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https://bibiserv.cebitec.uni-bielefeld.de/pkiss

Software tool for folding RNA secondary structures, including two limited classes of pseudoknots. Performs abstract shape analysis for structures holding pseudoknots up to complexity of kissing hairpin motifs. Successor of pknotsRG. Used for secondary structure prediction including kissing hairpin motifs.

Proper citation: pKiss (RRID:SCR_017256) Copy   

•   Source: SciCrunch Registry

http://research.mssm.edu/integrative-network-biology/Software.html

Software tool as probabilistic multi omics data matching procedure to curate data, identify and correct data annotation and errors in large databases. Used to check potential labeling errors in profiles where number of cis relationships is small, such as miRNA and RPPA profiles.

Proper citation: proMODMatcher (RRID:SCR_017219) Copy   

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https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger

Software tool as set of analysis pipelines that process chromium single cell RNA-seq output to align reads, generate feature-barcode matrices and perform clustering and gene expression analysis by 10xGenomics.

Proper citation: Cell Ranger (RRID:SCR_017344) Copy   

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https://github.com/aidenlab/juicer.git

Software platform for analyzing kilobase resolution Hi-C data. Open source tool for analyzing terabase scale Hi-C datasets. Allowes to transform raw sequence data into normalized contact maps.

Proper citation: Juicer (RRID:SCR_017226) Copy   

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http://snf-515788.vm.okeanos.grnet.gr/

Web tool for integrating human and mouse microRNAs in pathways.Pathway analysis web-server, providing statistics, while being able to accommodate advanced pipelines. Web server for assessment of miRNA regulatory roles and identification of controlled pathways. Supports all analyses for KEGG molecular pathways and Gene Ontology (GO) in seven species (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Caenorhabditis elegans, Gallus gallus and Danio rerio).DIANA miRPath v.2.0 includes investigating combinatorial effect of microRNAs in pathways.DIANA-miRPath v3.0 includes deciphering microRNA function with experimental support., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DIANA-mirPath (RRID:SCR_017354) Copy   

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http://pathwaynet.princeton.edu/

Web user interface for interaction predictions of human gene networks and integrative analysis of user data types that takes advantage of data from diverse tissue and cell-lineage origins. Predicts presence of functional association and interaction type among human genes or its protein products on whole genome scale. Used to analyze experimetnal gene in context of interaction networks.

Proper citation: PathwayNet (RRID:SCR_017353) Copy   

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https://www.keyence.co.jp/products/microscope/fluorescence-microscope/bz-8100/models/bz-h1a/

Software tool as analysis application BZ-H1A by Keyence, Japan for fluorescence microscope BZ-8100 series.

Proper citation: BZ Analyzer software (RRID:SCR_017205) Copy   

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http://relacs.sourceforge.net/

Software platform for closed loop data acquisition, online analysis, and stimulus generation specifically designed for, but not limited to, electrophysiological recordings.

Proper citation: Relacs (RRID:SCR_017280) Copy   

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https://www.mbfbioscience.com/vesselucida360

Software tool for visualization and automatic reconstruction of microvascular networks in 3D environment with built-in analysis tools by MBF Bioscience.

Proper citation: Vesselucida 360 (RRID:SCR_017320) Copy   

•   Source: SciCrunch Registry

http://bioinf.cs.ucl.ac.uk/psipred/

Web tool as secondary structure prediction method, incorporating two feed forward neural networks which perform analysis on output obtained from PSI-BLAST. Web server offering analyses of protein sequences.

Proper citation: PSIPRED (RRID:SCR_010246) Copy   

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https://www.mdc-berlin.de/8551903/en/research/research_teams/systems_biology_of_gene_regulatory_elements/projects/miRDeep

Software tool to identify known and novel miRNA genes in seven animal clades by analyzing sequenced RNAs. Used for discovering known and novel miRNAs from small RNA sequencing data.

Proper citation: miRDeep (RRID:SCR_010829) Copy   

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http://neuromorphometrics.com

Neuromorphometrics provides brain labeling and measurement services. Given raw MRI brain scans, we make precise quantitative measurements of the volume, shape, and location of specific neuroanatomical structures. Web tool for brain measurement services. Used for modeling living human brain and make quantitative measurements of volume, shape, and location of specific neuroanatomical structures using given MRI brain scans. Automated analyses are manually guided, inspected and certified by a neuroanatomical expert. Resource of neuroanatomically labeled MRI brain scans database. Resource for neuroanatomical localization and identification: NeuAtlas.

Proper citation: Neuromorphometrics (RRID:SCR_005656) Copy   

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http://thea.unice.fr/index-en.html

THIS RESOURCE IS NO LONGER IN SERVICE, on documented July 16, 2012. An integrated information processing system dedicated to the analysis of post-genomic data. It allows automatic annotation of data issued from classification systems with selected biological information (including the Gene Ontology). Users can either manually search and browse through these annotations, or automatically generate meaningful generalizations according to statistical criteria (data mining). Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: THEA - Tools for High-throughput Experiments Analysis (RRID:SCR_005802) Copy   

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http://vortex.cs.wayne.edu/projects.htm#Onto-Express

The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independently of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express (OE) as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. We demonstrated the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer data sets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms (Draghici et.al, Genomics, 81(2), 2003). Other results obtained with Onto-Express can be found in Khatri et.al., Genomics. 79(2), 2002. Custom level of abstraction of the Gene Ontology. User account required. Platform: Online tool

Proper citation: Onto-Express (RRID:SCR_005670) Copy   

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http://www.clipz.unibas.ch/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 20,2019.Database and analysis environment for experimentally determined binding sites of RNA-binding proteins. It supports the automatic functional annotation of short reads resulting primarily from crosslinking and immunoprecipitation experiments (CLIP) performed with RNA-binding proteins in order to identify the binding sites of these proteins. The functional annotation could be also applied to short reads resulting from other types of experiments such as mRNA-Seq, Digital Gene Expression, small RNA cloning, etc. The platform enables visualization and mining of individual data sets as well as analysis involving multiple experimental data sets. The platform can support collaborative projects involving multiple users and groups of users as well as public and private datasets.

Proper citation: CLIPZ (RRID:SCR_005755) Copy   

•   Source: SciCrunch Registry

http://users.loni.ucla.edu/~shattuck/brainsuite/

Suite of image analysis tools designed to process magnetic resonance images (MRI) of the human head. BrainSuite provides an automatic sequence to extract genus-zero cortical surface mesh models from the MRI. It also provides a set of viewing tools for exploring image and surface data. The latest release includes graphical user interface and command line versions of the tools. BrainSuite was specifically designed to guide its users through the process of cortical surface extraction. NITRC has written the software to require minimal user interaction and with the goal of completing the entire process of extracting a topologically spherical cortical surface from a raw MR volume within several minutes on a modern workstation. The individual components of BrainSuite may also be used for soft tissue, skull and scalp segmentation and for surface analysis and visualization. BrainSuite was written in Microsoft Visual C using the Microsoft Foundation Classes for its graphical user interface and the OpenGL library for rendering. BrainSuite runs under the Windows 2000 and Windows XP Professional operating systems. BrainSuite features include: * Sophisticated visualization tools, such as MRI visualization in 3 orthogonal views (either separately or in 3D view), and overlayed surface visualization of cortex, skull, and scalp * Cortical surface extraction, using a multi-stage user friendly approach. * Tools including brain surface extraction, bias field correction, voxel classification, cerebellum removal, and surface generation * Topological correction of cortical surfaces, which uses a graph-based approach to remove topological defects (handles and holes) and ensure a tessellation with spherical topology * Parameterization of generated cortical surfaces, minimizing a harmonic energy functional in the p-norm * Skull and scalp surface extraction

Proper citation: BrainSuite (RRID:SCR_006623) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.ubc.ca/ermineJ/

Data analysis software for gene sets in expression microarray data or other genome-wide data that results in rankings of genes. A typical goal is to determine whether particular biological pathways are doing something interesting in the data. The software is designed to be used by biologists with little or no informatics background. A command-line interface is available for users who wish to script the use of ermineJ. Major features include: * Implementation of multiple methods for gene set analysis: ** Over-representation analysis ** A resampling-based method that uses gene scores ** A rank-based method that uses gene scores ** A resampling-based method that uses correlation between gene expression profiles (a type of cluster-enrichment analysis). * Gene sets receive statistical scores (p-values), and multiple test correction is supported. * Support of the Gene Ontology terminology; users can choose which aspects to analyze. * User files use simple text formats. * Users can modify gene sets or create new ones. * The results can be visualized within the software. * It is simple to compare multiple analyses of the same data set with different settings. * User-definable hyperlinks are provided to external sites to allow more efficient browsing of the results. * For programmers, there is a command line interface as well as a simple application programming interface that can be used to plug ermineJ functionality into your own code Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: ErmineJ (RRID:SCR_006450) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ena/

Public archive providing a comprehensive record of the world''''s nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. All submitted data, once public, will be exchanged with the NCBI and DDBJ as part of the INSDC data exchange agreement. The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources including submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centers and routine and comprehensive exchange with their partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature. ENA is made up of a number of distinct databases that includes the EMBL Nucleotide Sequence Database (Embl-Bank), the newly established Sequence Read Archive (SRA) and the Trace Archive. The main tool for downloading ENA data is the ENA Browser, which is available through REST URLs for easy programmatic use. All ENA data are available through the ENA Browser. Note: EMBL Nucleotide Sequence Database (EMBL-Bank) is entirely included within this resource.

Proper citation: European Nucleotide Archive (ENA) (RRID:SCR_006515) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/interpro

Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.

Proper citation: InterPro (RRID:SCR_006695) Copy   

•   Source: SciCrunch Registry

http://www.mitk.org/DiffusionImaging

A selection of image analysis algorithms for the processing of diffusion-weighted MR images. Features & Highlights * Tensor and q-ball reconstruction * Glyph visualization * Quantification and partial volume clustering of tensor and q-ball images * Global fiber tractography, visualization, and tract post-processing * Brain network statistics and visualization (connectomics) * Interactive exploration of Tract-based spatial statistics (TBSS) results * Intra-voxel incoherent motion (IVIM) estimation * Synthetic data generation Additional system specific requirements: * Windows: If you have problems running the Windows application, please install the Microsoft Redistributable Packages for VS 2008: 32 bit or 64 bit * Linux: the Qt framework, version 4.6.2 or later Tested systems: Windows 7, Windows Vista; Ubuntu 12.04 and newer; OS X 10.6 (Snow Leopard), OS X 10.8 (Mountain Lion) The OS X 10.6 installer is compatible with OS X 10.7 (Lion) so there is no dedicated disk image build under 10.7. The MITK Diffusion application is based on the MITK research platform and the most of it is open-source. The available code is embedded into the source code of MITK as a module and can be accessed through the public git repository.

Proper citation: MITK Diffusion (RRID:SCR_006846) Copy   

•   Source: SciCrunch Registry