2005
DOI: 10.1038/nbt1118
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Design of a genome-wide siRNA library using an artificial neural network

Abstract: The largest gene knock-down experiments performed to date have used multiple short interfering/short hairpin (si/sh)RNAs per gene. To overcome this burden for design of a genome-wide siRNA library, we used the Stuttgart Neural Net Simulator to train algorithms on a data set of 2,182 randomly selected siRNAs targeted to 34 mRNA species, assayed through a high-throughput fluorescent reporter gene system. The algorithm, (BIOPREDsi), reliably predicted activity of 249 siRNAs of an independent test set (Pearson coe… Show more

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Cited by 338 publications
(419 citation statements)
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“…16 As many of the initial studies of mGluR7 have relied on information from mGluR7 knockout animals, 10,12,38,39 which are bred on a C57BL/6 background, we chose to conduct our siRNA studies on this background. Seventy-four male C57BL/6 mice (23-31 g; Charles River, France) were housed and surgeries performed as described previously, 15 40 ). Starting day 7 of intracerebroventricular infusions, mice were trained to drink water from 15 ml Falcon tubes (cut at the base for an outlet) for 30-min sessions per day, between 900 and 1000 (morning session), and between 1630 and 1730 (evening session).…”
Section: Cta Following Amn082mentioning
confidence: 99%
“…16 As many of the initial studies of mGluR7 have relied on information from mGluR7 knockout animals, 10,12,38,39 which are bred on a C57BL/6 background, we chose to conduct our siRNA studies on this background. Seventy-four male C57BL/6 mice (23-31 g; Charles River, France) were housed and surgeries performed as described previously, 15 40 ). Starting day 7 of intracerebroventricular infusions, mice were trained to drink water from 15 ml Falcon tubes (cut at the base for an outlet) for 30-min sessions per day, between 900 and 1000 (morning session), and between 1630 and 1730 (evening session).…”
Section: Cta Following Amn082mentioning
confidence: 99%
“…Individual shRNA constructs were generated as described previously. Targeting sequences were selected based on RNAi Codex algorithms (16) or BIOPREDsi design (42) and are available upon request.…”
Section: Methodsmentioning
confidence: 99%
“…The algorithm uses a neuronal network approach to design the siRNAs (21) and discards those sequences with high similarity to regions of other genes. Areas of the target sequence with known single nucleotide polymorphisms were avoided.…”
Section: Methodsmentioning
confidence: 99%