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https://github.com/epistasislab/hibachi

Software tool that creates data sets with particular characteristics. Method and open source software for simulating complex biological and biomedical data to aid in comparing and evaluating machine learning methods.

Proper citation: Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (RRID:SCR_017140) Copy   

•   Source: SciCrunch Registry

http://u-compare.org/

An integrated text mining / natural language processing system based on the Unstructured Information Management Architecture (UIMA) Framework. It allows interoperability of text mining tools and allows the creation of text mining workflows, comparison and visualization of tools. U-Compare can be launched straight from the web or downloaded. As the name implies comparison of components and workflows is a central feature of the system. U-Compare allows sets of components to be run in parallel on the same inputs and then automatically generates statistics for all possible combinations of these components. Once a workflow has been created in U-Compare it can be exported and shared with other users or used with other UIMA compatible tools and so in addition to comparison, U-Compare also functions as a general purpose workflow creation tool. It contains a repository of 50+ biomedical text mining components. These components are included in the U-Compare single-click-to-launch package, ready to use by just drag-and-drop. You can also use this repository independent from the U-Compare system. Link with Taverna It has a link with Taverna for scientific workflows, http://bioinformatics.oxfordjournals.org/content/26/19/2486.abstract, where you can use U-Compare and its workflow from within the Taverna workflow. There are two ways, the U-Compare Taverna plugin and the U-Compare command line mode as a Taverna activity. We have recently integrated it with Peter Murray-Rust''''s OSCAR for Chemistry (see http://www.nactem.ac.uk/cheta/) Web Demo: http://www.nactem.ac.uk/software/cheta/

Proper citation: U-Compare (RRID:SCR_004911) Copy   

•   Source: SciCrunch Registry

http://ccb.jhu.edu/software/FLASH/

Open source software tool to merge paired-end reads from next-generation sequencing experiments. Designed to merge pairs of reads when original DNA fragments are shorter than twice length of reads. Can improve genome assemblies and transcriptome assembly by merging RNA-seq data.

Proper citation: FLASH (RRID:SCR_005531) Copy   

•   Source: SciCrunch Registry

http://restraintsgrid.bmrb.wisc.edu/NRG/MRGridServlet

Original NMR (nuclear magnetic resonance) data as collected for over 2500 protein and nucleic acid structures with corresponding PDB entries. In addition to the original restraints, most of the distance, dihedral angle and RDC restraint data (>85%) were parsed, and those in over 500 entries were converted and filtered. The converted and filtered data sets constitute the Database Of Converted Restraints (DOCR) and the Filtered Restraints Database (FRED) respectively as described in the references. There are 9,672,968 parsed constraints in 7159 entries. (Mar. 2013)

Proper citation: NMR Restraints Grid (RRID:SCR_006127) Copy   

•   Source: SciCrunch Registry

http://mummer.sourceforge.net/

Software package as system for rapidly aligning entire genomes. Alignment tool for DNA and protein sequences. Can align incomplete genomes.

Proper citation: MUMmer (RRID:SCR_018171) Copy   

•   Source: SciCrunch Registry

http://lrpath.ncibi.org/

Web tool to perform gene set enrichment testing. Used to test for predefined biologically relevant gene sets that contain more significant genes from experimental dataset than expected by chance. Logistic regression approach for identifying enriched biological groups in gene expression data.

Proper citation: LRPath (RRID:SCR_018572) Copy   

•   Source: SciCrunch Registry

https://github.com/kilicogluh/limitation-recognizer

Software tool to recognize self acknowledged limitation sentences in biomedical articles. Automatic recognition of self acknowledged limitations in clinical research literature to support efforts in improving research transparency.

Proper citation: Limitation-Recognizer (RRID:SCR_018747) Copy   

•   Source: SciCrunch Registry

http://scratch.proteomics.ics.uci.edu/

Web tool as sequence-based, alignment-free and pathogen-independent predictor of protein antigenicity.Predicts likelihood that protein is protective antigen. Integrated in SCRATCH suite of predictors.

Proper citation: ANTIGENpro (RRID:SCR_018779) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/LOVE

A versatile 1D, 2D and 3D data viewer geared for cross-platform visualization of stereotactic brain data. It is a 3-D viewer that allows volumetric data display and manipulation of axial, sagittal and coronal views. It reads Analyze, Raw-binary and NetCDF volumetric data, as well as, Multi-Contour Files (MCF), LWO/LWS surfaces, atlas hierarchical brain-region labelings ( Brain Trees). It is a portable Java-based software, which only requires a Java interpreter and a 64 MB of RAM memory to run on any computer architecture. LONI_Viz allows the user to interactively overlay and browse through several data volumes, zoom in and out in the axial, sagittal and coronal views, and reports the intensities and the stereo-tactic voxel and world coordinates of the data. Expert users can use LONI_Viz to delineate structures of interest, e.g., sulcal curves, on the 3 cardinal projections of the data. These curves then may be use to reconstruct surfaces representing the topological boundaries of cortical and sub-cortical regions of interest. The 3D features of the package include a SurfaceViewer and a full real-time VolumeRenderer. These allow the user to view the relative positions of different anatomical or functional regions which are not co-planar in any of the axial, sagittal or coronal 2D projection planes. The interactive part of LONI_Viz features a region drawing module used for manual delineation of regions of interest. A series of 2D contours describing the boundary of a region in projection planes (axial, sagittal or coronal) could be used to reconstruct the surface-representation of the 3D outer shell of the region. The latter could then be resliced in directions complementary to the drawing-direction and these complementary contours could be loaded in all tree cardinal views. In addition the surface object could be displayed using the SurfaceViewer. A pre-loading data crop and sub-sampling module allows the user to load and view practically data of any size. This is especially important when viewing cryotome, histological or stained data-sets which may reach 1GB (109 bytes) in size. The user could overlay several pre-registered volumes, change intensity colors and ranges and the inter-volume opacities to visually inspect similarities and differences between the different subjects/modalities. Several image-processing aids provide histogram plotting, image-smoothing, etc. Specific Features: * Region description DataBase * Moleculo-genetic database * Brain anatomical data viewer * BrainMapper tool * Surface (LightWave objects/scenes) and Volume rendering tools * Interactive Contour Drawing tool Implementation Issues: * Applet vs. Application - the software is available as both an applet and a standalone application. The former could be used to browse data from within the LONI database, however, it imposes restrictions on file-size, Internet connection and network-bandwidth and client/server file access. The later requires a local install and configuration of the LONI_Viz software * Extendable object-oriented code (Java), computer architecture independent * Complete online software documentation is available at http://www.loni.ucla.edu/LONI_Viz and a Java-Class documentation is available at http://www.loni.ucla.edu/~dinov/LONI_Vis.dir/doc/LONI_Viz_Java_Docs.html

Proper citation: LONI Visualization Tool (RRID:SCR_000765) Copy   

•   Source: SciCrunch Registry

https://vanvalen.github.io/about/

Software for segmenting individual cells in microscopy images using deep learning. Cell segmentation software.

Proper citation: DeepCell (RRID:SCR_022197) Copy   

•   Source: SciCrunch Registry

http://www.clairlib.org

A suite of open-source Perl modules intended to simplify a number of generic tasks in natural language processing (NLP), information retrieval (IR), and network analysis (NA). Its architecture also allows for external software to be plugged in with very little effort. The latest version of clairlib is 1.06 which was released on March 2009 and includes about 130 modules implementing a wide range of functionalities. Clairlib is distributed in two forms: * Clairlib-core, which has essential functionality and minimal dependence on external software, and * Clairlib-ext, which has extended functionality that may be of interest to a smaller audience. Much can be done using Clairlib on its own. Some of the things that Clairlib can do are: Tokenization, Summarization, Document Clustering, Document Indexing, Web Graph Analysis, Network Generation, Power Law Distribution Analysis, Network Analysis, RandomWalks on Graphs, Tf-IDF, Perceptron Learning and Classification, and Phrase Based Retrieval and Fuzzy OR Queries.

Proper citation: Clair library (RRID:SCR_007019) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pubmedcommons/

A forum where authors who have published in PubMed may comment on any publication in PubMed. Members of PubMed Commons are not anonymous and must agree to certain terms and guidelines concerning appropriate and inapproriate comments.

Proper citation: Pubmed Commons (RRID:SCR_014021) Copy   

•   Source: SciCrunch Registry

https://open.med.harvard.edu/display/SHRINE/Community

Software providing a scalable query and aggregation mechanism that enables federated queries across many independently operated patient databases. This platform enables clinical researchers to solve the problem of identifying sufficient numbers of patients to include in their studies by querying across distributed hospital electronic medical record systems. Through the use of a federated network protocol, SHRINE allows investigators to see limited data about patients meeting their study criteria without compromising patient privacy. This software should greatly enable population-based research, assessment of potential clinical trials cohorts, and hypothesis formation for followup study by combining the EHR assets across the hospital system. In order to obtain the maximum number of cases representing the study population, it is useful to aggregate patient facts across as many sites as possible. Cutting across institutional boundaries necessitates that each hospital IRB remain in control, and that their local authority is recognized for each and every request for patient data. The independence, ownership, and legal responsibilities of hospitals predetermines a decentralized technical approach, such as a federated query over locally controlled databases. The application comes with the SHRINE Core Ontology but it can be used with any ontology, even one that is disease specific. The Core Ontology is designed to enable the widest range of studies possible using facts gathered in the EMR during routine patient care. SHRINE allows multiple ontologies to be used for different research purposes on the same installed systems.

Proper citation: SHRINE (RRID:SCR_006293) Copy   

•   Source: SciCrunch Registry

https://stemcells.nindsgenetics.org/

Cell sources currently include fibroblasts and/or induced pluripotent stem cells for Alzheimer's Disease, Amyotrophic Lateral Sclerosis (ALS), Ataxia-telangiectasia, Frontotemporal Lobar Degeneration (FTD), Huntington's Disease, Parkinson's Disease, and healthy controls. Cell sources, including isogenic cell lines for current and new diseases covered by the NINDS will be added over the next several years.

Proper citation: The NINDS Human Cell and Data Repository (NHCDR) (RRID:SCR_016319) Copy   

•   Source: SciCrunch Registry

http://www.midasplatform.org/

Open-source toolkit that enables the rapid creation of tailored, web-enabled data storage and provides a cohesive system for data management, visualization, and processing. At its core, Midas Platform is implemented as a PHP modular framework with a backend database (PostGreSQL, MySQL and non-relational databases). While the Midas Platform system can be installed and deployed without any customization, the framework has been designed with customization in mind. As building one system to fit all is not optimal, the framework has been extended to support plugins and layouts. Through integration with a range of other open-source toolkits, applications, or internal proprietary workflows, Midas Platform offers a solid foundation to meet the needs of data-centric computing. Midas Platform provides a variety of data access methods, including web, file system and DICOM server interfaces, and facilitates extending the methods in which data is stored to other relational and non-relational databases.

Proper citation: Midas Platform (RRID:SCR_002186) Copy   

•   Source: SciCrunch Registry

http://www.pondr.com/

Web tool to predict order and disorder from amino acid sequence. Used to predict of natural disordered regions in proteins.

Proper citation: PONDR (RRID:SCR_023691) Copy   

•   Source: SciCrunch Registry

https://masst.gnps2.org/microbemasst/

Web taxonomically informed mass spectrometry search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging database of over 60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns.

Proper citation: microbeMASST (RRID:SCR_024713) Copy   

•   Source: SciCrunch Registry

http://hanalyzer.sourceforge.net/

An open-source data integration system designed to assist biologists in explaining the results observed in genome-scale experiments as well as generating new hypotheses. It combines information extraction techniques, semantic data integration, and reasoning and facilitates network visualization. The Hanalyzer source code and binaries are available for download.

Proper citation: Hanalyzer (RRID:SCR_000923) Copy   

•   Source: SciCrunch Registry

https://integrativeomics.shinyapps.io/pseudofun_app/

Software as database and query tool for homologous pseudogene and coding gene families. Collection of human pseudogenes and gene associations. Supports search, graphical visualization and functional analysis of pseudogenes and coding genes based on PGG families.

Proper citation: PseudoFuN (RRID:SCR_017095) Copy   

•   Source: SciCrunch Registry

http://deweylab.biostat.wisc.edu/detonate/

Software tool to evaluate de novo transcriptome assemblies from RNA-Seq data. Consists of RSEM-EVAL and REF-EVAL packages. RSEM-EVAL is reference-free evaluation method. REF-EVAL is reference based and can be used to compare sets of any kinds of genomic sequences.

Proper citation: DETONATE (RRID:SCR_017035) Copy   

•   Source: SciCrunch Registry