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In silico study in medicine is thought to have the potential to speed the rate of discovery while reducing the need for expensive lab work and clinical trials. One way to achieve this is by producing and screening drug candidates more effectively. In 2010, for example, using the protein docking
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to aid in drug discovery, with the prime benefit of its being faster than real time simulated growth rates, allowing phenomena of interest to be observed in minutes rather than months. More work can be found that focus on modeling a particular cellular process such as the growth cycle of
1011:
Dantas, G; Corrent, C; Reichow, S; Havranek, J; Eletr, Z; Isern, N; Kuhlman, B; Varani, G; et al. (2007), "High-resolution
Structural and Thermodynamic Analysis of Extreme Stabilization of Human Procarboxypeptidase by Computational Protein Design",
151:
was first used to characterize biological experiments carried out entirely in a computer in 1989, in the workshop "Cellular
Automata: Theory and Applications" in Los Alamos, New Mexico, by Pedro Miramontes, a mathematician from
600:
Röhrig, Ute F.; Awad, Loay; Grosdidier, AuréLien; Larrieu, Pierre; Stroobant, Vincent; Colau, Didier; Cerundolo, Vincenzo; Simpson, Andrew J. G.; et al. (2010), "Rational Design of
Indoleamine 2,3-Dioxygenase Inhibitors",
928:
Dantas, Gautam; Kuhlman, Brian; Callender, David; Wong, Michelle; Baker, David (2003), "A Large Scale Test of
Computational Protein Design: Folding and Stability of Nine Completely Redesigned Globular Proteins",
224:(HTS) robotic labs to physically test thousands of diverse compounds a day, often with an expected hit rate on the order of 1% or less, with still fewer expected to be real leads following further testing (see
765:
Lee, Vannajan
Sanghiran; Chong, Wei Lim; Sukumaran, Sri Devi; Nimmanpipug, Pivarat; Letchumanan, Vengadesh; Goh, Bey Hing; Lee, Learn-Han; Md. Zain, Sharifuddin; Abd Rahman, Noorsaadah (2020).
652:
Lee, Vannajan
Sanghiran; Chong, Wei Lim; Sukumaran, Sri Devi; Nimmanpipug, Pivarat; Letchumanan, Vengadesh; Goh, Bey Hing; Lee, Learn-Han; Md. Zain, Sharifuddin; Abd Rahman, Noorsaadah (2020).
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originally applied only to computer simulations that modeled natural or laboratory processes (in all the natural sciences), and did not refer to calculations done by computer generically.
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269:, as well as the absence of available computer processing power, force large simplifying assumptions that constrain the usefulness of present in silico cell models.
798:
Athanaileas, Theodoros; et al. (2011). "Exploiting grid technologies for the simulation of clinical trials: the paradigm of in silico radiation oncology".
436:
127:). The latter phrases refer, respectively, to experiments done in living organisms, outside living organisms, and where they are found in nature.
974:
Dobson, N; Dantas, G; Baker, D; Varani, G (2006), "High-Resolution
Structural Validation of the Computational Redesign of Human U1A Protein",
767:"Computational screening and identifying binding interaction of anti-viral and anti-malarial drugs: Toward the potential cure for SARS-CoV-2"
654:"Computational screening and identifying binding interaction of anti-viral and anti-malarial drugs: Toward the potential cure for SARS-CoV-2"
261:
These efforts fall far short of an exact, fully predictive computer model of a cell's entire behavior. Limitations in the understanding of
247:
Efforts have been made to establish computer models of cellular behavior. For example, in 2007 researchers developed an in silico model of
178:
written to support the creation of bacterial genome programs by the
Commission of the European Community. The first referenced paper where
39:
153:
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appears was written by Hans B. Sieburg in 1990 and presented during a Summer School on
Complex Systems at the Santa Fe Institute.
1218:
504:
833:
Chua, Physilia Y. S.; Crampton-Platt, Alex; Lammers, Youri; Alsos, Inger G.; Boessenkool, Sanne; Bohmann, Kristine (2021).
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Physicochemical
Constraints, Cellular Automata and Molecular Evolution". The work was later presented by Miramontes as his
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Protein design. One example is RosettaDesign, a software package under development and free for academic use.
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Danchin, A; MĂ©digue, C; Gascuel, O; Soldano, H; HĂ©naut, A (1991), "From data banks to data bases",
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project aimed to develop in silico computational methods to minimize experimental tests for REACH
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212:), researchers found potential inhibitors to an enzyme associated with cancer activity
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appears was written by a French team in 1991. The first referenced book chapter where
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708:"Temporal Controls of the Asymmetric Cell Division Cycle in Caulobacter crescentus"
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292:), be digitally altered or be used as templates for creating new actual DNA using
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SIMULATION: Transactions of the Society for Modeling and Simulation International
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Liu, Y; Kuhlman, B (July 2006), "RosettaDesign server for protein design",
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216:. Fifty percent of the molecules were later shown to be active inhibitors
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In silico computer-based modeling technologies have also been applied in:
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Validation of taxonomic assignment steps in herbivore metagenomics study.
309:
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In Silico Biology. Journal of Biological Systems Modeling and Simulation
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Un modelo de autómata celular para la evolución de los ácidos nucleicos
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Registration, Evaluation, Authorisation and Restriction of Chemicals
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Ultimate Computing: Biomolecular Consciousness and NanoTechnology
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development and optimization e.g. optimization of product yields
835:"Metagenomics: A viable tool for reconstructing herbivore diet"
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in computer chips. It was coined in 1987 as an allusion to the
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Ludwig Institute for Cancer Research (2010, February 4).
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Simulation of oncological clinical trials exploiting
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Progress in Drug Discovery & Biomedical Science
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Progress in Drug Discovery & Biomedical Science
235:study in order to search for potential cures for
72:experiment is one performed on a computer or via
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231:As an example, the technique was utilized for a
220:. This approach differs from use of expensive
359:Analysis, interpretation and visualization of
27:Latin phrase referring to computer simulations
577:Sieburg, H.B. (1990), "Physiological Studies
135:The earliest known use of the phrase was by
636:New computational tool for cancer treatment
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339:Discovery of potential cure for COVID-19.
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154:National Autonomous University of Mexico
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14:
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684:University Of Surrey. June 25, 2007.
583:Studies in the Sciences of Complexity
197:Drug discovery with virtual screening
686:In Silico Cell For TB Drug Discovery
363:data sets from various sources e.g.
66:and other experimental sciences, an
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702:Li, S; Brazhnik, P; Sobral, B;
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1219:Alternatives to animal testing
692:. Retrieved February 12, 2010.
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642:. Retrieved February 12, 2010.
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603:Journal of Medicinal Chemistry
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493:Hameroff, S. R. (2014-04-11).
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145:Los Alamos National Laboratory
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1:
953:10.1016/S0022-2836(03)00888-X
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352:infrastructures, such as the
119:, which are commonly used in
58:'s laws of neuronal branching
1014:Journal of Molecular Biology
931:Journal of Molecular Biology
892:(Web Server issue): W235–8,
733:10.1371/journal.pcbi.1000463
557:10.1016/0923-2508(91)90073-J
354:European Grid Infrastructure
7:
1079:Seventh Framework Programme
839:Molecular Ecology Resources
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10:
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80:for 'in silicon' (correct
32:In silico (disambiguation)
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1026:10.1016/j.jmb.2006.11.080
989:10.1016/j.str.2006.02.011
440:molecular design programs
402:Computational biomodeling
294:artificial gene synthesis
278:Digital genetic sequences
222:high-throughput screening
1214:Latin biological phrases
812:10.1177/0037549710375437
535:Research in Microbiology
147:in 1987. The expression
76:software. The phrase is
1209:Pharmaceutical industry
852:10.1111/1755-0998.13425
784:10.36877/pddbs.a0000065
671:10.36877/pddbs.a0000065
308:Whole cell analysis of
1224:Animal test conditions
1100:In Silico Pharmacology
886:Nucleic Acids Research
255:Caulobacter crescentus
210:Protein-ligand docking
208:algorithm EADock (see
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43:A forest of synthetic
519:Miramontes P. (1992)
397:Computational biology
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1169:Computer programming
30:For other uses, see
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523:. PhD Thesis. UNAM.
427:Nonclinical studies
407:Computer experiment
288:, be analyzed (see
137:Christopher Langton
74:computer simulation
1093:2020-10-21 at the
1074:2012-03-30 at the
1061:World Wide Words:
898:10.1093/nar/gkl163
445:In silico medicine
286:sequence databases
263:molecular dynamics
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615:10.1021/jm9014718
506:978-0-444-60009-7
474:groups.google.com
392:Virtual screening
290:Sequence analysis
284:may be stored in
203:virtual screening
174:has been used in
16:(Redirected from
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325:B. subtilis
316:hosts e.g.
310:prokaryotic
243:Cell models
189:The phrase
1203:Categories
479:2020-01-05
456:References
343:Bioprocess
334:human cell
332:, CHO- or
314:eukaryotic
86:in silicio
50:generated
1181:Astronomy
1157:Chemistry
1063:In silico
976:Structure
939:CiteSeerX
820:206429690
704:Tyson, JJ
589:: 321–342
579:in silico
543:CiteSeerX
438:In silico
214:in silico
191:in silico
184:in silico
180:in silico
172:In silico
149:in silico
69:in silico
52:in silico
48:dendrites
45:pyramidal
1091:Archived
1072:Archived
1069:CADASTER
1044:17196978
998:16698546
961:12948494
916:16845000
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623:20055453
386:See also
373:proteome
273:Genetics
237:COVID-19
218:in vitro
107:in vitro
18:Insilico
1193:Science
1145:Biology
1133:Physics
1121:Science
1107:Portals
1035:3764424
907:1538902
862:8518049
743:2714070
720:Bibcode
565:1784830
450:Dry lab
319:E. coli
131:History
121:biology
115:in situ
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330:yeast
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56:Cajal
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957:PMID
912:PMID
867:PMID
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561:PMID
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375:data
312:and
265:and
160:and
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