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http://bmsr.usc.edu/software/lysis/

Interactive software of a set of modular programs (each performing a specific task) that provide an integrated computing environment for data analysis and system modeling. Unique capabilities of LYSIS include input-output nonlinear system modeling and the novel methodology of Principal Dynamic Modes (PDMs). LYSIS is currently available in two versions: one for LYSIS 7.1 Windows and one for LYSIS 7.2 Matlab. Early versions are also available for UNIX environments, distributed as source code that can be compiled for each UNIX implementation (e.g., Solaris, HPUX, Linux). Specific features of LYSIS that cannot be found in commercially available packages include the efficient kernel estimation using Laguerre expansions and the use of Principal Dynamic Modes (PDMs). These enable input-output modeling of dynamic nonlinear systems with relatively short data-records (even in the presence of considerable noise). System Requirements * Operating System ** Windows XP/Vista/7 ** Sun/Unix: Solaris 2.x

Proper citation: LYSIS (RRID:SCR_001385) Copy   

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http://www.neuroexplorer.com/

Data analysis software for neurophysiology with a multitude of features, including: * Import of native data files created by many popular data acquisition systems * All standard histogram and raster analyses * Shift predictors in crosscorrelograms and color markers in perievent rasters * Joint PSTH, burst analysis and many more analyses of timestamped data * Spectral analysis of spike and continuous data * 3D data view and animation * Fully customizable WYSIWYG graphics * Custom analysis and batch mode processing with internal scripting language * Direct data link to Matlab and Excel * Statistical tests via direct link to R-project

Proper citation: NeuroExplorer (RRID:SCR_001818) Copy   

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http://www.neuronland.net/NLMorphologyConverter/NLMorphologyConverter.html

NLMorphologyConverter is a simple command-line program for converting between the various neuron morphology data formats which are used to describe the three-dimensional physical branching structure of biological neurons. The aim is to provide coverage of all formats, old and new, in which data is available online, and/or which are supported by free and commercial software packages (e.g. software for neuron reconstruction, generation, simulation, visualization, and analysis of neuron morphology). Permission is granted for this software to be freely copied. Main Features Currently 21 different morphology file formats fully or partially supported. Automatic detection of input file format. Faithful reproduction of output file formatting. Many command line options for manipulating the imported data Intensively tested using over 10000 publicly available morphology data files. Sponsors. This software is supported by NeuronLand.

Proper citation: Neuronland: NLMorphologyConverter (RRID:SCR_001817) Copy   

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https://imagej.net/

Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.

Proper citation: ImageJ (RRID:SCR_003070) Copy   

•   Source: SciCrunch Registry

http://www.type2diabetesgenetics.org/

Portal and database of DNA sequence, functional and epigenomic information, and clinical data from studies on type 2 diabetes and analytic tools to analyze these data. .Provides data and tools to promote understanding and treatment of type 2 diabetes and its complications. Used for identifying genetic biomarkers correlated to Type 2 diabetes and development of novel drugs for this disease.

Proper citation: Accelerating Medicines Partnership Type 2 Diabetes Knowledge Portal (AMP-T2D) (RRID:SCR_003743) Copy   

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http://www.uib.no/en/cbu

An inter-department center that conducts bioinformatics research and expands the interface between bioinformatics and experimental biological and biomedical research. The unit is closely associated with the the Bioinformatics group at the Department of Informatics (II) and has tight links with the Sars Centre for Marine Molecular biology (SARS) and the Department of Molecular Biology (MBI). Six research groups are currently associated with CBU with projects that include sequence and structure analysis, molecular evolution, genome annotation and genomics data analysis. CBU also provides services and contributes to bioinformatics education primarily through training courses.

Proper citation: University of Bergen Computational Biology Unit (RRID:SCR_002970) Copy   

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http://www.moleculardevices.com/Products/Software/Meta-Imaging-Series/MetaMorph.html

Software tool for automated microscope acquisition, device control, and image analysis. Used for integrating dissimilar fluorescent microscope hardware and peripherals into a single custom workstation, while providing all the tools needed to perform analysis of acquired images. Offers user friendly application modules for analysis such as cell signaling, cell counting, and protein expression.

Proper citation: MetaMorph Microscopy Automation and Image Analysis Software (RRID:SCR_002368) Copy   

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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   

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http://www.oeb.harvard.edu/faculty/hartl/old_site/lab/publications/GeneMerge.html

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Web-based and standalone application that returns a wide range of functional genomic data for a given set of study genes and provides rank scores for over-representation of particular functions or categories in the data. It uses the hypergeometric test statistic which returns statistically correct results for samples of all sizes and is the #2 fastest GO tool available (Khatri and Draghici, 2005). GeneMerge can be used with any discrete, locus-based annotation data, including, literature references, genetic interactions, mutant phenotypes as well as traditional Gene Ontology queries. GeneMerge is particularly useful for the analysis of microarray data and other large biological datasets. The big advantage of GeneMerge over other similar programs is that you are not limited to analyzing your data from the perspective of a pre-packaged set of gene-association data. You can download or create gene-association files to analyze your data from an unlimited number of perspectives. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMerge (RRID:SCR_005744) Copy   

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https://www.synapse.org/

A cloud-based collaborative platform which co-locates data, code, and computing resources for analyzing genome-scale data and seamlessly integrates these services allowing scientists to share and analyze data together. Synapse consists of a web portal integrated with the R/Bioconductor statistical package and will be integrated with additional tools. The web portal is organized around the concept of a Project which is an environment where you can interact, share data, and analysis methods with a specific group of users or broadly across open collaborations. Projects provide an organizational structure to interact with data, code and analyses, and to track data provenance. A project can be created by anyone with a Synapse account and can be shared among all Synapse users or restricted to a specific team. Public data projects include the Synapse Commons Repository (SCR) (syn150935) and the metaGenomics project (syn275039). The SCR provides access to raw data and phenotypic information for publicly available genomic data sets, such as GEO and TCGA. The metaGenomics project provides standardized preprocessed data and precomputed analysis of the public SCR data.

Proper citation: Synapse (RRID:SCR_006307) Copy   

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http://pepr.cnmcresearch.org/

An experiment in web-database access to large multi-dimensional data sets using a standardized experimental platform to determine if the larger scientific community can be given simple, intuitive, and user-friendly web-based access to large microarray data sets. All data in PEPR is also available via NCBI GEO. The structure and goals of PEPR differ from other mRNA expression profiling databases in a number of important ways. * The experimental platform in PEPR is standardized, and is an Affymetrix - only database. All microarrays available in the PEPR web database should ascribe to quality control and standard operating procedures. A recent publication has described the QC/SOP criteria utilized in PEPR profiles ( The Tumor Analysis Best Practices Working Group 2004 ). * PEPR permits gene-based queries of large Affymetrix array data sets without any specialized software. For example, a number of large time series projects are available within PEPR, containing 40-60 microarrays, yet these can be simply queried via a dynamic web interface with no prior knowledge of microarray data analysis. * Projects in PEPR originate from scientists world-wide, but all data has been generated by the Research Center for Genetic Medicine, Children''''s National Medical Center, Washington DC. Future developments of PEPR will allow remote entry of Affymetrix data ascribing to the same QC/SOP protocols. They have previously described an initial implementation of PEPR, and a dynamic web-queried time series graphical interface ( Chen et al. 2004 ). A publication showing the utility of PEPR for pharmacodynamic data has recently been published ( Almon et al. 2003 ).

Proper citation: Public Expression Profiling Resource (RRID:SCR_007274) Copy   

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http://pbil.univ-lyon1.fr/acuts/ACUTS.html

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on August 12, 2014. Database that identifies new regulatory elements in untranslated regions of protein-coding genes (5 prime flanks, 5 prime UTRs, introns, 3 prime UTRs and 3 prime flanks). The analyses is focused on genes from metazoan species (essentially vertebrates, insects and nematodes). Information on highly conserved regions (sequences, alignments, annotations, bibliographic references) are compiled. Currently 176 out of 326 detected highly conserved regions (HCRs) have been analyzed and incorporated in the database. You can also access the list of annotated conserved elements and the list of conserved elements that remain to be processed. Their approach is based on comparative sequence analysis, for the identification of phylogenetic footprints.

Proper citation: Ancient conserved untranslated sequences (RRID:SCR_008130) Copy   

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http://bioinfo-out.curie.fr/ittaca/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on 6/12/25. ITTACA is a database created for Integrated Tumor Transcriptome Array and Clinical data Analysis. ITTACA centralizes public datasets containing both gene expression and clinical data and currently focuses on the types of cancer that are of particular interest to the Institut Curie: breast carcinoma, bladder carcinoma, and uveal melanoma. ITTACA is developed by the Institut Curie Bioinformatics group and the Molecular Oncology group of UMR144 CNRS/Institut Curie. A web interface allows users to carry out different class comparison analyses, including comparison of expression distribution profiles, tests for differential expression, patient survival analyses, and users can define their own patient groups according to clinical data or gene expression levels. The different functionalities implemented in ITTACA are: - To test if one or more gene, of your choice, is differentially expressed between two groups of samples exhibiting distinct phenotypes (Student and Wilcoxon tests). - The detection of genes differentially expressed (Significance Analysis of Microarrays) between two groups of samples. - The creation of histograms which represent the expression level according to a clinical parameter for each sample. - The computation of Kaplan Meier survival curves for each group. ITTACA has been developed to be a useful tool for comparing personal results to the existing results in the field of transcriptome studies with microarrays.

Proper citation: Integrated Tumor Transcriptome Array and Clinical data Analysis (RRID:SCR_008182) Copy   

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http://www.bh4.org/BH4DatabasesBiodef.asp

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. The BIODEF database have tabulated the most common clinical and laboratory data related to hyperphenylalaninaemia and tetrahydrobiopterin deficiencies. Additionally, there are data regarding treatment, outcome, and DNA analysis. Approximately 2% of newborns with hyperphenylalaninaemia are deficient in tetrahydrobiopterin. Selective screening must be performed in all instances where hyperphenylalaninaemia is detected by neonatal screening. In the last 20 years, 308 patients with tetrahydrobiopterin deficiencies have been recognized as a result of screening carried out, worldwide, in Departments of Paediatrics. Of these 308 patients, 181 suffered from 6-pyruvoyltetrahydropterin synthase deficiency, 92 from dihydropteridine reductase deficiency, 13 from pterin-4a-carbinolamine dehydratase deficiency, 12 from GTP cyclohydrolase I deficiency, and 10 are still unclassified. The BIODEF database have tabulated the most common clinical and laboratory data related to hyperphenylalaninaemia and tetrahydrobiopterin deficiencies. Additionally, there are data regarding treatment, outcome, and DNA analysis. Preliminary evaluation reveals that the degree of hyperphenylalaninaemia can vary from normal to 2500 mumol/L. Analyses of pterins in urine and measurement of dihydropteridine reductase activity from Guthrie cards are absolutely essential tests for accurate diagnosis. There is a regional (demographic) variation in the frequency of tetrahydrobiopterin deficiencies indicating the highest incidence in Saudi Arabia, probably a consequence of the high consanguinity rate.

Proper citation: International Database of Tetrahydrobiopterin Deficiencies (RRID:SCR_008171) Copy   

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http://report.nih.gov/

A database of federally funded biomedical research projects conducted at universities, hospitals, and other research institutions that provides a central point of access to reports, data, and analyses of NIH research. The RePORTER has replaced the CRISP database. The database, maintained by the Office of Extramural Research at the National Institutes of Health, includes projects funded by the National Institutes of Health (NIH), Substance Abuse and Mental Health Services (SAMHSA), Health Resources and Services Administration (HRSA), Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDCP), Agency for Health Care Research and Quality (AHRQ), and Office of Assistant Secretary of Health (OASH).

Proper citation: National Institutes of Health Research Portfolio Online Reporting Tool (RRID:SCR_006874) Copy   

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http://www.nlm.nih.gov/pubs/factsheets/medline.html

MEDLINE (Medical Literature Analysis and Retrieval System Online) is the U.S. National Library of Medicine''s (NLM) premier bibliographic database that contains over 16 million references to journal articles in life sciences with a concentration on biomedicine. MEDLINE is the primary component of PubMed, part of the Entrez series of databases provided by NLM''s National Center for Biotechnology Information (NCBI). MEDLINE may also be searched via the NLM Gateway. Currently, citations from approximately 5,200 worldwide journals in 37 languages; 60 languages for older journals. Citations for MEDLINE are created by the NLM, international partners, and collaborating organizations. The subject scope of MEDLINE is biomedicine and health, broadly defined to encompass those areas of the life sciences, behavioral sciences, chemical sciences, and bioengineering needed by health professionals and others engaged in basic research and clinical care, public health, health policy development, or related educational activities. MEDLINE also covers life sciences vital to biomedical practitioners, researchers, and educators, including aspects of biology, environmental science, marine biology, plant and animal science as well as biophysics and chemistry. Sponsors: Services/products providing access to MEDLINE data are also developed and made available by organizations that lease the database from NLM.

Proper citation: National Library of Health: Medical Literature Analysis and Retrieval System Online Fact Sheet (RRID:SCR_006994) Copy   

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http://www.nitrc.org/projects/jhucis_pedatlas/

Anatomical atlases constructed by Computational Anatomy of Johns Hopkins University for analysis of shape vectors. The atlases were generated from segmented hippocampal and amygdala structures in acquired populations of children, adolescents and young adults in neuroimaging studies of major depression disorder (MDD) at Washington University at St Louis.

Proper citation: Atlases of amygdala and hippocampus for pediatric populations (RRID:SCR_014085) Copy   

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http://hb.flatironinstitute.org/

Formerly known as GIANT (Genome-scale Integrated Analysis of gene Networks in Tissues), HumanBase applies machine learning algorithms to learn biological associations from massive genomic data collections. These integrative analyses reach beyond existing "biological knowledge" represented in the literature to identify novel, data-driven associations.

Proper citation: HumanBase (RRID:SCR_016145) Copy   

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https://github.com/stamatak/ExaML

Source code for large-scale phylogenetic analyses on whole-transcriptome and whole-genome alignments using supercomputers.

Proper citation: Examl (RRID:SCR_016087) Copy   

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http://www.nitrc.org/projects/reliability/

Data collected from subjects scanned 3 times (V1, V2, V3), with V1 and V2 on a scanner, V3 on another scanner in another site. Resting state blood oxygenation level dependent functional MRI (BOLD fMRI), pseudo continuous arterial spin labeling (pCASL), and high resolution 3D T1 imaging were performed under eyes open (EO) and eyes closed (EC) conditions.

Proper citation: Intra- and inter-scanner reliability of RS-fMRI BOLD and ASL with eyes closed vs. eyes open (RRID:SCR_016935) Copy   

•   Source: SciCrunch Registry