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http://jakarta.apache.org/tomcat

Apache Tomcat is an open source software implementation of the Java Servlet and JavaServer Pages technologies. The Java Servlet and JavaServer Pages specifications are developed under the Java Community Process. Apache Tomcat is developed in an open and participatory environment and released under the Apache License version 2. Apache Tomcat is intended to be a collaboration of the best-of-breed developers from around the world. We invite you to participate in this open development project. Apache Tomcat powers numerous large-scale, mission-critical web applications across a diverse range of industries and organizations. Some of these users and their stories are listed on the PoweredBy wiki page.

Proper citation: Apache Tomcat (RRID:SCR_008411) Copy   

•   Source: SciCrunch Registry

https://apps.childrenshospital.org/clinical/research/ingber/GEDI/samples.htm

A program that opens a new perspective to the analysis of microarray data (e.g., gene expression profiling). Unlike traditional gene clustering software, GEDI is primarily sample-oriented rather than gene-oriented. By treating each high-dimensional sample, such as one microarray experiment, as an object, it accentuates the genome-wide response of a tissue or a patient and treats it as an integrated biological entity. Hence, GEDI honors the new spirit of a system-level approach in biology. Yet, it also allows the researcher to quickly zoom-in from global patterns onto individual genes that exhibit interesting expression behavior and retrieve gene-specific information. Therefore, GEDI unites a novel holistic perspective with the traditional gene-centered approach in molecular biology. GEDI allows experimental biologists or clinicians with no bioinformatics background to efficiently and intuitively navigate through a large number of expression profiles, each with a memorizable face, and inspect, group and collect them, like managing a stack of baseball cards. DYNAMIC ANALYSIS: The unique strength of GEDI, for which GEDI was originally developed, is that it can display the results of parallel monitoring of multiple high-dimensional time courses, such as the comparison of expression profile time evolution in response to a series of drugs. GEDI creates animated graphics showing how 10,000s of genes change their expression over time in response to 100s of separately tested drugs. STATIC ANAYLSIS: The signature graphical output of GEDI, the GEDI-mosaics provide a unique, one-glance visual engram that gives each microarray or other high-dimensional dataset a face. A characteristic of GEDI''s analysis is that it does not prejudicate any particular structure in the data (such as clusters or hierarchical organization). Thus, it allows the researcher to use human pattern recognition to perform a global first-level analysis of the data. Sponsor. The project was supported by the Air Force Office of Scientific Research and the National Health Institutes. It is distributed for free academic use by the Childrens Hospital, Boston., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GEDI (RRID:SCR_008530) Copy   

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http://www.widetag.com/

Headquartered in Redwood City California, WideTag is a pioneer in architecting computing systems that integrate sensors, positioning devices and memory with social, Web 2.0-style services in applications that revolutionize business and push consumer technology.

Proper citation: Wide Tag (RRID:SCR_008566) Copy   

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http://www.biokin.com/dynafit/

Program DynaFit Analysis of (bio)chemical kinetics and equilibria Welcome to the DynaFit home page. Purpose Symbolic Notation Bibliographic Reference Numerical Methods Minimum System Requirements Purpose The main purpose of the program DynaFit is to perform nonlinear least-squares regression of chemical kinetic, enzyme kinetic, or ligand-receptor binding data. The experimental data can be either initial reaction velocities in dependence on the concentration of varied species (e.g., inhibitor concentration vs. velocity), or the reaction progress curves (e.g., time vs. absorbance). Symbolic Notation The main advantage in using the program DynaFit is in the ability to characterize the (bio)chemical reacting system in terms of symbolic, or stoichiometric, equations. For example, the ``slow, tight'''' inhibition of a dissociative dimeric enzyme is described by the following text: Monomer Monomer <==> Enzyme : k1 k2 Enzyme Inhibitor <==> Complex : k3 k4 Enzyme Substrate <==> ReactiveX : k5 k6 ReactiveX --> Product Enzyme : k7 k8 The names of chemical species (Monomer, Enzyme, etc.) are entirely arbitrary and can be freely chosen by the investigator. Bibliographic Reference If you publish any results obtained by using DYNAFIT, plase cite the following reference: Kuzmic, P. (1996) Anal. Biochem. 237, 260-273. Program DYNAFIT for the Analysis of Enzyme Kinetic Data: Application to HIV Proteinase ABSTRACT A computer program with the code name DYNAFIT was developed for fitting either the initial velocities, or the time-course of enzyme reactions, to an arbitrary molecular mechanism represented symbolically by a set of chemical equations. Seven numerical tests and five graphical tests are applied to judge the goodness of fit. Experimental data on the inhibition of the dissociative dimeric proteinase from HIV were used in four test examples. A set of initial velocities was analyzed to see if a tight-binding inhibitor could bind to the HIV proteinase monomer. Three different sets of progress curves were analyzed (i) to determine the kinetic properties of an irreversible inhibitor; (ii) to investigate the dissociation and denaturation mechanism for the protease dimer; and (iii) to investigate the inhibition mechanism for a transient inhibitor. See a MEDLINE abstract with related references concerning the kinetics of HIV-1 protease. Numerical Methods The nonlinear regression module uses the Levenberg-Marquardt algorithm [1]. The time-course of (bio)chemical reactions is computed by the numerical integration of simultaous first-order ordinary differential equations, using the Livermore Solver of ODe Systems (LSODE, [2]). The composition of complex mixtures at equilibrium (e.g., in the concentration jump experiment where a complex mixture is incubated prior to the addition of a reagent) is computed by solving simultaneous nonlinear algebraic equations, namely, the mass balance equations for the component species, by using the multidimensional Newton-Raphson method [3]. References G. A. F. Seber and C. J. Wild (1989) Nonlinear Regression, Wiley, New York, p. 624. A. C. Hindmarsh (1983) ODEPACK: a systematized collection of ODE solvers; in Scientific Computing, ed. R. S. Stepleman et al., North Holland, Amsterdam, pp. 55--64. E. Kreyszig (1993) Advanced Engineering Mathematics; 7th ed., John Wiley, New York, p. 929. Minimum System Requirements DynaFit for Windows Intel Pentium III or Celeron class 800 MHz or faster processor Microsoft Windows XP (SP1) or 2000 (SP2) 128 MB RAM 20 MB Hard Disk Space Ethernet Network Interface Card required for license activation(1) CD/DVD-ROM drive required for software installation(2) (1) The Network Interface Card is used to compute a unique Computer ID, tied to a particular DynaFit license. Essentially the Computer ID required for license activation is an encrypted Media Access Control (MAC address) associated with the given Network Card. (2) CD/DVD-ROM is not required if the software is being installed by using the downloadable installer file dynafit-install.zip. Sponsor. This work has been supported by the NIH, grant No. R43 AI52587-02 and the U.S. Department of Defense, U.S. Army Medical Research and Materials Command, Ft. Detrick, MD, administered by the Pacific Telehealth & Technology Hui, Honolulu, HI, contract No. V549P-6073.

Proper citation: Program DynaFit (RRID:SCR_008444) Copy   

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http://www.phru.nhs.uk/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Tools were developed by the Critical Appraisal Skills Programme (CASP) to help with the process of critically appraising articles of the following types of research. These are available and free to download for personal use.

Proper citation: Public Health Resources Unit (RRID:SCR_008564) Copy   

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http://lagan.stanford.edu

About the LAGAN Toolkit The LAGAN Tookit consists of four components: CHAOS CHAOS is a pairwise local aligner optimized for non-coding, and other poorly conserved regions of the genome. It uses both exact matching and degenerate seeds, and is able to find homology in the presence of gaps. LAGAN LAGAN is our highly parametrizable pairwise global alignment program. It takes local alignments generated by CHAOS as anchors, and limits the search area of the Needleman-Wunsch algorithm around these anchors; Multi-LAGAN Multi-LAGAN is a generalization of the pairwise algorithm to multiple sequence alignment. M-LAGAN performs progressive pairwise alignments, guided by a user-specified phylogenetic tree. Alignments are aligned to other alignments using the sum-of-pairs metric. Shuffle-LAGAN Shuffle-LAGAN is a novel glocal alignment algorithm that is able to find rearrangements (inversions, transpositions and some duplications) in a global alignment framework. It uses CHAOS local alignments to build a map of the rearrangements between the sequences, and LAGAN to align the regions of conserved synteny. The website uses scripts written by Alex Poliakov. The website was designed by Marina Sirota.

Proper citation: LAGAN (RRID:SCR_008558) Copy   

•   Source: SciCrunch Registry

http://safcsupplysolutions.com

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. A business division of Sigma-Aldrich Corporation, focusing on providing custom manufactured products and specialized services used in the industrial development and manufacturing, including processes, that bring new drugs and new electronic products to market., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SAFC (RRID:SCR_008554) Copy   

•   Source: SciCrunch Registry

http://rocr.bioinf.mpi-sb.mpg.de/

ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It features over 25 performance measures that can be freely combined to create two-dimensional performance curves. Standard methods for investigating trade-offs between specific performance measures are available within a uniform framework, including receiver operating characteristic (ROC) graphs, precision/recall plots, lift charts and cost curves. ROCR integrates tightly with R''s powerful graphics capabilities, thus allowing for highly adjustable plots. Being equipped with only three commands and reasonable default values for optional parameters, ROCR combines flexibility with ease of usage. Performance measures that ROCR knows: Accuracy, error rate, true positive rate, false positive rate, true negative rate, false negative rate, sensitivity, specificity, recall, positive predictive value, negative predictive value, precision, fallout, miss, phi correlation coefficient, Matthews correlation coefficient, mutual information, chi square statistic, odds ratio, lift value, precision/recall F measure, ROC convex hull, area under the ROC curve, precision/recall break-even point, calibration error, mean cross-entropy, root mean squared error, SAR measure, expected cost, explicit cost. ROCR features: ROC curves, precision/recall plots, lift charts, cost curves, custom curves by freely selecting one performance measure for the x axis and one for the y axis, handling of data from cross-validation or bootstrapping, curve averaging (vertically, horizontally, or by threshold), standard error bars, box plots, curves that are color-coded by cutoff, printing threshold values on the curve, tight integration with Rs plotting facilities (making it easy to adjust plots or to combine multiple plots), fully customizable, easy to use (only 3 commands). ROCR can be used under the terms of the GNU General Public License. Running within R, it is platform-independent.

Proper citation: Classifier Visualization in R (RRID:SCR_008551) Copy   

•   Source: SciCrunch Registry

http://cython.org/

Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. This makes Cython the ideal language for wrapping external C libraries, and for fast C modules that speed up the execution of Python code. Sponsor. Google and Enthought funded Dag Seljebotn to greatly improve Cython integration with NumPy. Kurt Smith and Danilo Freitas were funded through the Google Summer of Code program to work on improved Fortran and C support respectively.

Proper citation: Cython C-Extensions for Python (RRID:SCR_008466) Copy   

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http://www.broadinstitute.org/scientific-community/science/programs/cancer/ultrasome

An efficient methodology for detecting and delineating gains and losses of chromosomal material in DNA copy-number data.

Proper citation: Ultrasome (RRID:SCR_008465) Copy   

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http://www.sanger.ac.uk/cgi-bin/blast/submitblast/d_rerio

This Blast server offers searches against all D. rerio finished and unfinished clones in the Sanger sequencing pipeline. You can now also search the de novo assemblies generated from sequencing of one doubled haploid homozygous individual of each the AB and Tuebingen strain. Both fish were sequenced to ~40x coverage using Illumina GA sequencing technology and the sequences were assembled using Phusion2, resulting in a 1,33 Gb AB and a 1.48 Gb Tuebingen assembly. Due to the short reads and short inserts and no integration of physical or genetic map data, both assemblies are highly fragmented - with an N50 contig size of about 5kb. Mis-assembly errors may also be present in the contigs. Please note these assemblies are independent additions to the assemblies released by the zebrafish genome project and are intended to aid identification of polymorphisms between these two strains. Charity. Genome Research Limited is a charity registered in England with number 1021457

Proper citation: D. rerio Blast Server (RRID:SCR_008461) Copy   

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http://developer.yahoo.com/yui/

The YUI Library is a set of utilities and controls, written with JavaScript and CSS, for building richly interactive web applications using techniques such as DOM scripting, DHTML and AJAX. YUI is available under a BSD license and is free for all uses. YUI is proven, scalable, fast, and robust. Built by frontend engineers at Yahoo! and contributors from around the world, it''s an industrial-strength JavaScript library for professionals who love JavaScript.

Proper citation: Yahoo Developer Network (RRID:SCR_008594) Copy   

•   Source: SciCrunch Registry

http://www.ltp-program.com

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on Jan 16th 2025. WinLTP is a stimulation, data acquisition and on-line analysis electrophysiological software for studying Long-Term Potentiation (LTP), Long-term Depression (LTD), and related phenomena. WinLTP is multitasking and simultaneously runs 1) LTP stimulus/acquisition/analyzing sweeps with protocol scripting, and 2) continuous acquisition saving Axon Binary Files (abf). WinLTP runs on Windows PCI bus computers and uses National Instruments PCI M-Series boards and Axon Instruments'' Digidata 1320A and 1322A data acquisition boards. Other software that can use the M-Series boards includes Axograph Scientific''s AxoGraph X, WaveMetrics'' IGOR, National Instruments'' LabView, John Dempster''s Strathclyde Electrophysiology Suite (WinWCP and WinEDR), Silver lab''s Nclamp, and QUB data acquisition., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: WinLTP (RRID:SCR_008590) Copy   

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http://motif-x.med.harvard.edu

motif-x (short for motif extractor) is a software tool designed to extract overrepresented patterns from any sequence data set. The algorithm is an iterative strategy which builds successive motifs through comparison to a dynamic statistical background.

Proper citation: Motif Extractor (RRID:SCR_008628) Copy   

•   Source: SciCrunch Registry

http://www.de-idata.com

A commercial organization that suppplies software which creates separate HIPAA-compliant repositories of de-identified patient records and reports. This software allows clinicians, researchers, and administrative leadership to safely access, search, share, and analyze de-identified patient-level data. DE-ID can be acquired as stand-alone tool or integrated with data networks or clinical information systems.

Proper citation: DE-ID Data Corp (RRID:SCR_008668) Copy   

•   Source: SciCrunch Registry

http://www.oracle.com/us/sun/index.htm

Oracle''s complete, open, and integrated product strategy provides flexibility and choice to our customers across their IT infrastructure. Now, with Sun server, storage, operating-system, and virtualization technology, Oracle is the only vendor able to offer a complete technology stack in which every layer is integrated to work together as a single system. Oracle''s open architecture and multiple operating-system options gives our customers unmatched benefits, including excellent system availability, scalability, energy efficiency, powerful performance, and low total cost of ownership Starting more than 30 years ago with Oracle''s innovative relational database, the Oracle stack today includes Oracle Enterprise Linux, Oracle VM, Oracle Fusion Middleware, and the largest and most complete set of industry and business applications software on the market. The addition of Sun storage and systems technology makes the Oracle stack complete. Oracle integrates every layer of the IT stack to deliver compelling value, based on high system availability and security, stunning performance, and low TCO. Only Oracle can offer this stack advantage to its customers through deep and seamless integration between the tiers that our competitors cannot match.

Proper citation: SUN Interface Engine (RRID:SCR_008659) Copy   

•   Source: SciCrunch Registry

http://pga.mgh.harvard.edu/oligopicker/

Software to help selecting up to five oligo probes for each of the DNA sequences you provided for microarray spotting.

Proper citation: OligoPicker (RRID:SCR_008720) Copy   

•   Source: SciCrunch Registry

http://www.opentox.org/dev/apis/api-1.1/structure

Tools for the integration of data from various sources (public and confidential), for the generation and validation of computer models for toxic effects, libraries for the development and seamless integration of new algorithms, and scientifically sound validation routines. The goal of OpenTox is to develop an interoperable predictive toxicology framework which may be used as an enabling platform for the creation of predictive toxicology applications. OpenTox is relevent for users from a variety of research areas: Toxicological and chemical experts (e.g. risk assessors, drug designers, researchers) computer model developers and algorithm developers non specialists requiring access to Predictive Toxicology models and data OpenTox applications can combine multiple web services providing users access to distributed toxicological resources including data, computer models, validation and reporting. Applications are based on use cases that satisfy user needs in predictive toxicology. OpenTox was initiated as a collaborative project involving a combination of different enterprise, university and government research groups to design and build the initial OpenTox framework. Additionally numerous organizations with industry, regulatory or expert interests are active in providing guidance and direction. The goal is to expand OpenTox as a community project enabling additional expert and user participants to be involved in developments in as timely a manner as possible. To this end, our mission is to carry out developments in an open and transparent manner from the early days of the project, and to open up discussions and development to the global community at large, who may either participate in developments or provide user perspectives. Cooperation on data standards, data integration, ontologies, integration of algorithm predictions from different methods, and testing and validation all have significant collaboration opportunities and benefits for the community. OpenTox is working to meet the requirements of the REACH legislation using alternative testing methods to contribute to the reduction of animal experiments for toxicity testing. Relevant international authorities (e.g., ECB, ECVAM, US EPA, US FDA) and industry organizations participate actively in the advisory board of the OpenTox project and provide input for the continuing development of requirement definitions and standards for data, knowledge and model exchange. OpenTox actively supports the development and validation of in silico models and algorithms by improving the interoperability between individual systems (common standards for data and model exchange), increasing the reproducibility of in silico models (by providing a quality source of structures, toxicity data and algorithms) and by providing scientifically sound and easy-to-use validation routines. OpenTox is committed to the support and integration of alternative testing methods using in vitro assay approaches, systems biology, stem cell technology, and the mining and analysis of human epidemiological data. Hence the framework design must take into account extensibility to satisfy a broad range of scientific developments and use cases.

Proper citation: OpenTox Framework (RRID:SCR_008686) Copy   

•   Source: SciCrunch Registry

http://www.procure.ca/index.php

The main goal of PROCURE is to provide science and humanity with means to help prevent and cure prostate cancer a disease which this year alone will be diagnosed in an estimated 25,500 Canadian men and one which will, on average, take the lives of 85 men every week. PROCURE strives to redefine the boundaries of research and knowledge by: * Initiating an on-going dialogue with the public and healthcare community to provide needed information and support through accessible means such as: ** A comprehensive website in French and English ** Lectures and special events ** Free book on prostate cancer * Funding and structuring over time a bank of biological materials and data on men with prostate cancer as well as those at risk of developing the disease. Such a Biobank, as it is known, will accelerate breakthrough scientific discovery. Join our alliance today by informing yourself and loved ones. Encourage the other men you care about to have an examination. Make a contribution to our cause. Help us keep information on this site up-to-date. In doing so you will become part of the force against prostate cancer!

Proper citation: PROCURE (RRID:SCR_008722) Copy   

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http://dc.crs4.it/projects/biodoop

A suite of parallel bioinformatics applications based upon a popular open-source Java implementation of MapReduce, Hadoop.

Proper citation: Biodoop (RRID:SCR_008711) Copy   

•   Source: SciCrunch Registry