Informatics  Map: Finding guide to terms in these glossaries  Site Map
Related glossaries include: 
Applications  Drug discovery & development  Genomics, Proteomics
Informatics Algorithms & data analysis   Bioinformatics   Information management & interpretation  In silico & molecular Modeling
Technologies: Combinatorial libraries & synthesis   Sequencing 
Biology DNA   Gene definitions  RNA  Protein Structures

ASP: Active Server Pages: A scripting technology for dynamic interactive webpages. 

agent: Definitions for autonomous agents, intelligent agents, user- agent.  WebRobots FAQ http://www.robotstxt.org/wc/faq.html#agent 

Amazon Web Services AWS: in late 2007 [Chris]  Dagdigian and his BioTeam colleagues realized that, without any managerial mandate, the whole group of consultants was independently experimenting with Amazon Web Services (AWS) to solve a customer problem. The cost of EC2 is ridiculously cheap, with almost infinite ways of controlling it. Bio-IT World Nov 18, 2009
http://www.bio-itworld.com/2009/11/18/c-word.html 

amorphous computing:  Amorphous computing is inspired by the recent astonishing developments in molecular biology and in microfabrication. Each of these is the basis of a kernel technology that makes it possible to build or grow huge numbers of almost- identical information- processing units, with integral actuators and sensors (e.g. MEMS), at almost no cost. Microelectronic components are so inexpensive that we can imagine mixing them into materials that are produced in bulk, such as paints, gels, and concrete. Such ``smart materials'' will be used in structural elements and in surface coatings, such as skins or paints. [Harold Abelson, Thomas F. Knight, Gerald Jay Sussman, and friends, Amorphous Computing Manifesto, MIT, 1996] http://www.swiss.ai.mit.edu/projects/amorphous/white-paper/amorph-new/amorph-new.html

Google = about 1,150 July 19, 2002; about 4,450 July 26, 2004

Amorphous Computing Homepage, Artificial Intelligence, MIT, US  http://www.swiss.ai.mit.edu/projects/amorphous/

"Amorphous computing" Communications of the ACM, May 2000  http://www.swiss.ai.mit.edu/projects/amorphous/cacm-2000.html

automation: Drug discovery & development

Google = about 3,720,000 Aug. 20, 2002; about 8,770,000 July 26, 2004

autonomic computing: An approach to self-managed computing systems with a minimum of human interference. The term derives from the body's autonomic nervous system, which controls key functions without conscious awareness or involvement. [IBM Corp, Autonomic Computing Glossary]  http://www.research.ibm.com/autonomic/glossary.html

BIRN Biomedical Informatics Research Network: http://www.nbirn.net/
A consortium of 12 universities and 16 research groups to foster large- scale biomedical science collaborations by utilizing emerging cyberinfrastructure (high speed networks, distributed high- performance computing and the necessary software and data integration capabilities).

Beowulf computing: Wikipedia http://en.wikipedia.org/wiki/Beowulf_(computing) 

Google = about 699 Aug. 20, 2002; about 3,770 July 26, 2004; about 9,160 June 11, 2007

biocomputing:  Biocomputing could be defined as the construction and use of computers which function like living organisms or contain biological components, so-called biocomputers (Kaminuma, 1991). Biocomputing could, however, also be defined as the use of computers in biological research and it is this definition which I am going to use in this essay. With this interpretation of biocomputing the complicated ethical questions connected with concepts like artificial life and intelligence are not dealt with.
Peter Hjelmström, Ethical issues in biocomputing http://www.techfak.uni-bielefeld.de/bcd/ForAll/Ethics/welcome.html 

Google = about 32,000 July 19, 2002; about 61,400 July 26, 2004, about 575,000 June 11, 2007

biological computing: Simson Garfinkel "Biological computing" Technology Review, May/ June 2000 http://www.technologyreview.com/articles/garfinkel0500.asp

Google = about 3,200 July 19, 2002; about 14,900 July 26, 2004

Related terms: biocomputing, DNA computing

bikeshed:  Why should I care? [metaphor] http://www.unixguide.net/freebsd/faq/16.19.shtml  Thanks to World Wide Words 

biomedical computing: (biomedical information science and technology): Includes database design, graphical interfaces, querying approaches, data retrieval, data visualization and manipulation, data integration through the development of integrated analytical tools, synthesis, and tools for electronic collaboration, as well as computational research including the development of structural, functional, integrative, and analytical models and simulations. Innovations in biomedical information science and technology: SBIR/ STTR Initiative, NIH program announcement, June 29, 2000 http://grants.nih.gov/grants/guide/pa-files/PA-00-118.html

Google = about 11,800 July 19, 2002; about 22,400 July 26, 2004

CORBA Common Object Request Broker Architecture: A set of core specifications proposed by the Object Management Group (OMG). CORBA is designed to be object- oriented.  

Common Object Request Broker Architecture, OMG's open, vendor- independent architecture and infrastructure that computer applications use to work together over networks. Using the standard protocol IIOP, a CORBA- based program from any vendor, on almost any computer, operating system, programming language, and network, can interoperate with a CORBA- based program from the same or another vendor, on almost any other computer, operating system, programming language, and network. [CORBA FAQ, OMG, 1997- 2002] http://www.omg.org/gettingstarted/corbafaq.htm

Google = about 1,430,000 Aug. 20, 2002

Related terms: interoperability, object- oriented 

captology: The study of computers as persuasive technologies. This includes the design, research, and analysis of interactive computing products created for the purpose of changing people's attitudes or behaviors.  Key Concepts: Computers as Persuasive Technologies, Stanford Univ. Persuasive Technologies Lab, US  http://captology.stanford.edu/

Google = 8,090 July 26, 2004 

Captology.org http://captology.stanford.edu/http://captology.stanford.edu/

cellular computing: Cell biology

Google = about 14,500 July 26, 2004; about 20,400 June 11, 2007

cloud computing: An increasing number of the top life science companies are considering a switch from the outright acquisition and customization of e-clinical technologies to establishing and accessing “clinical clouds.” Indeed, it may be the only sensible way to access needed software and information as they engage in more collaborations, alliances, and partnerships to weather the “perfect storm of unprecedented challenges” bearing down on their collective bottom line, says Paul Papas, the Americas life sciences leader for IBM Global Business Services. IBM’s Sunny Forecast for Clinical Cloud Computing, eCliniqua June 2009 http://www.bio-itworld.com/2009/06/01/ibm-clouds.html 

BioIT World report on cloud computing 2009 http://www.bio-itworld.com/BioIT_Article.aspx?id=95016   See also: Amazon Web Services AWS,  utility computing

computation: Has become an essential component of biological research. The great quantity and diversity of the data being generated by different technologies is daunting, and impossible to organize or oversee without computational assistance. In functional genomics, a great deal of effort has been devoted to developing community- based standards for reporting gene expression data to allow others to replicate experiments. The same will need to be done for proteomics to validate across the different technologies. Perhaps never before has a bioinformatics problem of this magnitude been approached. Without effective and integrated databases to store and retrieve these data and advanced computational methods such as pattern recognition and other machine learning approaches to analyze and interpret them, the full implications of these data will not be realized. Defining the Mandate of Proteomics in the Post- Genomics Era, Board on International Scientific Organizations, National Academy of Sciences, 2002 http://www.nap.edu/books/NI000479/html/R1.html

computational biology: Bioinformatics

Google = about 90,900 Aug. 20, 2002; about 331,000 July 26, 2004;a bout 1,430,000 May 7, 2007

computational genomics: In silico & molecular Modeling

computational linguistics: Information management & interpretation

computational pharmacology: Pharmacogenomics

computational therapeutics: Molecular Medicine

computational video:  The study and application of the processing of streamed video data. This field of research is emerging from the convergence of two technologies: digital cameras and high performance computing and high bandwidth networks. In addition, past and current research in machine vision has provided some practical solutions to some of the fundamental processing problems inherent in processing video.  Institute for Information Technology, National Research Council, Canada, Research Programs Computational Video http://iit-iti.nrc-cnrc.gc.ca/templates/itiiit/itiiit2.cfm?CFID=33974&CFTOKEN=93356...

Google = about 1,980 July 26, 2004; about 19,400 May 7, 2007

compute farm: Related terms: compute server farm, ranch, server farm. 

Google = about 2,850 Aug. 20, 2002; about 10,200 July 26, 2004

computer virus: Glossary of terms, McAfee,  100 + definitions, 2002 http://www.mcafee.com/anti-virus/virus_glossary.asp

computers: Narrower terms include high performance computers, supercomputers

computing: Related terms include ASP Active Server Pages, compute farm, informatics, MPP Massively Parallel Processing, parallel processing, petaflop, teraflop, server farm, supercomputer. 
Narrower terms: DCE Distributed Computing Environment, DNA computing, grid computing, high performance computing, molecular computing, molecular computing, quantum computing, soft computing, utility computing 

computing and biology: Frontiers at the Interface of Computing and Biology, National Academies of Science, US http://www7.nationalacademies.org/cstb/project_biology.html

data security:

data storage:

digital asset management: An IT-based practice for the systematic reuse and re- expression of pre- existing digital objects that, when successfully done, accelerates business processes and time to market deliverables.  Debra D'Agostino, Digital Asset Management; Making the most of what you've got. CIO Insight May 28, 2003 http://www.cioinsight.com/article2/0,3959,1110620,00.asp

DNA computers: Seeks to use biological molecules such as DNA and RNA to solve basic mathematical problems. Fundamentally, many of these experiments recapitulate natural evolutionary processes that take place in biology, especially during the early evolution of life and the creation of genes. Laura Landweber, "DNA Computing" Princeton Univ. Freshman Seminar, 1999. http://www.princeton.edu/~lfl/FRS.html

Google = about 3,690 Aug. 20, 2003; about 5,990 July 26, 2004; about 55,800 May 7, 2007

DNA computing: An interdisciplinary field that draws together molecular biology, chemistry, computer science and mathematics. There are currently several research disciplines driving towards the creation and use of DNA nanostructures for both biological and non-biological applications. These converging areas are:  The miniaturization of biosensors and biochips into the nanometer scale regime; The fabrication of nanoscale objects that can be placed in intracellular locations for monitoring and modifying cell function; The replacement of silicon devices with nanoscale molecular- based computational systems, and The application of biopolymers in the formation of novel nanostructured materials with unique optical and selective transport properties DNA Computing & Informatics at Surfaces, Univ. of Wisconsin- Madison, June 1-4 2003. http://analytical.chem.wisc.edu/DNA9/

Google = about 8,900 July 19, 2002; about 13,800 June 16, 2003; about 191,000 May 7, 2007

Related terms: molecular computing, quantum computing Or are these the same/overlapping? 

DTDs Document Type Definitions: The National Center for Biotechnology Information (NCBI) of the National Library of Medicine (NLM) created the Journal Archiving and Interchange Document Type Definition (DTD) with the intent of providing a common format in which publishers and archives can exchange journal content. http://dtd.nlm.nih.gov/

data mapping: Wikipedia http://en.wikipedia.org/wiki/Data_mapping 

Google = about 26,700 Aug. 20, 2002; about 55,000 July 26, 2004; about 208,000 Nov 27, 2006

discretization strategies: See under mesh interface

Distributed Computing Environment DCE: From the Open Software Foundation. (The Open Software Foundation is now called the Open Group.) DCE consists of multiple components which have been integrated to work closely together. ... DCE is called "middleware" or "enabling technology." It is not intended to exist alone, but instead should be bundled into a vendor's operating system offering, or integrated in by a third- party vendor. DCE's security and distributed filesystem, for example, can completely replace their current, non- network, analogs. DCE is not an application in itself, but is used to build custom applications or to support purchased applications. [Open Software Foundation Distributed Computing Environment FAQ, Oct. 1998 ] http://www.faqs.org/faqs/dce/faq/

Related terms: CORBA, OMG; Nanoscience & miniaturization  nanocomputer

EDC electronic data capture: Wikipedia http://en.wikipedia.org/wiki/Electronic_Data_Capture 

evolutionary computation: Algorithms & data analysis

Google = about 56,000 July 19, 2002

Narrower terms: Algorithms & data analysis  genetic algorithms, genetic programming 

FLOP: Floating point operations per second. A measure of how fast a computer is based on calculations per second. A floating point is a number representation consisting of a mantissa, an exponent, and an assumed radix. The number represented is M multiplied by R raised to the power of E (M*R^E) where R is the radix or base of the number system. (For example, 10 is the radix of the decimal system.) National Center for Supercomputing Applications, MetaComputer Glossary, Univ. of Illinois, Urbana- Champaign 1995 http://archive.ncsa.uiuc.edu/Cyberia/MetaComp/MetaGlossary.html

Related terms: petaflop, teraflop

free software:  http://en.wikipedia.org/wiki/Free_software 

Software in which the source code is by definition freely available to the general public for redistribution, modification, examination or any other conceivable purpose. Similar to "open- source software," except that "open- source" is a relatively recent term coined for marketing purposes by people who wanted to put a more "business- friendly" face on the concept. Free software, as an idea, is usually associated with Richard Stallman, founder of the Free Software Foundation.   [Andrew Leonard, The Free Software Project,  Free software glossary, Salon.com, 2000 http://dir.salon.com/story/tech/fsp/2000/03/05/glossary/ 

Google = about 2,160,000  Aug. 17, 2002; about 92,000,000 May 7, 2007

GUI Graphical User Interface: The two most useful GUI’s are the Query interface to the database and the Report/ Analysis interfaces … each interface should do only a handful of tasks. The most common mistake is to keep adding functionality to an interface rather than creating a new interface…The Query tools are just starting to emerge…The unmet need of querying data is in the area of joining internal and external data …The other emerging concept for the query tool is the need for relationships between the data. The most critical need is to have consistent terms used to describe the data. This is often a very difficult task to get scientists across a multi- site company to agree on one. The other complication is legacy data, either having the wrong terms or no terms at all. Frank Brown "Chemoinformatics: What is it and How does it Impact Drug Discovery" Annual Reports in Medicinal Chemistry 33: 375- 384, 1998

Related terms: Ontologies & taxonomies

geek: http://en.wikipedia.org/wiki/Geek  Compares with nerd but there are many nuances and variations.

genetic programming: Algorithms & data analysis

Google = about 53,100 July 19, 2002, about 882,000 May 7, 2007

genomic computing: A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a genetic algorithm to fit particular tasks and environments. The genome has three portions: one for specifying links and their initial weights, a second for specifying how a node updates its internal state, and a third for specifying how a node updates the weights on its links. Preliminary experiments demonstrate that genomic computing networks can use node internal state to solve POMDPs more complex than those solved previously using neural networks. Association for Computing Machinery, ACM Digital Library, Guide to Computing Literature http://portal.acm.org/citation.cfm?id=1143997.1144037&coll=&dl=&type=series&idx=1143997&part=Proce

Google = about 676 Aug. 29, 2003; about 567 May 7, 2007

grid computing: Wikipedia http://en.wikipedia.org/wiki/Grid_computing  
Grid computing glossary, Israel Association of Grid Technologies  http://www.grid.org.il/?CategoryID=365 

Google = about 201,000 July 19, 2002; about 19, 800,000 May 7, 2007

Narrower term: desktop grids; Related terms:  utility grids, Information management & interpretation semantic grid

high performance computing: Weboepedia definition http://www.webopedia.com/TERM/H/High_Performance_Computing.html

Google = about 374,000 July 19, 2002; about 15,700,000 May 7m 2007

Related terms: Distributed Computing Environment DCE, MPP Massively Parallel Processing, petaflop, supercomputers, teraflop

Human Computer Interface HCI:  http://usableweb.com/authors/perlmangary.html

information extraction: Information management  & interpretation

information technology: Information technology plays a key role in helping organizations achieve profitable results and keep competitive forces in check. With the completion of the draft sequence of the human genome and the push for protein data analysis, the life sciences industry is faced with the daunting task of creating computing infrastructures that support a high level of data interpretation. Never before has the need for significant computing power been so great.  Cambridge Healthtech Institute, IT and Informatics conference series 

Throughout society, the utility of IT applications tends to advance much more slowly than the underlying technologies. ... The effective implementation and use of IT are the result of a complex process that requires not only adoption of a technology but also changes in organizations and institutions. As part of this process, individuals and organizations actively adapt (and sometimes resist) the technologies. As a result, the effects of IT on society often take place more slowly than visionaries predict. Nevertheless, the effects—driven by the continual change in underlying technologies—are substantial over time. Science and Engineering Indicators 2002 : Significance of Information Technology: Conclusion,  National Science Foundation, 2002 http://www.nsf.gov/sbe/srs/seind02/c8/c8s4.htm

Google = about  2,970,000 July 19, 2002

information visualization, interoperability, knowledge management: Information management  & interpretation

Google = "knowledge management" about 826,000 July 19, 2002

interoperability: Information management & interpretation

LIMS Laboratory Information Management Systems: Drug discovery & development

LSR [Life Sciences Research] group:  Focused on  the use of CORBA for objects at all levels of software systems for life sciences research. CORBA is implementation language and  platform- independent, so specifications adopted by the LSR group can be implemented in the most appropriate language(s) on a variety of hardware and  operating systems. Part of OMG. http://www.omg.org/homepages/lsr/FAQ.html#LSR vs BW

legacy systems: Wikipedia http://en.wikipedia.org/wiki/Legacy_systems 

Google = about 256,000 July 19, 2002; about 1,100,000 May 4, 2005; about 1,250,000 May 7, 2007

Linux:  A free Unix- type operating system originally created by Linus Torvalds with the assistance of developers around the world. Developed under the GNU General Public License , the source code for Linux is freely available to everyone. Linux Home Page  http://www.linux.org/

Linux clusters: Network multiple processors together to form a unified and more powerful computing system, are becoming a major technology in the bioinformatics industry. ... dozens, if not hundreds of these processors or "nodes" [are used] for the explicit purpose of gene sequencing, proteomic research, or drug discovery and development. Joshua Harr, Linux NetworX, "Linux clusters - The New Workhorse of Gene Sequencing, Proteomics and Drug Development" Genome Link, Nov. 2001 http://www.healthtech.com/newsarticles/issue12_2.asp

A node within a Linux cluster is the basic unit of processing.

Google = about  14,700 July 19, 2002

MPP Massively Parallel Processing: 

Google = about 8,770 July 19, 2002

machine-readable: See under metadata

Google= about 303,000 July 19, 2002

machine-understandable:  http://iswc2006.semanticweb.org/items/doctoral_consortium_tao.pdf 

See also under metadata

Google= about 3,730 July 19, 2002; about 107,000 Nov 17, 2006

markup languages:  XML  eXtensible Markup Language; Bioengineering & Biomaterials BIOML Biopolymer Markup Language, MatML Materials Markup Language; Bioinformatics BSML Bioinformatic Sequence Markup Language; Cheminformatics CML Chemical Markup Language; Information management DAML DARPA Agent Markup Language, DAML + OIL; In silico & Molecular Modeling VRML Virtual Reality Modeling Language; Microarrays GEML Gene Expression Markup Language, MAGE-ML MicroArray and Gene Expression Markup Language, MAML Microarray Markup Language [no longer supported]

Google = about 55,700 Aug. 12, 2002

markup languages, standards core: Robin Cover, Core Standards for Markup Languages, 2002  http://xml.coverpages.org/coreStandards.html

mathML: Algorithms

memory-mapped data structures: In this approach [to data- level integration without semantic cleaning] subsets of data from various sources are collected, normalized, and integrated in memory for quick access. While this approach performs actual data integration and addresses the problem of  poor performance in the federated approach, it requires additional calls to traditional relational databases to integrate descriptive data. While data cleaning is being performed on some of the data sources, it is not being done across all sources or in the same place. This makes it difficult to quickly add new data sources. [Approaches to Integrating Biological Data, K. Griffiths, R. Resnick, NetGenics, Inc. Intelligent Systems in Molecular Biology, August 19- 23, 2000 La Jolla CA, US]  http://ismb2000.sdsc.edu/tutorials/griffiths.html

Google = about 33 July 19, 2002

mesh interface: There is a wide array of mesh and discretization strategies available to solve application problems and many times it is not clear a priori which is the best strategy for a particular simulation. See Fig 1. The only way to determine the proper choice is to experiment with a number of options. This is both time consuming and difficult because most mesh and discretization tools have very different programming interfaces. To enable this kind of experimentation, and as a first step toward interoperability, the TSTT team is developing a common software interface for its many mesh management infrastructures. A key aspect of our approach is that we do not enforce any particular data structure or implementation with our interfaces, only that certain questions about the mesh can be answered through calls to the interface. The challenges inherent in this type of effort include balancing performance of the interface with the flexibility needed to support a wide variety of mesh types. Further challenges arise when considering the support of many different scientific programming languages. Terascale Simulations Tools and Technologies Center [TSTT], Scientific Discovery Through Advanced Computing, 2003  http://www.osti.gov/scidac/updatesglimm1.html

metacomputer: A collection of computers held together by state- of- the- art technology and "balanced" so that, to the individual user, it looks and acts like a single computer. The constituent parts of the resulting "metacomputer" could be housed locally, or distributed between buildings, even continents. [MetaComputer HomePage, National Center for Supercomputing Applications, Univ. of Illinois Urbana- Champaign, US] http://archive.ncsa.uiuc.edu/Cyberia/MetaComp/MetaHome.html

Google = about 9,510 July 19, 2002

MetaComputer Glossary of Terms http://archive.ncsa.uiuc.edu/Cyberia/MetaComp/MetaGlossary.html

metadata: Information management & interpretation

middleware:  Wikipedia  http://en.wikipedia.org/wiki/Middleware

Google = about  584,000 July 19, 2002; about 13,300,000 June 11, 2007

Related term: DCE Distributed Computing Environment 

modularity:  Ensures that, for the particular task at hand, the data will be collected and stored in an appropriate manner - which differs greatly from one level of activity (simply gathering the raw data) to another (storing analyzed data) and from one type of high- throughput system to another. ... The best system is one that employs integration at those levels where it is an advantage but maintains enough modularity to ensure that (1) there are no major compromises regarding how any one type of data is handled and, (2) all the key elements in a researcher’s information system can be adjusted or updated independently.

Wikipedia http://en.wikipedia.org/wiki/Modularity 

Google = about  159,000 July 19, 2002; about 3,610,000 Nov 17, 2006

Related terms: integration, interoperability

molecular computers: Computers whose input, output and state transitions are carried out by biochemical interactions and reactions. MeSH 2003

Google = about 2,880 Aug. 20, 2003; about 38,000 Nov 17, 2006

Wikipedia http://en.wikipedia.org/wiki/Molecular_computer 

molecular computing: Ruzena Bajcsy, Assistant Director for Computer and Information Science and Engineering at the National Science Foundation, was lead off witness at a September 12 [2000] House Science Committee Hearing on "Beyond Silicon Computing: Quantum and Molecular Computing" ... is currently supporting a number of researchers who are exploring physical processes can be exploited as computing substrates - chemical, biomolecular, optical computing via photonics, and quantum systems... Chairman Nick Smith pressed the panel for their visions of where this research would take us in 20 or 30 years. Witnesses suggested applications for non- silicon based computing, including cryptography, pharmaceutical development, protein folding, and data storage and mining. Dr. Bajcsy suggested that very small computers would provide portable devises that would enhance and extend of our sensory capabilities - the vision of an eagle, the olfaction of a dog, or the hearing of a rabbit. [National Science Foundation, Hearing Summary: House Science Committee's Hearing on "Beyond Silicon Computing: Quantum and Molecular Computing" Sept. 12, 2000] http://www.nsf.gov/od/lpa/congress/106/hs_beyondsilicon.htm

Google = about 5,000 July 19, 2002; about 125,000 Nov 17, 2006

Related terms: DNA computing, quantum computing. Or are any of these the same?

Moore's Law: Gordon Moore made his famous observation in 1965, just four years after the first planar integrated circuit was discovered. The press called it "Moore's Law" and the name has stuck. In his original paper, Moore observed an exponential growth in the number of transistors per integrated circuit and predicted that this trend would continue. Through Intel's relentless technology advances, Moore's Law, the doubling of transistors every couple of years, has been maintained, and still holds true today. Intel expects that it will continue at least through the end of this decade. ["Moore's Law, Intel Research, 2002] http://www.intel.com/research/silicon/mooreslaw.htm

Wikipedia http://en.wikipedia.org/wiki/Moore's_law 

Google = about 46,800 July 19, 2002; about 697,000 Nov 17, 2006

munging: A common term in the programmer’s world. Many computing tasks require taking data from one computer system, manipulating it in some way, and passing it to another. Munging can mean manipulating raw data to achieve a final form. It can mean parsing or filtering data, or the many steps required for data recognition. Or it can be something as simple as converting hours worked plus pay rates into a salary cheque. This book shows you how to process data productively with Perl. It discusses general munging techniques and how to think about data munging problems. David Cross, Data Munging with Perl, Manning Publications Co., 2001 http://www.manning.com/cross/

Wikipedia http://en.wikipedia.org/wiki/Munging 

OASIS Organization for the Advancement of Structured Information Systems: A not- for- profit, global consortium that drives the development, convergence and adoption of e-business standards. http://www.oasis-open.org/who/

OASIS Glossary of terms http://www.oasis-open.org/glossary/index.php  50 + terms

OMG Object Management Group: Distributed object computing industry standards group founded in 1989. The OMG is moving forward in establishing CORBA as the "Middleware that's Everywhere" through its worldwide standard specifications: CORBA/IIOP, Object Services, Internet Facilities and Domain Interface specifications, UML and other specifications supporting Analysis and Design. http://www.omg.org/

Object- Oriented Modeling OOM: A method for designing software and databases that combines programs and data into self- contained packages called classes, and organizes these classes into a type/ subtype hierarchy. It is an excellent way to design software and databases that have to cope with a lot of picayune detail and many "exceptions to the rule," so long as the basic structure of the problem can be well- represented by a type/ subtype hierarchy, easily distributed, language- independent, and hardware- neutral. [CHI Bioinformatics report]  

Google = about 371,000 July 19, 2002 Object- Oriented Modelling = about 168,000

Object- Protocol Model (OPM): Developed initially by members of the Data Management Research and Development Group at Lawrence Berkeley National Laboratory ... aim to support rapid development of complete database systems, construction of powerful system- independent query interfaces on top of relational and flat- file data resources, integration of heterogeneous data resources and applications into a common object- oriented framework, deployment of configurable Web- based query interfaces for single or multiple databases.  [CHI Bioinformatics report]

Google = about 568,000 July 19, 2002

open source: Open source definition annotated http://www.opensource.org/docs/definition.php 

Google = about 3,300,000,000  Aug. 17, 2002; about 464, 000,000 June 11, 2007

open source software:  Wikipedia http://en.wikipedia.org/wiki/Open_source_software 

The Cathedral and the bazaar, Eric Steven Raymond http://catb.org/~esr/writings/cathedral-bazaar/ 

Google = about 421, 000  Aug. 17, 2002; about 55.500,000 June 11, 2007

peta: 10¹⁵ quadrillions. SI unit prefixes beyond peta are exa¹⁰¹⁸ (quintillions), zetta¹⁰²¹ (sextillions) and yotta¹⁰²⁴ (septillions) Compare with prefixes for the smallest numbers: Ultrasensitivity atto, femto, micro, nano, pico, yocto, zepto 

petaflop: A petaflops computer is more powerful than all of the computers on today's Internet combined. If such a system incorporated a petabyte of memory, it could hold all 17 million books in the Library of Congress or several thousand years' worth of videotapes. To fabricate such a system today from the best price/ performance systems available requires up to 10 million processors and consumes more than one billion watts of power. Its cost would be approximately $25 billion dollars, and the supercomputer would fail every couple of minutes. The system would cover the flight decks of all existing Nimitz-class aircraft carriers or fill up most of the Empire State Building with its hardware. [T. Sterling "In pursuit of a quadrillion operations per second" Insights, NASA, Apr. 1998] http://www.hq.nasa.gov/hpcc/insights/vol5/petaflop.htm

Google = about  5,500  July 19, 2002

Related term: teraflop computing. Broader term: FLOP

quantum computation: A fundamentally new mode of information processing that can be performed only by harnessing physical phenomena unique to quantum mechanics (especially quantum interference). [FAQ, Centre for Quantum Computation, Univ. Oxford, UK, 2001] http://www.qubit.org/oldsite/QuantumComputationFAQ.html

Google = about 22,800 July 19, 2002, about 613,000 Oct. 3, 2005

quantum computing:  The idea of a computational device based on quantum mechanics was first explored in the 1970's and early 1980's by physicists and computer scientists such as Charles H. Bennett of the IBM Thomas J. Watson Research Center,  Paul A. Benioff of Argonne National Laboratory in Illinois, David Deutsch of the University of Oxford, and the late Richard P. Feynman of the California Institute of Technology (Caltech).  The idea emerged when scientists were pondering the fundamental limits of computation.  They understood that if technology continued to abide by Moore's Law, then the continually shrinking size of circuitry packed onto silicon chips would eventually reach a point where individual elements would be no larger than a few atoms.  Here a problem arose because at the atomic scale the physical laws that govern the behavior and properties of the circuit are inherently quantum mechanical in nature, not classical.  This then raised the question of whether a new kind of computer could be devised based on the principles of quantum physics.   Feynman was among the first to attempt to provide an answer to this question by producing an abstract model in 1982 that showed how a quantum system could be used to do computations.  He also explained how such a machine would be able to act as a simulator for quantum physics.  In other words, a physicist would have the ability to carry out experiments in quantum physics inside a quantum mechanical computer.   Later, in 1985, Deutsch realized that Feynman's assertion could eventually lead to a general purpose quantum computer and published a crucial theoretical paper showing that any physical process, in principle, could be modeled perfectly by a quantum computer.  Thus, a quantum computer would have capabilities far beyond those of any traditional classical computer.  After Deutsch published this paper, the search began to find interesting applications for such a machine.  [Jacob West, The Quantum Computer, An introduction, 2000]  http://www.cs.caltech.edu/~westside/quantum-intro.html

Google = about 44,700 July 19, 2002

Related terms: DNA computing, molecular computing, nanocomputer. Or are any of these the same? 

quantum information: Currently predicts that small bits of matter that are both exquisitely intertwined yet absolutely isolated are capable of such incredible feats as: absolutely foolproof protection of data transmissions (quantum cryptography) exponentially powerful and exceedingly rapid computation and data searching (quantum computing), in its most science-fiction-like (but at least theoretically possible) example, the ethereal "quantum teleportation" of the essence of matter — its quantum states — from one location to another. IBM Almaden Research Center, Quantum information at Almaden http://www.almaden.ibm.com/st/quantum_information/qio/index.shtml

qubit: A key concept in the very new field of quantum computing. The aim is to produce a device which is the quantum equivalent of the digital computer. The qubit (pronounced exactly the same was as the Old Testament measurement) is a 'quantum bit', the analogue at quantum dimensions of the ordinary computer's 1 or 0, on or off, heads or tails binary digit or bit. Unlike such digital representations, a qubit remains in an indeterminate state until it is observed, like a tossed coin that is still spinning. It was shown recently that in theory a quantum computer could solve certain mathematical problems, such as factoring large numbers, much faster than conventional ones, and so could be used, for example, in codebreaking. It might even be possible to employ the 'action at a distance' properties of quantum mechanics to transport information instantaneously over great distances without loss. This may all sound like S[cience] F[iction], but the first two- bit quantum logic gates were actually demonstrated at the end of 1995. [World Wide Words, 1996]  http://www.quinion.com/words/turnsofphrase/tp-qub1.htm

Google = about 20,000 July 19, 2002

RDF Resource Description Framework:  Integrates a variety of applications from library catalogs and world- wide directories to syndication and aggregation of news, software, and content to personal collections of music, photos, and events using XML as an interchange syntax. The RDF specifications provide a lightweight ontology system to support the exchange of knowledge on the Web.  W3C Semantic Web Activity, accessed May 5, 2005  http://www.w3.org/RDF/  

RSS  A format for syndicating news and the content of news-like sites ...  The name "RSS" is an umbrella term for a format that spans several different versions of at least two different (but parallel) formats. Mark Pilgrim, What is RSS? O'Reilly XML, 2002  http://www.xml.com/pub/a/2002/12/18/dive-into-xml.html 

robots: See Google definitions for WWW robot http://www.robotstxt.org/wc/faq.html#what other kinds of robots, and spiders, webcrawlers, worm, and ants http://www.robotstxt.org/wc/faq.html#kinds

Web robots http://www.robotstxt.org/wc/robots.html 

See also: Drug discovery & development  robot, robotic systems  

SMP Symmetric MultiProcessing: Multiple processors (two or more) share the same memory and operating system. SMP systems are scalable, as more processors can be added as needed. Related term: MMP

server farm:  geek.com definition http://www.geek.com/glossary/glossary_search.cgi?s  
Netlingo definition http://www.netlingo.com/lookup.cfm?term=server%20farm
TechTarget definition: http://whatis.techtarget.com/definition/0,,sid9_gci213707,00.html
Weboepedia definition http://www.webopedia.com/TERM/S/server_farm.html

Google = about 78,000 July 19, 2002

Related term: compute farm

server types:  Webopaedia http://www.webopedia.com/quick_ref/servers.asp

soft computing: Principal constituents of soft computing (SC) are fuzzy logic (FL), neural network theory (NN) and probabilistic reasoning (PR), with the latter subsuming belief networks, evolutionary computing including DNA computing, chaos theory and parts of learning theory.... Differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost.  Lotfi A. Zadeh, What is BISC? Berkeley Initiative on Soft Computing,   http://www-bisc.cs.berkeley.edu/bisc/bisc.memo.html#what_is_sc

software interoperability: Information management & interpretation

supercomputer: FOLDOC definition http://wombat.doc.ic.ac.uk/foldoc/foldoc.cgi?supercomputer 
Webopedia definition http://www.webopedia.com/TERM/S/supercomputer.html
whatis.com definition http://www.swif.uniba.it/lei/foldop/foldoc.cgi?supercomputer

Very fast computers. Often used for graphics, modeling or simulations. 

Getting up to Speed: The Future of Supercomputing, National Academies of Science, US, 2004  http://books.nap.edu/catalog/11148.html 

Google = about 393,000 July 19, 2002

Related terms: high performance computing, petaflop, teraflop; Protein structure Blue gene 

teraFlop (Tflop): 10 ¹² floating point operations per second  (trillions).

The development of massively parallel computers with teraflop speed and the mastering of the associated programming problems will clearly shape new computational solutions for biomedicine in coming years ... in the field of experimental structural biology. Techniques for the experimental determination of biological structure increasingly rely on advanced computational tools. X-ray crystallography, NMR structure determination, and single molecule electron microscopy all continue to make advances in capabilities following increases in computing power. [Opportunities in Molecular Biomedicine in the Era of Teraflop Computing, March 3 & 4, 1999, Rockville, MD, NIH Resource for Macromolecular Modeling and Bioinformatics; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana- Champaign]  http://www.ks.uiuc.edu/Publications/Reports/teraflop/node4.html

Google = about  12,500 July 19, 2002; about 21,000 June 16, 2003

Related term: petaflop computing. Broader term: FLOP

teragrid:  A multi- year effort to build and deploy the world's largest, fastest, most comprehensive, distributed infrastructure for open scientific research. When completed, the TeraGrid will include 13.6 teraflops of Linux Cluster computing power distributed at the four TeraGrid sites, facilities capable of managing and storing more than 450 terabytes of data, high- resolution visualization environments, and toolkits for grid computing. These components will be tightly integrated and connected through a network that will initially operate at 40 gigabits per second and later be upgraded to 50- 80 gigabits/ second — 16 times faster than today's fastest research network.  [TeraGrid.org Home Page] http://www.teragrid.org/

Google = about 5, 590 Aug. 21, 2002

ubiquitous computing: Ubiquitous computing and wearable computing have been posed as polar opposites even though they are often applied in very similar applications. Here we first outline the advantages and disadvantages of each and propose that the two perspectives have complementary problems. We then attempt to demonstrate that the failing of both ubiquitous and wearable computing can be alleviated by the development of systems that properly mix the two. ... When Mark Weiser coined the phrase "ubiquitous computing" in 1988 he envisioned computers embedded in walls, in tabletops, and in everyday objects. In ubiquitous computing, a person might interact with hundreds of computers at a time, each invisibly embedded in the environment and wirelessly communicating with each other [Weiser, 1993]. Closely related to the ubiquitous computing vision is the more centralized idea of smart rooms, where a room might contain multiple sensors that keep track of the comings and goings of the people around [Pentland, 1996]. [Bradley J. Rhodes et. al, Wearable computing meets ubiquitous computing: Reaping the best of both worlds, The Proceedings of The Third International Symposium on Wearable Computers (ISWC '99), San Francisco, CA, October 18-19, 1999, pp. 141-149] http://web.media.mit.edu/~rhodes/Papers/wearhive.html

Has roots in many aspects of computing. In its current form, it was first articulated by Mark Weiser in 1988 at the Computer Science Lab at Xerox PARC. [Ubiquitous computing, Xerox PARC Sandbox Server] http://www.ubiq.com/hypertext/weiser/UbiHome.html

Ubiquitous computing, MIT Media Lab special issue IBM Systems Journal 39 (384) 2000  http://www.research.ibm.com/journal/sj39-34.html

Google = about 39,900 July 19, 2002

Related term: pervasive computing

utility computing:  {Chris] Dagdigian [of BioTeam]  tries hard not to use the term ‘cloud,’ preferring instead utility computing or simply “The C word.” “Amazon Web Services is the cloud,” said Dagdigian  Bio-IT World Nov 18, 2009 http://www.bio-itworld.com/2009/11/18/c-word.html 

Computing power on demand (similar to electricity). Sun, HP [Hewlett Packard] and IBM have utility computing initiatives.

Google = about 24,500 Mar. 27, 2003

virtualization:  TechTarget definition http://searchstorage.techtarget.com/sDefinition/0,,sid5_gci499539,00.html

wrappers: See Bioinformatics under integrated databases

XACML Extensible Access Control Markup Language: The purpose of this TC [Technical Committee] is to define a core schema and corresponding namespace for the expression of authorization policies in XML against objects that are themselves identified in XML http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xacml

Google = about 10,100   May 2, 2003

XML eXtensible Markup Language : The universal format for structured documents and data on the Web. [W3C, "Extensible Markup Language (XML)" 2002] http://www.w3.org/XML/

Describes a class of data objects called XML documents and partially describes the behavior of computer programs which process them. XML is an application profile or restricted form of SGML, the Standard Generalized Markup Language. By construction, XML documents are conforming SGML documents."

"XML is primarily intended to meet the requirements of large- scale Web content providers for industry- specific markup, vendor- neutral data exchange, media- independent publishing, one- on- one marketing, workflow management in collaborative authoring environments, and the processing of Web documents by intelligent clients. It is also expected to find use in certain metadata applications. [Robin Cover, XML Cover Pages, 2002]

Google = about  13,100,000  July 19, 2002

XML glossary, http://java.sun.com/xml/jaxp/dist/1.1/docs/tutorial/glossary.html  50+ definitions, from  Working with XML, Eric Armstrong and a worldwide cast of contributors, 

Well-formed XML Documents, Bonnie SooHoo, WebReview, Aug. 4, 2000. http://www.webreview.com/2000/08_04/webauthors/08_04_00_4.shtml

XML in 10 points http://www.w3.org/XML/1999/XML-in-10-points

Related terms: CORBA, RDF; Bioinformatics bioxml.org Narrower term: Business of biopharmaceuticals XBRL

XML schema: Express shared vocabularies and allow machines to carry out rules made by people.  They provide a means for defining the structure, content and semantics of XML documents. [W3C consortium "XML schema"] http://www.w3.org/XML/Schema

Google = about  205,000 July 19, 2002

XSLT eXtensible Stylesheet Language Transformations: http://www.w3.org/TR/xslt 

Bibliography
ACM Computing Classification System, Association of Computing Machinery, 1998 http://www.acm.org/class/1998/ Currently valid [2002] no definitions
Cnet glossary, http://www.cnet.com/Resources/Info/Glossary/index.html
FDA, Glossary of Computerized System and Software Development Terminology last updated 2009, 700 + terms  http://www.fda.gov/iceci/inspections/inspectionguides/ucm074875.htm 
FOLDOC Free On-line Dictionary of Computing, Denis Howe, 2007. 14,400+ terms.  http://foldoc.org/ 
Free software glossary, Leonard Andrew, The Free Software Project, Salon.com, 2000, 66 definitions http://dir.salon.com/story/tech/fsp/2000/03/05/glossary/
Geek.com Technical Glossary, 1996-2002, 2000+ definitions.    http://www.geek.com/glossary/glossary_search.htm
Howe, Walt, Glossary of Internet Terms,  2002, 360 + terms http://www.walthowe.com/glossary/
IBM terminology website http://www-306.ibm.com/software/globalization/terminology/index.jsp 
Jargon File 4.4.7, 2003  http://catb.org/esr/jargon/ 
Lycos Tech Glossary 2002 http://webopedia.lycos.com/
Microsoft Lexicon or Microspeak made easier, Ken Barnes et. al, 1995-1998, 150 + terms.  http://www.cinepad.com/mslex.htm
National Center for Supercomputing Applications, MetaComputer Glossary, Univ. of Illinois, Urbana- Champaign 1995] 45 definitions. http://archive.ncsa.uiuc.edu/Cyberia/MetaComp/MetaGlossary.html
W3C Glossaries, http://www.w3.org/Glossary  Links to 6 web, internet, W3c, hypermedia glossaries, acronyms and 5 specialized glossaries [document object model, math, quality assurance, web accessibility initiative and web services. 
Weboepedia  http://www.webopedia.com/
whatis.com Information Technology encyclopedia. About 3,000 +  definitions.  http://whatis.techtarget.com/
WordSpy, Paul McFedries  http://www.wordspy.com/ 

Alpha glossary index

How to look for other unfamiliar  terms