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http://sourceforge.net/projects/bio-rainbow/

Software developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq.

Proper citation: Rainbow (RRID:SCR_002724) Copy   

•   Source: SciCrunch Registry

http://www.genmapp.org/

GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web. The main features underlying GenMAPP are: *Draw pathways with easy to use graphics tools *Color genes on MAPP files based on user-imported genomic data *Query data against MAPPs and the GeneOntology Enhanced features include the simultaneous view of multiple color sets, expanded species-specific gene databases and custom database options.

Proper citation: Gene Map Annotator and Pathway Profiler (RRID:SCR_005094) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/molbiolib/

A compact, portable, and extensively tested C++11 software framework and set of applications tailored to the demands of next-generation sequencing data and applicable to many other applications. It is designed to work with common file formats and data types used both in genomic analysis and general data analysis. A central relational-database-like Table class is a flexible and powerful object to intuitively represent and work with a wide variety of tabular datasets, ranging from alignment data to annotations. MolBioLib includes programs to perform a wide variety of analysis tasks such as computing read coverage, annotating genomic intervals, and novel peak calling with a wavelet algorithm. This package assumes fluency in both UNIX and C++.

Proper citation: MolBioLib (RRID:SCR_005372) Copy   

•   Source: SciCrunch Registry

http://primegens.org/

A Web-based Tool for High-throughput Primer and Probe Design. The program has its different utilities available on its web server. A standalone version is also available. Algorithms: * SSPD - Sequence Specific Primer Design: to design primers for each of the specific sequences given by the user in the query input file against any alternate potential hybridization with any of the sequences given in the database input file. * PSPD - Probe Specific Primer Design: to design primers it selects the gene-specific fragments (probes) to design primer pairs for their PCR amplification. * FSPD Fragment Specific Primer Design: primer design algorithm used when there is a very long query sequence for which multiple primers are required for its amplification. * Check Binding Specificity * Probe Design Only: Probe design algorithm could be used to find sequence-specific probes, which doesn''t show any blast hit against database. Such probe design has been used for targeted sequencing like agilent sure-select technology with next-generation sequencing.

Proper citation: PRIMEGENS (RRID:SCR_005474) Copy   

•   Source: SciCrunch Registry

http://bowtie-bio.sourceforge.net/index.shtml

Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.

Proper citation: Bowtie (RRID:SCR_005476) Copy   

•   Source: SciCrunch Registry

http://www.cma.mgh.harvard.edu/iatr/

A centrally available listing of all image analysis tools that are available to the neuroscience community in order to facilitate the development, identification, and sharing of tools. It is hoped that this helps the tool developers to get their tools to a larger user community and to reduce redundancy (or at least utilize tool redundancy to facilitate optimal tool design) in tool development. This also helps tool users in identification of the existing tools for specific problems as they arise. The registry is designed to be self-moderated. This means that all tool entries are owned by some responsible party who enters the tool information, and keeps it up to date via the Web.

Proper citation: Internet Analysis Tools Registry (RRID:SCR_005638) Copy   

•   Source: SciCrunch Registry

http://genemania.org/

Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMANIA (RRID:SCR_005709) Copy   

•   Source: SciCrunch Registry

http://estbioinfo.stat.ub.es/?page_id=2

The Statistics and Bioinformatics research group has as its main objectives the development of methods and tools to deal with problems appearing in the interface between Statistics and Bioinformatics. We started focusing in DNA microarrays but we are also interested in statistical methods for ''omics'' data integration and next generation sequencing (NGS). Our group collaborates with different research groups in the fields of biology and biomedicine, to whom it offers statistical support for problems which are specifically statistic in nature, such as experimental design or microarray data analysis, and also in more general aspects, such as modeling, analysis or data mining. After a first period of collaboration agreements with the Fundaci�� Vall d''Hebr��n Institut de Recerca we contributed to the creation of the Statistics and Bioinformatics Unit (UEB) which provides statistical and bioinformatical support to VHIR researchers.

Proper citation: University of Barcelona Statistics and Bioinformatics Research Group (RRID:SCR_005704) Copy   

•   Source: SciCrunch Registry

http://geneontology.svn.sourceforge.net/viewvc/geneontology/go-moose/

go-moose is intended as a replacement for the aging go-perl and go-db-perl Perl libraries. It is written using the object oriented Moose libraries. It can be used for performing a number of analyses on GO data, including the remapping of GO annotations to a selected subset of GO terms. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-moose (RRID:SCR_005666) Copy   

•   Source: SciCrunch Registry

http://www.gotaxexplorer.de/

GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products. This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOTaxExplorer (RRID:SCR_005720) Copy   

•   Source: SciCrunch Registry

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

Onto-Miner (OM) provides a single and convenient interface that allows the user to interrogate our databases regarding annotations of known genes. OM will return all known information about a given list of genes. Advantages of OM include the fact it allows queries with multiple genes and allows for scripting. This is unlike GenBank which uses a single gene navigation process. Scripted search of the Onto-Tools database for gene annotations. User account required. Platform: Online tool

Proper citation: Onto-Miner (RRID:SCR_005722) Copy   

•   Source: SciCrunch Registry

http://www.nanostring.com/products/nSolver

Data analysis software program that offers nCounter users the ability to QC, normalize, and analyze data without having to purchase additional software packages.

Proper citation: nSolver Analysis Software (RRID:SCR_003420) Copy   

•   Source: SciCrunch Registry

http://www.minituba.org

miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data. miniTUBA represents in a network view possible influences that occur between time varying variables in your dataset. For these networks of influence, miniTUBA predicts time courses of disease progression or response to therapies. minTUBA offers a probabilistic framework that is suitable for medical inference in datasets that are noisy. It conducts simulations and learning processes for predictive outcomes. The DBN analysis conducted by miniTUBA describes from variables that you specify how multiple measures at different time points in various variables influence each other. The DBN analysis then finds the probability of the model that best fits the data. A DBN analysis runs every combination of all the data; it examines a large space of possible relationships between variables, including linear, non-linear, and multi-state relationships; and it creates chains of causation, suggesting a sequence of events required to produce a particular outcome. Such chains of causation networks - are difficult to extract using other machine learning techniques. DBN then scores the resulting networks and ranks them in terms of how much structured information they contain compared to all possible models of the data. Models that fit well have higher scores. Output of a miniTUBA analysis provides the ten top-scoring networks of interacting influences that may be predictive of both disease progression and the impact of clinical interventions and probability tables for interpreting results. The DBN analysis that miniTUBA provides is especially good for biomedical experiments or clinical studies in which you collect data different time intervals. Applications of miniTUBA to biomedical problems include analyses of biomarkers and clinical datasets and other cases described on the miniTUBA website. To run a DBN with miniTUBA, you can set a number of parameters and constrain results by modifying structural priors (i.e. forcing or forbidding certain connections so that direction of influence reflects actual biological relationships). You can specify how to group variables into bins for analysis (called discretizing) and set the DBN execution time. You can also set and re-set the time lag to use in the analysis between the start of an event and the observation of its effect, and you can select to analyze only particular subsets of variables.

Proper citation: miniTUBA (RRID:SCR_003447) Copy   

•   Source: SciCrunch Registry

https://www.nanoporetech.com/

Commercial organization developing a disruptive, proprietary technology platform for the direct, electronic analysis of single molecules. The instruments GridION and MinION are adaptable for the analysis of DNA, RNA, proteins, small molecules and other types of molecule. Consequently, the platform has a broad range of potential applications, including scientific research, personalized medicine, crop science and security / defence.

Proper citation: Oxford Nanopore Technologies (RRID:SCR_003756) Copy   

•   Source: SciCrunch Registry

http://www.quretec.com/

Commercial organization that builds software for collection, management, and analysis of complex data, most typical in biomedical domain. The solutions are generic and can be used for multitude of uses and application domains.

Proper citation: Quretec (RRID:SCR_003826) Copy   

•   Source: SciCrunch Registry

http://www.althia.es/

A biomedical company in Spain focused on the development of new tools for diagnosis and personalized treatment of oncological diseases and precancerous. It has three areas of activity in permanent innovation: Assistance in Diagnosis / Prognosis in solid and hematological tumors, Translational Research covering the gap between basic and clinical research and advanced radiotherapy treatments based image-guided single dose (SD-IGRT). Their objectives are: * Provide an integrated tissue and tumor molecular phenotype analysis using the most advanced technologies in diagnosis, to guide the most appropriate treatment for each patient. * Discover and validate molecular patterns by molecular systems and platforms including pathology, to generate predictive algorithms through computational biology, evolution and determining the response of patients with a particular tumor profile. Althia has laboratories equipped with the most advanced equipment and technologies in Barcelona and Granada Genyo Center, with offices in Madrid.

Proper citation: Althia (RRID:SCR_003918) Copy   

•   Source: SciCrunch Registry

http://www.alacris.de/

Commercial organization that uses next generation sequencing technologies coupled with computational modeling of tumor and somatic tissues in order to identify individualized therapies for cancer patients. The company also uses these technologies to help pharmaceutical partners stratify patients for their clinical trials. Alacris has an exclusive worldwide commercial license for the computational modeling of tumors and somatic tissues using proprietary computational systems modeling technologies ModCell developed at the Max Planck Institute for Molecular Genetics (MPI-MG) in Berlin coupled with next generation sequencing and genotyping technology developed at Harvard Medical School in Boston. The company also is building up the first next generation sequencing center in Europe for clinical operations.

Proper citation: Alacris Theranostics (RRID:SCR_003953) Copy   

•   Source: SciCrunch Registry

http://psynova.com/

Commercial organization focused on the development and exploitation of novel biomarkers for psychiatric illnesses. They provide industrial and academic partners with comprehensive biomarker discovery services in commercial and collaborative projects. They operate in the field of psychiatric disorders and their products and services are designed to excel biomarker research. In 2010, Psynova Neurotech and its partner company Rules-Based-Medicine Inc (now MyriadRBM) conducted a beta launch of a blood test aiding in the diagnosis of schizophrenia (http://www.veripsych.com/). They are now refining the test and have shifted their focus to the development of new blood-based biomarker tests that aid in the diagnosis, prognosis and differential diagnosis of schizophrenia, bipolar disorder and major depression. They offer not only their pre-selceted Multiple Reaction Monitoring (MRM) and Multiplex Immunoassay products, but also custom build panels. If they are provided with a list of analyses to evaluate, they can produce an analytical panel according to individual needs utilizing either MRM or Multiplex Immunoassay technologies., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Psynova Neurotech (RRID:SCR_003959) Copy   

•   Source: SciCrunch Registry

http://www.genomedics.it/

A commercial company specialized in the field of clinical governance, research and clinical-epidemiological analysis and development of services and software applications for healthcare. Products and Services * Analysis and development software solutions, web, e-learning * Design and Implementation APP for Smartphone and Tablet (iOS, Android, Windows Phone) * Clinical Intelligence & Clinical Decision Support Systems (CDSS) * Data center services and Application Server Provider * Epidemiology, Surveillance and Health Promotion - Development of studies and epidemiological research

Proper citation: Genomedics (RRID:SCR_004103) Copy   

•   Source: SciCrunch Registry

http://www.sierrasensors.com/

In 2018 Bruker acquired Sierra Sensors GmbH, based in Hamburg, Germany. Sierra develops and manufactures innovative analytical biosensors based on Surface Plasmon Resonance (SPR) detection. Driven by patented technologies in the areas of SPR detection and microfluidic sample delivery, Sierra instruments are setting a new standard in high-throughput and high-performance label-free analysis.

Proper citation: Sierra Sensors (RRID:SCR_004062) Copy   

•   Source: SciCrunch Registry