Data management/Annotation software tools | Cryo-electron microscopy image analysis
Find and compare the best bioinformatics software tools for navigating, sharing and collaboratively annotating massive image data sets of biological specimens acquired by cryo-electron microscopy. Tools are ranked by the biomedical research community.
Hosts heterogeneous tools dedicated to neuroimaging research. BrainVISA aims to help researchers in developing new neuroimaging tools, sharing data and distributing software. It offers a way to define viewers which may use any visualization software. Thanks to its data management functions, the tool can define the data types handled by the software, associate key attributes for indexation, and filename patterns to make the link between the filesystem and the database schema.
Assists users in the fitting and building of atomic models. CCP-EM was developed to provides support for individual scientists to a coherent cryoEM community. It can aid scientists in their use of cryoEM software. It also supports software developers in producing and disseminating robust and user-friendly programs. This application provides generic tools for manipulating and visualizing image and volume data.
Annotates and permits proofreading for large segmented image data. Raveler capabilities for displaying large image datasets depend of disk storage abilities. The tool was applied to an adult Drosophila imaged by scanning electron microscopy (EM), with successive sections ablated away by focused ion beam milling (FIB-SEM).
An open-source, rich web environment to enable highly collaborative analysis of multi-gigapixel imaging data. Cytomine (i) provides remote and collaborative principles, (ii) relies on data models that allow to easily organize and semantically annotate imaging datasets in a standardized way, (iii) efficiently supports high-resolution multi-gigapixel images, (iv) provides mechanisms to readily proofread and share image quantifications produced by machine learning-based image recognition algorithms.
A multi-user web-based collaborative management system for images and volumes which allows users to view multi-terabyte datasets, annotate images with their own annotation schema, and summarize the results. Viking has several key features. (1) It works over the internet using HTTP and supports many concurrent users limited only by hardware. (2) It supports a multi-user, collaborative annotation strategy. (3) It cleanly demarcates viewing and analysis from data collection and hosting. (4) It is capable of applying transformations in real-time. (5) It has an easily extensible user interface, allowing addition of specialized modules without rewriting the viewer.
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.