calculation.
A software package for running highly comparative time-series analysis. hctsa automates the selection of quantitative phenotypes from time-series data by leveraging a large and interdisciplinary literature on time-series analysis. hctsa allows thousands of time-series analysis features to be extracted from time series (or a time-series dataset), as well as tools for normalizing and clustering the data, producing low-dimensional representations of the data, identifying discriminating features between different classes of time series, learning multivariate classification models using large sets of time-series features, finding nearest matches to a time series of interest, and a range of other visualization and analysis functionality.
Deduces microbial mutation rates from fluctuation assay data. rSalvador is a R package that provides various computational method for computing maximum likelihood (ML) estimates and likelihood ratio-based confidence intervals. The application can also be used to compare mutation rates using likelihood ratio tests and to compute mutant cell distribution and plot log-likelihood functions, simulate fluctuation experiments as well as determine sample size.
Smoothes an image without altering its edges. BEEPS is an ImageJ plugin that consists in a version of the bi-exponential filter with adaptive weights. The software performs edge-preserving smoothing, while producing results that closely mimic those of the bilateral filter. It transforms an input image into an output image of the same size.