in silico

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From in and silicon (from Latin silex (flint, pebble, stone; crag, rock)) +‎ -o, by analogy with English in vitro (in glass, referring to an experiment conducted in a test tube). The silico component refers to silicon chips which were used for computing at the time when the term was coined.


Prepositional phrase[edit]

in silico

  1. (computing, sciences) In computer simulation or in virtual reality.
    He was able to dissect the frog in silico.
    • 1996, Antoine Danchin, “On Genomes and Cosmologies”, in Julio Collado-Vides, Boris Magasanik, and Temple F[erris] Smith, editors, Integrative Approaches to Molecular Biology, Cambridge, Mass.; London: MIT Press, →ISBN, page 92:
      In the future, computers can be used as experimental tools, generating a new source of investigation of living organisms, their study in silico (in contrast to in vivo or in vitro).
    • 2016, Bruno O. Villotriex; Melaine A. Kuenemann; David Lagorce; Olivier Sperandio; Maria A. Miteva, “In Silico Approaches Assisting the Rational Design of Low Molecular Weight Protein–Protein Interaction Modulators”, in Claudio N. Cavasotto, editor, In Silico Drug Discovery and Design: Theory, Methods, Challenges, and Applications, Boca Raton, Fla.: CRC Press, →ISBN, page 460:
      The term "virtual screening" (or in silico screening) was first reported in the scientific literature in 1997 []; it can be defined as a set of computer methods that analyzes large databases or collections of compounds in order to identify and prioritize likely hit candidates []. In silico screening search can be performed on libraries that contain physically existing compounds or on virtual libraries, and thus on compounds that are not yet synthesized. [] [I]t should be noted that in silico screening goes much beyond number crunching, it helps to generate ideas, to reduce the cost and to gain knowledge.
    • [2017], D. Bower; K. P. Cross; S. Escher; G. J. Myatt; D. P. Quigley, “In Silico Toxicology: An Overview of Toxicity Databases, Prediction Methodologies, and Expert Review”, in Dale E. Johnson and Rudy J. Richardson, editors, Computational Systems Pharmacology and Toxicology (Issues in Toxicology; no. 31), London: Royal Society of Chemistry, →ISBN, ISSN 1757-7179, page 213:
      There is an increasing number of in silico models for toxicological endpoints. Some of these models offer significant benefits over existing in vivo or in vitro models. First, they require no materials and will make a prediction from the chemical structure alone. Once the models are built, they are usually fast and cheap to run. []

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