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https://github.com/SilverLabUCL/SilverLab-Microscope-Software

Software for use with compact Acousto-Optic Lens Microscope (AOLM) developed in the Silver Lab at UCL. Written in LabVIEW. Performs multiple imaging modes and protocols including Z-stacks, multi-plane, single-plane, sub-volume, patches and points. It comes with tools for visualising data acquired with system.

Proper citation: Silver Lab Microscopy Software (RRID:SCR_017456) Copy   

•   Source: SciCrunch Registry

https://scfind.sanger.ac.uk/

Software R package as search tool for single cell RNA-seq data by gene lists. Builds index from scRNA-seq datasets which organizes information in suitable and compact manner so that datasets can be very efficiently searched for either cells or cell types in which given list of genes is expressed.

Proper citation: Scfind (RRID:SCR_017339) Copy   

•   Source: SciCrunch Registry

https://modbase.compbio.ucsf.edu/foxs/

Web server for computing theoretical scattering profile of structure and fitting of experimental profile. Computes SAXS profile of given atomistic model and fits it to experimental profile. Used for structural modeling applications with small angle X-ray scattering data.

Proper citation: FoXS (RRID:SCR_017269) Copy   

•   Source: SciCrunch Registry

https://kimosys.org

Web application for quantitative KInetic MOdels of biological SYStems. Platform includes public data repository of relevant published measurements, including metabolite concentrations, flux data, and enzyme measurements and tools in order to build ODE-based kinetic model. Designed to search, exchange and disseminate experimental data and associated kinetic models for systems modeling community.

Proper citation: Kinetic Models of Biological Systems (KiMoSys) (RRID:SCR_017423) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/Glimma.html

Software package for interactive graphics for gene expression analysis. Generates interactive visualisations for analysis of RNA-sequencing data.

Proper citation: Glimma (RRID:SCR_017389) Copy   

•   Source: SciCrunch Registry

https://github.com/JosephCrispell/homoplasyFinder/wiki

Software tool to identify and annotate homoplasies on phylogeny and sequence alignment. Used to automatically identify any homoplasies present in simulated and real phylogenetic data. Java application that can be used as standalone tool or within statistical programming environment R.

Proper citation: HomoplasyFinder (RRID:SCR_017300) Copy   

•   Source: SciCrunch Registry

https://github.com/Sethupathy-Lab/miRquant

Software tool for accurate annotation and quantification of microRNAs and their isomiRs from small RNA-sequencing data. Provides information on quality of sequencing data, genome mapping statistics, abundance of other types of small RNAs such as tDRs and yDRs, prevalence of post transcriptional modifications.

Proper citation: miRquant (RRID:SCR_017261) Copy   

•   Source: SciCrunch Registry

https://icsd.products.fiz-karlsruhe.de/

Database for completely identified inorganic crystal structures. Collection of known inorganic crystal structures published since 1913, including their atomic coordinates. Includes only data which have passed thorough quality checks. Tool for materials research.

Proper citation: Inorganic Crystal Structure Database (ICSD) (RRID:SCR_017429) Copy   

•   Source: SciCrunch Registry

https://github.com/ISUgenomics/SequelQC

Software tool that calculates key statistics and generates publication quality plots for raw PacBio Sequel data. Open source software for analyzing PacBio Sequel raw sequence data.

Proper citation: SequelQC (RRID:SCR_017279) Copy   

•   Source: SciCrunch Registry

https://hnn.brown.edu/

Open source software package for circuit level interpretation of human EEG/MEG data. Software tool for interpreting cellular and network origin of human MEG/EEG data. Simulates electrical activity of neocortical cells and circuits that generate primary electrical currents underlying EEG/MEG recordings. Designed for researchers and clinicians, without computational neural modeling experience, to develop and test hypothesis on circuit origin of their data.

Proper citation: Human Neocortical Neurosolver (RRID:SCR_017437) Copy   

•   Source: SciCrunch Registry

http://www.bioisis.net

Software JAVA based application for basic analysis of Small Angle X-ray Scattering datasets.

Proper citation: SCÅTTER (RRID:SCR_017271) Copy   

•   Source: SciCrunch Registry

https://wiki.med.harvard.edu/SysBio/Megason/GoFigure

GoFigure is a software platform for quantitating complex 4d in vivo microscopy based data in high-throughput at the level of the cell. A prime goal of GoFigure is the automatic segmentation of nuclei and cell membranes and in temporally tracking them across cell migration and division to create cell lineages. GoFigure v2.0 is a major new release of our software package for quantitative analysis of image data. The research focuses on analyzing cells in intact, whole zebrafish embryos using 4d (xyzt) imaging which tends to make automatic segmentation more difficult than with 2d or 2d+time imaging of cells in culture. This resource has developed an automatic segmentation pipeline that includes ICA based channel unmixing, membrane nuclear channel subtraction, Gaussian correlation, shape models, and level set based variational active contours. GoFigure was designed to meet the challenging requirements of in toto imaging. In toto imaging is a technology that we are developing in which we seek to track all the cell movements and divisions that form structures during embryonic development of zebrafish and to quantitate protein expression and localization on top of this digital lineage. For in toto imaging, GoFigure uses zebrafish embryos in which the nuclei and cell membranes have been marked with 2 different color fluorescent proteins to allow cells to be segmented and tracked. A transgenic line in a third color can be used to mark protein expression and localization using a genetic approach that this resource developed called FlipTraps or using traditional transgenic approaches. Embryos are imaged using confocal or 2-photon microscopy to capture high-resolution xyzt image sets used for cell tracking. The GoFigure GUI will provide many tools for visualization and analysis of bioimages. Since fully automatic segmentation of cells is never perfect, GoFigure will provide easy to use tools for semi-automatically and manually adding, deleting, and editing traces in 2d (figures-xy, xz, or yz), 3d (meshes- xyz), 4d (tracks- xyzt) and 4d+cell division (lineages). GoFigure will also provide a number of views into complex image data sets including 3d XYZ and XYT image views, tabular list views of traces, histograms, and scattergrams. Importantly, all these views will be linked together to allow the user to explore their data from multiple angles. Data will be easily sorted and color-coded in many ways to explore correlations in higher dimensional data. The GoFigure architecture is designed to allow additional segmentation, visualization, and analysis filters to be plugged in. Sponsors: GoFigure is developed by Harvard University., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Harvard Medical School, Department of Systems Biology: The Megason Lab -GoFigure Software (RRID:SCR_008037) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/cancer/software/genecluster2/gc2.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding supervised classification, gene selection, class discovery and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting (WV) and k-nearest neighbor (KNN) algorithms, a module for systematically finding and evaluating clustering via self-organizing maps, and modules for marker gene selection and heat map visualization that allow users to view and sort samples and genes by many criteria. It enhances the clustering capabilities of GeneCluster 1.0 by adding a module for batch SOM clustering, and also includes a marker gene finder based on a KNN analysis and a visualization module. GeneCluster 2.0 is a stand-alone Java application and runs on any platform that supports the Java Runtime Environment version 1.3.1 or greater.

Proper citation: GeneCluster 2: An Advanced Toolset for Bioarray Analysis (RRID:SCR_008446) Copy   

•   Source: SciCrunch Registry

http://connectomics.org/viewer

Extensible, scriptable, pythonic software tool for visualization and analysis in structural neuroimaging research on many spatial scales. Employing the Connectome File Format, diverse data such as networks, surfaces, volumes, tracks and metadata are handled and integrated. The field of Connectomics research benefits from recent advances in structural neuroimaging technologies on all spatial scales. The need for software tools to visualize and analyze the emerging data is urgent. The ConnectomeViewer application was developed to meet the needs of basic and clinical neuroscientists, as well as complex network scientists, providing an integrative, extensible platform to visualize and analyze Connectomics data. With the Connectome File Format, interlinking different datatypes such as hierarchical networks, surface data, volumetric data is easy and might provide new ways of analyzing and interacting with data. Furthermore, ConnectomeViewer readily integrates with: * ConnectomeWiki: a semantic knowledge base representing connectomics data at a mesoscale level across various species, allowing easy access to relevant literature and databases. * ConnectomeDatabase: a repository to store and disseminate Connectome files.

Proper citation: ConnectomeViewer: Multi-Modal Multi-Level Network Visualization and Analysis (RRID:SCR_008312) Copy   

•   Source: SciCrunch Registry

http://www.biobankcentral.org/resource/wwibb.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 27, 2013. Web-based portal to connect all the constituencies in the global biobank community. The project seeks to increase the transparency and accessibility of the scientific research process by connecting researchers with an additional source of funding - microinvestments received from the broader online community. In exchange for these public investments, researchers will maintain research logs detailing the play-by-play progress made in their project, as well as publishing all of their data in a public database under a science commons license. These research projects, in turn, will serve to continually update a research-based neuroscience-based human brain & body curriculum. Biobanks are the meeting point of two major information trends in biomedical research: the generation of huge amounts of genomic and other laboratory data, and the electronic capture and integration of patient clinical records. They are comprised of large numbers of human biospecimens supplemented with clinical data. Biobanks when implemented effectively can harness the power of both genomic and clinical data and serve as a critical bridge between basic and applied research, linking laboratory to patient and getting to cures faster. As science and technology leaders work to address the many challenges facing U.S. biobanks logistical, technical, ethical, financial, intellectual property, and IT BioBank Central will serve as an accurate and timely source of knowledge and news about biorepositories and their role in research and drug development. The Web site also provides a working group venue, patient and public education programs, and a forum for international collaboration and harmonization of best practices.

Proper citation: BioBank Central (RRID:SCR_008645) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=nuro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Portal that provides researchers with easy access to data on rat genes, QTLs, strain models, biological processes and pathways related to neurological diseases. This resource also includes dynamic data analysis tools.

Proper citation: Rat Genome Database: Neurological Disease Portal (RRID:SCR_008685) Copy   

•   Source: SciCrunch Registry

http://pubchem.ncbi.nlm.nih.gov/

Collection of information about chemical structures and biological properties of small molecules and siRNA reagents hosted by the National Center for Biotechnology Information (NCBI).

Proper citation: PubChem (RRID:SCR_004284) Copy   

•   Source: SciCrunch Registry

http://figshare.com/

Repository for all data, figures, theses, publications, posters, presentations, filesets, videos, datasets, negative data in a citable, shareable and discoverable manner with Digital Object Identifiers. Allows to upload any file format to be made visualisable in the browser so that figures, datasets, media, papers, posters, presentations and filesets can be disseminated in a way that the current scholarly publishing model does not allow. Features integration with ORCID, Symplectic Elements, can import items from Github and is a source tracked by Altmetric.com. Figshare gives users unlimited public space and 1GB of private storage space for free. Data are digitally preserved by CLOCKSS. Supported by Digital Science, a division of Macmillan Publishers Limited, as a community-based, open science project that retains its autonomy.

Proper citation: FigShare (RRID:SCR_004328) Copy   

•   Source: SciCrunch Registry

http://eupathdb.org/eupathdb/

EuPathDB integrates numerous database resources and multiple data types. The phylum Apicomplexa comprises veterinary and medically important parasitic protozoa including human pathogenic species of genera Cryptosporidium, Plasmodium and Toxoplasma. ApiDB serves not only as database but unifies access to three major existing individual organism databases, PlasmoDB.org, ToxoDB.org and CryptoDB.org, and integrates these databases with data available from additional sources. Through ApiDB site, users may pose queries and search all available apicomplexan data and tools, or they may visit individual component organism databases. EuPathDB Bioinformatics Resource Center for Biodefense and Emerging/Re-emerging Infectious Diseases is a portal for accessing genomic-scale datasets associated with eukaryotic pathogens.

Proper citation: Eukaryotic Pathogen Database Resources (RRID:SCR_004512) Copy   

•   Source: SciCrunch Registry

http://www.embl.de/

Intergovernmental organisation funded by public research money from its member states in Europe. Groups and laboratories perform basic research in molecular biology and molecular medicine, training for scientists, students and visitors. Provides development of services, new instruments and methods, data and technology in its member states.

Proper citation: European Molecular Biology Laboratory (RRID:SCR_004473) Copy   

•   Source: SciCrunch Registry