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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
1000:
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",
140:
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
589:
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",
917:
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",
213:(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
754:
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).
641:
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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258:, as well as the absence of available computer processing power, force large simplifying assumptions that constrain the usefulness of present in silico cell models.
787:
Athanaileas, Theodoros; et al. (2011). "Exploiting grid technologies for the simulation of clinical trials: the paradigm of in silico radiation oncology".
425:
116:). The latter phrases refer, respectively, to experiments done in living organisms, outside living organisms, and where they are found in nature.
963:
Dobson, N; Dantas, G; Baker, D; Varani, G (2006), "High-Resolution
Structural Validation of the Computational Redesign of Human U1A Protein",
756:"Computational screening and identifying binding interaction of anti-viral and anti-malarial drugs: Toward the potential cure for SARS-CoV-2"
643:"Computational screening and identifying binding interaction of anti-viral and anti-malarial drugs: Toward the potential cure for SARS-CoV-2"
250:
These efforts fall far short of an exact, fully predictive computer model of a cell's entire behavior. Limitations in the understanding of
236:
Efforts have been made to establish computer models of cellular behavior. For example, in 2007 researchers developed an in silico model of
167:
written to support the creation of bacterial genome programs by the
Commission of the European Community. The first referenced paper where
28:
142:
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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.
1207:
493:
822:
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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201:), 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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697:"Temporal Controls of the Asymmetric Cell Division Cycle in Caulobacter crescentus"
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281:), 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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205:. 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.
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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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87:
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52:
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development and optimization e.g. optimization of product yields
824:"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
224:study in order to search for potential cures for
61:experiment is one performed on a computer or via
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220:As an example, the technique was utilized for a
209:. This approach differs from use of expensive
348:Analysis, interpretation and visualization of
16:Latin phrase referring to computer simulations
566:Sieburg, H.B. (1990), "Physiological Studies
124:The earliest known use of the phrase was by
625:New computational tool for cancer treatment
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328:Discovery of potential cure for COVID-19.
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143:National Autonomous University of Mexico
27:
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673:University Of Surrey. June 25, 2007.
572:Studies in the Sciences of Complexity
186:Drug discovery with virtual screening
675:In Silico Cell For TB Drug Discovery
352:data sets from various sources e.g.
55:and other experimental sciences, an
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1208:Alternatives to animal testing
681:. Retrieved February 12, 2010.
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631:. Retrieved February 12, 2010.
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592:Journal of Medicinal Chemistry
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482:Hameroff, S. R. (2014-04-11).
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134:Los Alamos National Laboratory
1:
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341:infrastructures, such as the
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47:'s laws of neuronal branching
1003:Journal of Molecular Biology
920:Journal of Molecular Biology
881:(Web Server issue): W235–8,
722:10.1371/journal.pcbi.1000463
546:10.1016/0923-2508(91)90073-J
343:European Grid Infrastructure
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1068:Seventh Framework Programme
828:Molecular Ecology Resources
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69:for 'in silicon' (correct
21:In silico (disambiguation)
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1015:10.1016/j.jmb.2006.11.080
978:10.1016/j.str.2006.02.011
429:molecular design programs
391:Computational biomodeling
283:artificial gene synthesis
267:Digital genetic sequences
211:high-throughput screening
1203:Latin biological phrases
801:10.1177/0037549710375437
524:Research in Microbiology
136:in 1987. The expression
65:software. The phrase is
1198:Pharmaceutical industry
841:10.1111/1755-0998.13425
773:10.36877/pddbs.a0000065
660:10.36877/pddbs.a0000065
297:Whole cell analysis of
1213:Animal test conditions
1089:In Silico Pharmacology
875:Nucleic Acids Research
244:Caulobacter crescentus
199:Protein-ligand docking
197:algorithm EADock (see
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32:A forest of synthetic
508:Miramontes P. (1992)
386:Computational biology
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1158:Computer programming
19:For other uses, see
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512:. PhD Thesis. UNAM.
416:Nonclinical studies
396:Computer experiment
277:, be analyzed (see
126:Christopher Langton
63:computer simulation
1082:2020-10-21 at the
1063:2012-03-30 at the
1050:World Wide Words:
887:10.1093/nar/gkl163
434:In silico medicine
275:sequence databases
252:molecular dynamics
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604:10.1021/jm9014718
495:978-0-444-60009-7
463:groups.google.com
381:Virtual screening
279:Sequence analysis
273:may be stored in
192:virtual screening
163:has been used in
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314:B. subtilis
305:hosts e.g.
299:prokaryotic
232:Cell models
178:The phrase
1192:Categories
468:2020-01-05
445:References
332:Bioprocess
323:human cell
321:, CHO- or
303:eukaryotic
75:in silicio
39:generated
1170:Astronomy
1146:Chemistry
1052:In silico
965:Structure
928:CiteSeerX
809:206429690
693:Tyson, JJ
578:: 321–342
568:in silico
532:CiteSeerX
427:In silico
203:in silico
180:in silico
173:in silico
169:in silico
161:In silico
138:in silico
58:in silico
41:in silico
37:dendrites
34:pyramidal
1080:Archived
1061:Archived
1058:CADASTER
1033:17196978
987:16698546
950:12948494
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695:(2009).
612:20055453
375:See also
362:proteome
262:Genetics
226:COVID-19
207:in vitro
96:in vitro
1182:Science
1134:Biology
1122:Physics
1110:Science
1096:Portals
1024:3764424
896:1538902
851:8518049
732:2714070
709:Bibcode
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439:Dry lab
308:E. coli
120:History
110:biology
104:in situ
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856:PMID
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