Chemistry
term index
Drug
discovery term index Informatics
term index Technologies term
index Biology term index
Related glossaries include: Drug discovery &
development Genomics, Proteomics
Informatics Algorithms & data
analysis Bioinformatics
Clinical informatics Drug
discovery informatics Information management
& interpretation
Technologies: Combinatorial libraries &
synthesis Sequencing
Biology DNA Gene definitions
RNA Protein Structures
agent:
Definitions for autonomous agents, intelligent agents, user- agent.
Amazon
Web Services AWS: Today's life science
organizations must deal with increasingly complex network, storage and
computational requirements. Next-generation lab instruments and protocols are
changing faster than the underlying research IT infrastructures built to support
them. Operating an efficient, scalable and agile research IT infrastructure in
the face of such rapid change is a complex challenge we all encounter.
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: refers to computational systems that use very
large numbers of identical, parallel processors each having limited
computational ability and local interactions. The term Amorphous Computing was
coined at MIT in 1996 in a paper entitled "Amorphous
Computing Manifesto" by Abelson, Knight, Sussman, et al. Wikipedia
accessed 2018 Oct 25
https://en.wikipedia.org/wiki/Amorphous_computing
Amorphous Computing Homepage,
Artificial Intelligence, MIT, US http://groups.csail.mit.edu/mac/projects/amorphous/
autonomic computing:
https://en.wikipedia.org/wiki/Autonomic_computing
Beowulf computing:
Wikipedia http://en.wikipedia.org/wiki/Beowulf_(computing)
bikeshed:
Why should I care? [metaphor] http://www.unixguide.net/freebsd/faq/16.19.shtml
Thanks to World Wide Words
biomedical
computational science and technology
The
NIH is interested in promoting research and developments in computational
science and technology that will support rapid progress in areas of scientific
opportunity in biomedical research. As defined here, biomedical computing or
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, and tools for electronic collaboration, as well as
computational and mathematical research including the development of structural,
functional, integrative, and analytical models and simulations.
Program Announcement (PA) Number: PAR-09-218
https://grants.nih.gov/grants/guide/pa-files/PAR-09-218.html
Blockchain in Pharma, R&D, and Healthcare: Empowering
the Networking Ecosystem 2019 April 17-18 Boston MS Blockchain
is becoming increasingly adopted to address the perennial networking
challenges of visibility, integrity, security, and speed for data
management in pharma, R&D, and healthcare. Innovative personalized
therapies are driving this shift of proprietary data-driven life sciences
supply chains, from basic research to R&D to clinical trials to
manufacturing to patient.
http://www.bio-itworldexpo.com/blockchain
Cloud
Computing: Applying
Cloud for Expanding Applications 2019 April 17-18 Boston MA
Cloud computing has become the platform
enterprises turn to for their application analysis as well as data
storage. Data-intensive life scientists from biological researchers to
biopharmaceutical organizations realize this practicality and necessity.
Thus, adoption has been greater than anyone expected and users continue to
expand applications. Through case studies, explores the rapid growth and
progressive maturation of cloud as well as evolving provider and user
experiences.
http://www.bio-itworldexpo.com/cloud-computing
See also: Amazon Web Services AWS, utility computing
computational linguistics: Information management
& interpretation
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...
compute farm: Related terms: compute server farm, ranch, server farm.
computer virus:
Virus Glossary of terms,
McAfee, 100 + definitions, http://home.mcafee.com/VirusInfo/Glossary.aspx
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
configurable:
To eliminate confusion and hopefully give the
industry a common way to talk about these issues, LNS Research will use
the following definitions for each of these terms:
Out-of-the-Box: Any functionality that
comes shipped directly from the software vendor or can be configured
easily (where “easily” means configured by a business, not IT user) with
built-in workflow tools, templates, and/or best practices provided
directly by the vendor.
Configurable: Any functionality that can
be created using built-in workflow tools shipped by the vendor. To be
considered configurable, functionality should be forward-compatible with
future releases.
Customizable: Any functionality that is
configured using built-in workflow tools shipped by the vendor, but may
not be forward compatible with future releases. Also, other functionality
not shipped directly from the vendor that cannot be created using built-in
workflow tools shipped by the vendor. All customization has no guarantee
of compatibility with future releases and contains the risk of being
costly to maintain over time.
Understanding Out-of-the-Box vs.
Configured vs. Customized Software Posted by Matthew
Littlefield on
Fri, Jan 30, 201
http://blog.lnsresearch.com/blog/bid/204226/Understanding-Out-of-the-Box-vs-Configured-vs-Customized-Software
Configurable gives users the chance to
modify options, without expensive programming.
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
Related terms: interoperability, object- oriented
customizable:
Customized
implies programming and expense. Compare configurable
Data & Storage Management:
Infrastructure and data storage solutions to enable discovery and east
data bloat 2018 April 16-18 Boston MA Is the burden of managing your data
growing larger every day? Do you have a scalable and robust data
management infrastructure in place to process, analyze, and store vast
quantities of data according to your organization policies? Is your
organization using new tools and analytical processes such as AI and deep
learning that stress your supporting IT infrastructure beyond the
expectations of system designers? Managing data has become a prevalent
issue in the life sciences industry. Organizations are spending millions
on systems and platforms to manage and store many types of data (e.g.,
experimental, operational, clinical) from many different disparate
sources. The role of data engineering is critical in orchestrating,
configuring, managing, and scaling solutions to manage the data bloat
problem. http://www.bio-itworldexpo.com/data-storage
Data Computing: Improving
Scale, Speed and Ease of Deployment 2019 April 17-18 Boston MA
There is an increased demand in computing power from life science
researchers and scientists tackling big data issues. To do their work,
their storage and infrastructure must be able to scale to handle billions
of data points and files efficiently. The Data
Computing
track will explore data computing resources and application deployment
tools that are needed to process computational workflows and drive
automation, advance analytics capabilities, reproduce software deployment,
maximize application performance, and drive broad organizational decision
processes.
http://www.bio-itworldexpo.com/data-computing
Data management in the Cloud 2019
March 11-13 San Francisco CA Integrating Data from
Disparate Sources to Achieve the Goal of Personalized Medicine
Program
Today, IT professionals are
challenged with finding solutions to manage big data being generated at
research labs, pharmaceutical companies and medical centers. In order to
do this, one must have the compute power, storage solutions, and analytic
capability to make the data clinically actionable. Data from disparate
sources including omics (genomics, proteomics, metabolomics, etc.),
imaging, and sensors must be integrated. Cambridge Healthtech Institute's
2nd Annual
Data Management in the Cloud program will bring together key leaders in
the fields of cloud architecture and data management to share case studies
and to discuss the challenges and solutions they face in their centers.
Overall, this event is will offer practical solutions for network
engineers, data architects, software engineers, etc. to build data
ecosystems which enable the goal of personalized medicine. https://www.bio-itworldexpowest.com/Converged-IT-and-the-Cloud
Edge: Intelligent
Compute from Device to Cloud 2019 April 17-18 Boston MA
Simply defined, edge can be considered where people and devices or things
connect with the network. Compute-intensive edge applications, including
Internet of Things (IOT), augmented reality (AR), and artificial intelligence
(AI), interact with their environment based on ever-changing conditions. Where
should this complex data be transferred, stored, and analyzed? During the
Inaugural Edge
track, data scientists share their real-world living-on-edge experiences of
leveraging this shifting space to increasingly deliver on the promise of cloud
and its growing complexity
http://www.bio-itworldexpo.com/edge
also known as just “edge”—brings processing close to the data source, and
it does not need to be sent to a remote cloud or other centralized systems
for processing. By eliminating the distance and time it takes to send data
to centralized sources, we can improve the speed and performance of data
transport, as well as devices and applications on the edge. Cisco,
Edge Computing vs. Fog Computing: Definitions and Enterprise Applications
https://www.cisco.com/c/en/us/solutions/enterprise-networks/edge-computing.html
a distributed
computing paradigm in which computation is largely or completely
performed on distributed device nodes known
as smart devices or edge
devices as opposed to primarily taking place in a centralized cloud
environment. The eponymous "edge" refers to the geographic
distribution of computing nodes in the network as Internet
of Things devices, which are at the "edge" of an enterprise, metropolitan or
other network.
The motivation is to provide server
resources, data
analysis and artificial
intelligence("ambient
intelligence") closer
to data collection sources and cyber-physical
systems such as smart
sensors and actuators.[1] Edge
computing is seen as important in the realization of physical
computing, smart
cities, ubiquitous
computing and the Internet
of Things. Wikipedia accessed 2018 Dec. 10
https://en.wikipedia.org/wiki/Edge_computing
Related term: Internet of Things
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
Fog computing is
a standard that defines how edge computing should work, and it facilitates
the operation of compute, storage and networking services between end
devices and cloud computing data centers. Additionally, many use fog as a
jumping-off point for edge computing. Cisco, Edge Computing vs. Fog
Computing: Definitions and Enterprise Applications
https://www.cisco.com/c/en/us/solutions/enterprise-networks/edge-computing.html
Related term: Internet of Things
geek:
http://en.wikipedia.org/wiki/Geek
Compares with nerd but there are many nuances and variations.
Google
Custom Search APIs and Tools Glossary http://code.google.com/apis/customsearch/docs/glossary.html
grid computing:
Wikipedia http://en.wikipedia.org/wiki/Grid_computing
Narrower term: desktop grids; Related
terms: utility grids, Information management
& interpretation semantic grid
Grid computing glossary, Israel Association of Grid Technologies http://www.grid.org.il/?CategoryID=365
Hadoop:
The Apache™ Hadoop®
project develops open-source software for reliable, scalable, distributed
computing. The Apache Hadoop
software library is a framework that allows for the distributed processing of
large data sets across clusters of computers using simple programming models. It
is designed to scale up from single servers to thousands of machines, each
offering local computation and storage. Rather than rely on hardware to deliver
high-availability, the library itself is designed to detect and handle failures
at the application layer, so delivering a highly-available service on top of a
cluster of computers, each of which may be prone to failures. Hadoop http://hadoop.apache.org/
high performance computing:
Weboepedia
definition http://www.webopedia.com/TERM/H/High_Performance_Computing.html
Related terms: Distributed Computing Environment
DCE,
MPP Massively Parallel Processing, petaflop, supercomputers, teraflop
Internet of Things (IoT):
the network of
physical devices, vehicles, home appliances, and other items embedded
with electronics, software, sensors, actuators,
and connectivity which
enables these things to connect, collect and
exchange data.[1][2][3][4] IoT
involves extending Internet
connectivity beyond standard devices,
such as desktops, laptops, smartphones and
tablets, to any range of traditionally dumb or non-internet-enabled
physical devices and everyday objects. Embedded with technology, these
devices can communicate and interact over the Internet,
and they can be remotely monitored and controlled. Wikipedia accessed 2018
Nov 1 https://en.wikipedia.org/wiki/Internet_of_things
Kevin
Lonergan at Information Age, a business-technology magazine, has referred
to the terms surrounding IoT as a “terminology zoo”.[207] The
lack of clear terminology is not “useful from a practical point of view”
and a “source of confusion for the end user”.[207] A
company operating in the IoT space could be working in anything related to
sensor technology, networking, embedded systems, or analytics.[207] According
to Lonergan, the term IoT was coined before smart phones, tablets, and
devices as we know them today existed, and there is a long list of terms
with varying degrees of overlap and technological
convergence: Internet of things,
Internet of everything (IoE), Internet of Goods (Supply Chain), industrial
Internet, pervasive
computing, pervasive sensing, ubiquitous
computing, cyber-physical
systems (CPS), wireless
sensor networks (WSN), smart
objects, digital
twin, cyberobjects or avatars,[108] cooperating
objects, machine
to machine (M2M), ambient
intelligence (AmI), Operational
technology (OT), and information
technology(IT).[207] Regarding IIoT,
an industrial sub-field of IoT, the Industrial
Internet Consortium's Vocabulary Task
Group has created a "common and reusable vocabulary of terms"[208] to
ensure "consistent terminology"[208][209] across
publications issued by the Industrial Internet Consortium. IoT One has
created an IoT Terms Database including a New Term Alert[210] to
be notified when a new term is published. As of March 2017, this database
aggregates 711 IoT-related terms, while keeping material "transparent and
comprehensive."[211][212]https://en.wikipedia.org/wiki/Internet_of_things#Confusing_terminology
legacy systems:
Wikipedia http://en.wikipedia.org/wiki/Legacy_systems
Linux:
a family of free
and open-source software operating
systems built around the Linux
kernel. Typically, Linux is packaged in
a form known as a Linux
distribution (or distro for short) for both desktop and server use. The
defining component of a Linux distribution is the Linux
kernel,[11] an operating
system kernel first released on September 17, 1991, by Linus
Torvalds.[12][13][14] Many
Linux distributions use the word "Linux" in their name. .
Wikipedia accessed 2018 Nov 1
http://en.wikipedia.org/wiki/Linux
machine-understandable:
http://www.w3.org/DesignIssues/Semantic.html
See
also under metadata
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;
Drug
discovery informatics
VRML Virtual Reality Modeling Language; Microarrays
GEML Gene Expression Markup Language, MAGE-ML MicroArray and Gene Expression Markup Language
markup languages, standards core:
Robin Cover, Core Standards for Markup Languages, 2002 http://xml.coverpages.org/coreStandards.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
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
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. Related terms: integration,
interoperability
Wikipedia
http://en.wikipedia.org/wiki/Modularity
molecular
computers: Computers whose input, output and state
transitions are carried out by biochemical interactions and reactions. MeSH 2003
molecular computing:
Related terms: DNA computing, quantum
computing. Or are any of these the same?
Moore's Law:
Intel co-founder Gordon Moore is a visionary. His prediction, popularly known as
Moore's
Law, states that the number of transistors on a chip will double about every
two years. http://www.intel.com/technology/mooreslaw/
Wikipedia
http://en.wikipedia.org/wiki/Moore's_law
open source:
Open
source definition annotated http://www.opensource.org/docs/definition.php
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/
open
source programming languages:
http://opensourceforu.com/2017/03/most-popular-programming-languages/
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
Related term: teraflop computing. Broader
term: FLOP
quantum computing:
is computing using quantum-mechanical phenomena,
such as superposition and entanglement.[1] A quantum
computer is
a device that performs quantum computing. They are different from binary digital
electronic computers based
on transistors.
Whereas common digital computing requires that the data be encoded into binary
digits (bits),
each of which is always in one of two definite states (0 or 1), quantum
computation uses quantum
bits,
which can be in superpositions of
states. A quantum
Turing machine is
a theoretical model of such a computer, and is also known as the universal
quantum computer. The field of quantum computing was initiated by the work of Paul
Benioff (de)[2] and Yuri
Manin in
1980,[3] Richard
Feynman in
1982,[4] and David
Deutsch in
1985.[5]
...
As of 2018, the development of
actual quantum computers is still in its infancy, but experiments have been
carried out in which quantum computational operations were executed on a very
small number of quantum bits.[7] Both
practical and theoretical research continues, and many national governments and
military agencies are funding quantum computing research in additional effort to
develop quantum computers for
civilian, business,
trade, environmental and national security purposes, such as cryptanalysis.[8] A
small 20-qubit quantum computer exists and is available for experiments via the IBM
quantum experience project. Wikipedia accessed 2018 Feb 16
https://en.wikipedia.org/wiki/Quantum_computing
one
class of problems in which quantum computers have a significant speed
advantage is the modeling of large molecules to understand specific
interactions and chemical processes. The idea is to use quantum processors
to create a quantum (as opposed to a digital) twin, or simulation, and
model the quantum processes involved at the subatomic level.
Pharmaceutical and chemical companies are already experimenting with the
potential of quantum simulation to accelerate drug discovery and design
molecules with fewer unintended side effects. Executives in these
industries estimate that identifying new targets in this way could
increase the rate of drug discovery by 5% to 10% and accelerate
development times by 15% to 20%.
Boston Consulting Group, Coming Quantum
Leap Computing, 2018
https://www.bcg.com/en-us/publications/2018/coming-quantum-leap-computing.aspx
Related terms: DNA computing, molecular computing,
nanocomputer. Or are any of these the same?
quantum
information:
http://en.wikipedia.org/wiki/Quantum_information
supercomputer:
FOLDOC definition http://foldoc.org/supercomputer
Webopedia definition http://www.webopedia.com/TERM/S/supercomputer.html
Very fast computers. Often used for
graphics, modeling or simulations. Related terms: high performance computing, petaflop, teraflop;
Protein structure Blue gene
teraFlop (Tflop):
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 10 12
floating point operations per second (trillions).
Molecular Biomedicine in the Era of Teraflop Computing - DDDAS.org
Related term: petaflop computing.
Broader term: FLOP
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).
IT Infrastructure resources
FOLDOC Free On-line Dictionary of Computing, Denis
Howe,
http://foldoc.org/
Gartner IT Glossary
https://www.gartner.com/it-glossary/
IBM Terminology Website http://www-01.ibm.com/software/globalization/terminology/index.html
Intel Glossary
https://www.intel.com/content/www/us/en/support/topics/glossary.html
Jargon File 4.4.7, 2004 http://catb.org/esr/jargon/
McAfee Online Security Glossary 2003-2017 http://home.mcafee.com/VirusInfo/Glossary.aspx
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 Glossary & Dictionary, http://www.w3.org/2003/glossary/
2003-2010
Weboepedia, Quinstreet http://www.webopedia.com/
whatis.com Information Technology encyclopedia. http://whatis.techtarget.com/
How
to look for other unfamiliar terms
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