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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://ompc.juricap.com

OMPC aims to enable reuse of the huge open and free code base of MATLAB on a free and faster growing Python platform. Running Python and MATLAB in a single interpreter avoids issues with running two separate applications. Python adds general purpose programming libraries to the convenient syntax of the language of technical computing. OMPC is not an interpreter, it lets Python to do the work. This means that if Python gets faster OMPC gets faster too. OMPC translates the m-files preserving the structure of the original programs as much as possible. Although OMPC comes with a library that emulates the features of numerical array of MATLAB there is nothing that will stop you from running the translated code the way you like it. This means that you could run the OMPC generated code on IronPython, Jython, PyPy or whatever else if you write your own numerical class. Sponsors: This resource is supported by RIKEN Brain Science Institute.

Proper citation: An Open-Source MATLAB-to-Python Compiler (RRID:SCR_008409) Copy   

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http://faculty.washington.edu/chudler/ehc.html

This web site focuses on neuroscience, the study of the nervous system. Links on this page are limited to those Dr. Chundler finds to be the most interesting and useful.

Proper citation: Eric H. Chundlers Links (RRID:SCR_008328) Copy   

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http://www.uni-mannheim.de/fakul/psycho/irtel/cvd.html

This page leads you to some screen shots from the Color Vision Demonstrations program CVD for IBM PCs and compatibles as described in this reference: Irtel, H. (1992). Color-vision demonstrations on an IBM PC/AT with VGA. Behavior Research Methods, Instruments, & Computers, 24, 88-89. Note that in order to display these images correctly you need a true color display with 8 bits resolution per color channel.

Proper citation: Color Vision Demonstrations (RRID:SCR_008327) Copy   

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http://www.brl.ntt.co.jp/cs/human/index.html

This site provides information about the NTT Human and Information Science Laboratory. Technologies that enable users to get along well with information and technologies that can handle information properly on computers and networks are the keys to secure and high-quality information distribution services in a network society. In realizing those technologies, a comprehensive understanding of how human beings, the creators and the recipients of information, process information and novel principles for handling information are indispensable. From this viewpoint, the NTT Human and Information Science Laboratory has been pursuing scientific research in two areas: Sensory and Emotion Research, and Sensory and Motor Research. Sponsors: This resource is supported by NTT Communication Science Laboratories.

Proper citation: Human and Information Science Laboratory (RRID:SCR_008329) Copy   

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http://cgems.cancer.gov

The project began as a pilot study to identify inherited genetic susceptibility to prostate and breast cancer. CGEMS has developed into a robust research program involving genome-wide association studies (GWASs) for a number of cancers to identify common genetic variants that affect a person''s risk of developing cancer. In collaboration with extramural scientists, NCI''s Division of Cancer Epidemiology and Genetics (DCEG) has carried out genome-wide scans for breast, prostate, pancreatic, and lung cancers, while a GWAS of bladder cancer is currently underway. By making the data available to both intramural and extramural research scientists, as well as those in the private sector through rapid posting, NIH can leverage its resources to ensure that the dramatic advances in genomics are incorporated into rigorous population-based studies. Ultimately, findings from these studies may yield new preventive, diagnostic, and therapeutic interventions for cancer. Sponsors: This resource is supported by the U.S. National Institues Of Health.

Proper citation: CGEMS (RRID:SCR_008445) 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.wheaton.com

Wheaton Industries Inc. is a leading marketer, manufacturer and re-packager of containers, laboratory ware, instrumentation and associated products and services sold principally to customers in the general laboratory, life sciences, and diagnostics and reagent / chemicals packaging markets. Our products and services are marketed and sold globally through two divisions. The laboratory research products are sold through Wheaton Science Products, and the packaging products are sold through Wheaton Science Packaging.

Proper citation: Wheaton Industry Inc (RRID:SCR_008565) Copy   

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http://www.uow.edu.au/

Public research university in New South Wales, Australia which offers degree programs across a wide spectrum of disciplines, as well as providing research facilities to scientists

Proper citation: University of Wollongong; New South Wales; Australia (RRID:SCR_008322) 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://www.randomizer.org

This site is designed for researchers and students who want a quick way to generate random numbers or assign participants to experimental conditions. Research Randomizer can be used in a wide variety of situations, including psychology experiments, medical trials, and survey research. The program uses a JavaScript random number generator to produce customized sets of random numbers. Since its release in 1997, Research Randomizer has been used to generate number sets over 10.7 million times. This service is part of Social Psychology Network and is fast, free, and runs with any recent web browser as long as JavaScript isn''t disabled. Research Randomizer is a free service offered to students and researchers interested in conducting random assignment and random sampling. By using this service, you agree to abide by the SPN User Policy and to hold Research Randomizer and its staff harmless in the event that you experience a problem with the program or its results. Although every effort has been made to develop a useful means of generating random numbers, Research Randomizer and its staff do not guarantee the quality or randomness of numbers generated. Any use to which these numbers are put remains the sole responsibility of the user who generated them. What are the system requirements needed to run Research Randomizer? This program works best with Firefox and other recent web browsers. If you''re using a browser that came with America Online, or older browsers made prior to 2003, you may experience some difficulties with Research Randomizer. You may also not be able to use Research Randomizer with some limited-function browsers that do not fully support JavaScript, such as the Opera broswer used on certain game consoles. We would suggest that you update to a fairly recent, fully- functional stand-alone browser. How do I know what browser I am using? The easiest way to find this out is to click Help on the pulldown menu at the top of the screen. One of the options should be About Mozilla Firefox, About Internet Explorer, About Netscape, or something similar. Selecting this option will open a window that displays the name, version number, and copyright date of your browser. How does Research Randomizer generate its numbers? Research Randomizer uses the Math.random method within the JavaScript programming language to generate its random numbers for all modern web browsers. If you are using an older version of Microsoft Internet Explorer or Netscape Navigator (that is prior to version 4.0 of either), Research Randomizer uses an adaptation of the Central Randomizer by Paul Houle. Note that Research Randomizer no longer supports much-older browsers by other vendors (e.g., Mosaic). Who designed Research Randomizer? The original idea and programming for Research Randomizer came from Geoffrey C. Urbaniak in 1997. Research Randomizer was then jointly developed with Scott Plous, webmaster of Social Psychology Network, and online tutorials were added to the main program. In 1999 the site was redesigned with the assistance of Mike Lestik, in 2003 Mike Lestik added the download function, and in 2007 Mike Lestik and Scott Plous redesigned the site and added new content.

Proper citation: Research Randomizer (RRID:SCR_008563) Copy   

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http://www.ariad.com/

Cambridge, Massachusetts-based biotechnology company focused on cancer. Focus areas are blood cancers and solid tumors. Compounds: ponatinib, AP26113, ridaforolimus and AP1903., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ARIAD (RRID:SCR_008559) Copy   

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http://www.cns.caltech.edu/

The Computation and Neural Systems degree program is organized jointly by the Division of Biology, the Division of Engineering and Applied Science, and the Division of Physics, Mathematics and Astronomy. It is the program''s objective to provide a broad knowledge of this inherently multidisciplinary field, while at the same time requiring an appropriate depth of knowledge in the particular field of the thesis research. For example, a student working on cooperative circuits for early visual processing will also develop an in-depth knowledge of the anatomy and electrophysiology of early visual areas and a knowledge of visual psychophysics. A student working on olfactory cortex electrophysiology and its simulation would include the study of concurrent processing and the ethology of olfaction, and the relevant knowledge of dynamical and collective systems. A student working on the theory of complex systems could study collective and statistical properties of physics as well as the anatomical and algorithmic structure of biological and applied networks. Sponsors: The computational and neural systems is funded by the California Institute of Technology.

Proper citation: Computational and Neural Systems (RRID:SCR_008316) 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   

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http://www.strout.net/conical/

CONICAL is a C++ class library for building simulations common in computational neuroscience. Currently its focus is on compartmental modeling, with capabilities similar to GENESIS and NEURON. Future classes may support reaction-diffusion kinetics and more. A key feature of CONICAL is its cross-platform compatibility; it has been fully co-developed and tested under Unix, DOS, and Mac OS. Any C++ compiler which adheres to the emerging ANSI standard should be able to compile the CONICAL classes without modification. It is intended to encourage the rapid development of simulator software, especially on non-Unix systems where such software is sorely lacking. The present focus of the CONICAL library of C++ classes is compartmental modeling. A model neuron is built out of compartments, usually with a cylindrical shape. When small enough, these open-ended cylinders can approximate nearly any geometry, just as the stack of cylinders approximates a cone in the logo above. While any compartment has passive electrical properties (like a simple resistor-capacitor circuit), more interesting properties require the use of active ion channels whose conductance varies as a function of the time or membrane voltage. A standard Hodgkin-Huxley ion channel is included as one of the built-in CONICAL object types. Most of the voltage-gated ion channels in the literature can be directly implemented merely by setting the parameters of this class. For extensibility, this class is derived from several layers of more general classes. Connections between neurons can be implemented in several ways. For a gap junction (i.e., simple electrical connection), a passive current (or pair of currents, one in each direction) can be used. Synapses are more complex objects, but used in a similar fashion. The Alpha-function synapse is a very popular model of synaptic transmission, and is a basic CONICAL class. More complex (and realistic) synapses can be built using the Markov-model synapse. (A Markov model can be used on its own for other purposes as well.) In addition to classes directly related to neural modeling, CONICAL contains several other useful object types. These include a current injector, and a column-oriented output stream for storing data in table form.

Proper citation: Conical: The Computational Neuroscience Class Library (RRID:SCR_008318) Copy   

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http://www.lexisnexis.com

A commercial software provider designed for legal, risk management, corporate, government, law enforcement, accounting, and academic markets. Sponsors: This resource is Reed Elsevier, Inc. Keywords: Workflow, Professional, Legal, Risk, Management, Corporate, Government, Law, Enforcement, Accounting, Academic, Technology, Information,

Proper citation: LexisNexis (RRID:SCR_008433) Copy   

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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   

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http://www.ieee.org/portal/site/iportals?WT.mc_id=hplogo_upleft

IEEE is the worlds largest professional association advancing innovation and technological excellence for the benefit of humanity. IEEE and its members inspire a global community to innovate for a better tomorrow through its highly cited publications, conferences, technology standards, and professional and educational activities. IEEE is the trusted voice for engineering, computing and technology information around the globe. Through its global membership, IEEE is a leading authority on areas ranging from aerospace systems, computers and telecommunications to biomedical engineering, electric power and consumer electronics among others. Members rely on IEEE as a source of technical and professional information, resources and services. To foster an interest in the engineering profession, IEEE also serves student members in colleges and universities around the world. Other important constituencies include prospective members and organizations that purchase IEEE products and participate in conferences or other IEEE programs. IEEE has: -more than 375,000 members in more than 160 countries; 45 percent of whom are from outside the United States -more than 80,000 student members -329 sections in ten geographic regions worldwide -1,860 chapters that unite local members with similar technical interests -1,789 student branches in 80 countries -483 student branch chapters at colleges and universities -390 affinity groups -- IEEE Affinity Groups are non-technical sub-units of one or more Sections or a Council. The Affinity Group patent entities are Consultants'' Network, Graduates of the Last Decade (GOLD), Women in Engineering (WIE) and Life Members (LM) IEEE''s core purpose is to foster technological innovation and excellence for the benefit of humanity. It will be essential to the global technical community and to technical professionals everywhere, and be universally recognized for the contributions of technology and of technical professionals in improving global conditions., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: IEEE (RRID:SCR_008314) Copy   

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http://molbiocore.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 31, 2022. The UCSD CFAR/VMRF Molecular Biology Core (MBC) is a service core designed to facilitate and support HIV/AIDS research at the University of California San Diego (UCSD), the VA San Diego Healthcare System (VASDHCS), the Veterans Medical Research Foundation (VMRF), the UCSD Antiviral Research Center (AVRC), the Scripps Research Institute, and others in the San Diego HIV/AIDS research community. The MBC provides a variety of services, including DNA sequencing, viral DNA and RNA quantification, cDNA microarray analysis of herpesvirus expression, lentiviral vectors, RNAi design and synthesis, custom vector and plasmid design and construction, plasmids and other reagents of interest to HIV/AIDS research, shared access to computational biology software, and a variety of other services. The core is operated in association with the VMRF, the UCSD AIDS Research Institute (ARI), the VASDHCS, and the VA Research Center for AIDS and HIV Infection (RACHI). The VMRF/CFAR MBC is open to all UCSD, VA, and VMRF investigators as well as those from outside institutions. Keywords: Biology, Research, Medical, Molecular, DNA, Sequencing, Healthcare, RNA, DNA, cDNA, Microarray, Analysis, Herpesvirus, Expression, Lentiviral,

Proper citation: UCSD Center for AIDS Research Molecular Biology Core (RRID:SCR_008435) Copy   

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