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Showing 49 to 52 of 52 entries
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NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis.

Nucleic acids research

Zhou G, Soufan O, Ewald J, Hancock REW, Basu N, Xia J.
PMID: 30931480
Nucleic Acids Res. 2019 Jul 02;47:W234-W241. doi: 10.1093/nar/gkz240.

The growing application of gene expression profiling demands powerful yet user-friendly bioinformatics tools to support systems-level data understanding. NetworkAnalyst was first released in 2014 to address the key need for interpreting gene expression data within the context of protein-protein...

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Zhou G, Soufan O, Ewald J, et al. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res. 2019;47:W234-W241doi: 10.1093/nar/gkz240.
Zhou, G., Soufan, O., Ewald, J., Hancock, R. E. W., Basu, N., & Xia, J. (2019). NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic acids research, 47W234-W241. https://doi.org/10.1093/nar/gkz240
Zhou, Guangyan, et al. "NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis." Nucleic acids research vol. 47 (2019): W234-W241. doi: https://doi.org/10.1093/nar/gkz240
Zhou G, Soufan O, Ewald J, Hancock REW, Basu N, Xia J. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res. 2019 Jul 02;47:W234-W241. doi: 10.1093/nar/gkz240. PMID: 30931480; PMCID: PMC6602507.
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ROC'n'Ribo: Characterizing a Riboswitching Expression System by Modeling Single-Cell Data.

ACS synthetic biology

Schneider C, Bronstein L, Diemer J, Koeppl H, Suess B.
PMID: 28591515
ACS Synth Biol. 2017 Jul 21;6(7):1211-1224. doi: 10.1021/acssynbio.6b00322. Epub 2017 Jun 30.

RNA-engineered systems offer simple and versatile control over gene expression in many organisms. In particular, the design and implementation of riboswitches presents a unique opportunity to manipulate any reporter device in cis, executing tight temporal and spatial control at...

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Schneider C, Bronstein L, Diemer J, et al. ROC'n'Ribo: Characterizing a Riboswitching Expression System by Modeling Single-Cell Data. ACS Synth Biol. 2017;6(7):1211-1224doi: 10.1021/acssynbio.6b00322.
Schneider, C., Bronstein, L., Diemer, J., Koeppl, H., & Suess, B. (2017). ROC'n'Ribo: Characterizing a Riboswitching Expression System by Modeling Single-Cell Data. ACS synthetic biology, 6(7), 1211-1224. https://doi.org/10.1021/acssynbio.6b00322
Schneider, Christopher, et al. "ROC'n'Ribo: Characterizing a Riboswitching Expression System by Modeling Single-Cell Data." ACS synthetic biology vol. 6,7 (2017): 1211-1224. doi: https://doi.org/10.1021/acssynbio.6b00322
Schneider C, Bronstein L, Diemer J, Koeppl H, Suess B. ROC'n'Ribo: Characterizing a Riboswitching Expression System by Modeling Single-Cell Data. ACS Synth Biol. 2017 Jul 21;6(7):1211-1224. doi: 10.1021/acssynbio.6b00322. Epub 2017 Jun 30. PMID: 28591515.
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DrugSig: A resource for computational drug repositioning utilizing gene expression signatures.

PloS one

Wu H, Huang J, Zhong Y, Huang Q.
PMID: 28562632
PLoS One. 2017 May 31;12(5):e0177743. doi: 10.1371/journal.pone.0177743. eCollection 2017.

Computational drug repositioning has been proved as an effective approach to develop new drug uses. However, currently existing strategies strongly rely on drug response gene signatures which scattered in separated or individual experimental data, and resulted in low efficient...

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Wu H, Huang J, Zhong Y, et al. DrugSig: A resource for computational drug repositioning utilizing gene expression signatures. PLoS One. 2017;12(5):e0177743doi: 10.1371/journal.pone.0177743.
Wu, H., Huang, J., Zhong, Y., & Huang, Q. (2017). DrugSig: A resource for computational drug repositioning utilizing gene expression signatures. PloS one, 12(5), e0177743. https://doi.org/10.1371/journal.pone.0177743
Wu, Hongyu, et al. "DrugSig: A resource for computational drug repositioning utilizing gene expression signatures." PloS one vol. 12,5 (2017): e0177743. doi: https://doi.org/10.1371/journal.pone.0177743
Wu H, Huang J, Zhong Y, Huang Q. DrugSig: A resource for computational drug repositioning utilizing gene expression signatures. PLoS One. 2017 May 31;12(5):e0177743. doi: 10.1371/journal.pone.0177743. eCollection 2017. PMID: 28562632; PMCID: PMC5451001.
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A Fokker-Planck approach to the study of robustness in gene expression.

Mathematical biosciences and engineering : MBE

Degond P, Herda M, Mirrahimi S.
PMID: 33378862
Math Biosci Eng. 2020 Sep 24;17(6):6459-6486. doi: 10.3934/mbe.2020338.

We study several Fokker-Planck equations arising from a stochastic chemical kinetic system modeling a gene regulatory network in biology. The densities solving the Fokker-Planck equations describe the joint distribution of the mRNA and

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Degond P, Herda M, Mirrahimi S. A Fokker-Planck approach to the study of robustness in gene expression. Math Biosci Eng. 2020;17(6):6459-6486doi: 10.3934/mbe.2020338.
Degond, P., Herda, M., & Mirrahimi, S. (2020). A Fokker-Planck approach to the study of robustness in gene expression. Mathematical biosciences and engineering : MBE, 17(6), 6459-6486. https://doi.org/10.3934/mbe.2020338
Degond, Pierre, et al. "A Fokker-Planck approach to the study of robustness in gene expression." Mathematical biosciences and engineering : MBE vol. 17,6 (2020): 6459-6486. doi: https://doi.org/10.3934/mbe.2020338
Degond P, Herda M, Mirrahimi S. A Fokker-Planck approach to the study of robustness in gene expression. Math Biosci Eng. 2020 Sep 24;17(6):6459-6486. doi: 10.3934/mbe.2020338. PMID: 33378862.
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Showing 49 to 52 of 52 entries