Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 1 to 12 of 105 entries
Sorted by: Best Match Show Resources per page
Using shRNA experiments to validate gene regulatory networks.

Genomics data

Olsen C, Fleming K, Prendergast N, Rubio R, Emmert-Streib F, Bontempi G, Quackenbush J, Haibe-Kains B.
PMID: 26484195
Genom Data. 2015 Apr 01;4:123-6. doi: 10.1016/j.gdata.2015.03.011. eCollection 2015 Jun.

Quantitative validation of gene regulatory networks (GRNs) inferred from observational expression data is a difficult task usually involving time intensive and costly laboratory experiments. We were able to show that gene knock-down experiments can be used to quantitatively assess...

Cite
Olsen C, Fleming K, Prendergast N, et al. Using shRNA experiments to validate gene regulatory networks. Genom Data. 2015;4:123-6doi: 10.1016/j.gdata.2015.03.011.
Olsen, C., Fleming, K., Prendergast, N., Rubio, R., Emmert-Streib, F., Bontempi, G., Quackenbush, J., & Haibe-Kains, B. (2015). Using shRNA experiments to validate gene regulatory networks. Genomics data, 4123-6. https://doi.org/10.1016/j.gdata.2015.03.011
Olsen, Catharina, et al. "Using shRNA experiments to validate gene regulatory networks." Genomics data vol. 4 (2015): 123-6. doi: https://doi.org/10.1016/j.gdata.2015.03.011
Olsen C, Fleming K, Prendergast N, Rubio R, Emmert-Streib F, Bontempi G, Quackenbush J, Haibe-Kains B. Using shRNA experiments to validate gene regulatory networks. Genom Data. 2015 Apr 01;4:123-6. doi: 10.1016/j.gdata.2015.03.011. eCollection 2015 Jun. PMID: 26484195; PMCID: PMC4535466.
Copy Download .nbib Format: NLM
Revisiting inconsistency in large pharmacogenomic studies.

F1000Research

Safikhani Z, Smirnov P, Freeman M, El-Hachem N, She A, Rene Q, Goldenberg A, Birkbak NJ, Hatzis C, Shi L, Beck AH, Aerts HJWL, Quackenbush J, Haibe-Kains B.
PMID: 28928933
F1000Res. 2016 Sep 16;5:2333. doi: 10.12688/f1000research.9611.3. eCollection 2016.

In 2013, we published a comparative analysis of mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer...

Cite
Safikhani Z, Smirnov P, Freeman M, et al. Revisiting inconsistency in large pharmacogenomic studies. F1000Res. 2016;5:2333doi: 10.12688/f1000research.9611.3.
Safikhani, Z., Smirnov, P., Freeman, M., El-Hachem, N., She, A., Rene, Q., Goldenberg, A., Birkbak, N. J., Hatzis, C., Shi, L., Beck, A. H., Aerts, H. J. W. L., Quackenbush, J., & Haibe-Kains, B. (2016). Revisiting inconsistency in large pharmacogenomic studies. F1000Research, 52333. https://doi.org/10.12688/f1000research.9611.3
Safikhani, Zhaleh, et al. "Revisiting inconsistency in large pharmacogenomic studies." F1000Research vol. 5 (2016): 2333. doi: https://doi.org/10.12688/f1000research.9611.3
Safikhani Z, Smirnov P, Freeman M, El-Hachem N, She A, Rene Q, Goldenberg A, Birkbak NJ, Hatzis C, Shi L, Beck AH, Aerts HJWL, Quackenbush J, Haibe-Kains B. Revisiting inconsistency in large pharmacogenomic studies. F1000Res. 2016 Sep 16;5:2333. doi: 10.12688/f1000research.9611.3. eCollection 2016. PMID: 28928933; PMCID: PMC5580432.
Copy Download .nbib Format: NLM
Assessment of pharmacogenomic agreement.

F1000Research

Safikhani Z, El-Hachem N, Quevedo R, Smirnov P, Goldenberg A, Juul Birkbak N, Mason C, Hatzis C, Shi L, Aerts HJ, Quackenbush J, Haibe-Kains B.
PMID: 27408686
F1000Res. 2016 May 09;5:825. doi: 10.12688/f1000research.8705.1. eCollection 2016.

In 2013 we published an analysis demonstrating that drug response data and gene-drug associations reported in two independent large-scale pharmacogenomic screens, Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE), were inconsistent. The GDSC and...

Cite
Safikhani Z, El-Hachem N, Quevedo R, et al. Assessment of pharmacogenomic agreement. F1000Res. 2016;5:825doi: 10.12688/f1000research.8705.1.
Safikhani, Z., El-Hachem, N., Quevedo, R., Smirnov, P., Goldenberg, A., Juul Birkbak, N., Mason, C., Hatzis, C., Shi, L., Aerts, H. J., Quackenbush, J., & Haibe-Kains, B. (2016). Assessment of pharmacogenomic agreement. F1000Research, 5825. https://doi.org/10.12688/f1000research.8705.1
Safikhani, Zhaleh, et al. "Assessment of pharmacogenomic agreement." F1000Research vol. 5 (2016): 825. doi: https://doi.org/10.12688/f1000research.8705.1
Safikhani Z, El-Hachem N, Quevedo R, Smirnov P, Goldenberg A, Juul Birkbak N, Mason C, Hatzis C, Shi L, Aerts HJ, Quackenbush J, Haibe-Kains B. Assessment of pharmacogenomic agreement. F1000Res. 2016 May 09;5:825. doi: 10.12688/f1000research.8705.1. eCollection 2016. PMID: 27408686; PMCID: PMC4926729.
Copy Download .nbib Format: NLM
Estimating gene regulatory networks with pandaR.

Bioinformatics (Oxford, England)

Schlauch D, Paulson JN, Young A, Glass K, Quackenbush J.
PMID: 28334344
Bioinformatics. 2017 Jul 15;33(14):2232-2234. doi: 10.1093/bioinformatics/btx139.

CONTACT: [email protected] or [email protected] AND IMPLEMENTATION: PandaR is provided as a Bioconductor R Package and is available at bioconductor.org/packages/pandaR.

Cite
Schlauch D, Paulson JN, Young A, et al. Estimating gene regulatory networks with pandaR. Bioinformatics. 2017;33(14):2232-2234doi: 10.1093/bioinformatics/btx139.
Schlauch, D., Paulson, J. N., Young, A., Glass, K., & Quackenbush, J. (2017). Estimating gene regulatory networks with pandaR. Bioinformatics (Oxford, England), 33(14), 2232-2234. https://doi.org/10.1093/bioinformatics/btx139
Schlauch, Daniel, et al. "Estimating gene regulatory networks with pandaR." Bioinformatics (Oxford, England) vol. 33,14 (2017): 2232-2234. doi: https://doi.org/10.1093/bioinformatics/btx139
Schlauch D, Paulson JN, Young A, Glass K, Quackenbush J. Estimating gene regulatory networks with pandaR. Bioinformatics. 2017 Jul 15;33(14):2232-2234. doi: 10.1093/bioinformatics/btx139. PMID: 28334344; PMCID: PMC5870629.
Copy Download .nbib Format: NLM
Mechanism of suckling-rat hypercholesteremia. II. Cholesterol biosynthesis and cholic acid turnover studies.

Lipids

Harris RA, Rivera ER, Villemez CL, Quackenbush FW.
PMID: 17805740
Lipids. 1967 Mar;2(2):137-42. doi: 10.1007/BF02530913.

Cholesterol biosynthesis from acetate-2-(14)C by the livers of suckling rats, which is known to be relatively slow, was increased 2-3-fold within 24 hours after severing the bile duct. Cholesterol synthesis by sham-operated litter mates showed no change under similar...

Cite
Harris RA, Rivera ER, Villemez CL, et al. Mechanism of suckling-rat hypercholesteremia. II. Cholesterol biosynthesis and cholic acid turnover studies. Lipids. 1967;2(2):137-42doi: 10.1007/BF02530913.
Harris, R. A., Rivera, E. R., Villemez, C. L., & Quackenbush, F. W. (1967). Mechanism of suckling-rat hypercholesteremia. II. Cholesterol biosynthesis and cholic acid turnover studies. Lipids, 2(2), 137-42. https://doi.org/10.1007/BF02530913
Harris, R A, et al. "Mechanism of suckling-rat hypercholesteremia. II. Cholesterol biosynthesis and cholic acid turnover studies." Lipids vol. 2,2 (1967): 137-42. doi: https://doi.org/10.1007/BF02530913
Harris RA, Rivera ER, Villemez CL, Quackenbush FW. Mechanism of suckling-rat hypercholesteremia. II. Cholesterol biosynthesis and cholic acid turnover studies. Lipids. 1967 Mar;2(2):137-42. doi: 10.1007/BF02530913. PMID: 17805740.
Copy Download .nbib Format: NLM
Reduction of atherogenicity of natural fats by small additions of ethyl linoleate in the diet of the rat.

Lipids

Hutsell TC, Quackenbush FW.
PMID: 17805763
Lipids. 1967 Jul;2(4):342-4. doi: 10.1007/BF02532123.

Ethyl linoleate was substituted in part for the 20% of butterfat, hydrogenated coconut oil, lard, or tallow in an atherogenic diet fed to rats throughout a 40-week experimental period. Aortic degeneration, evidenced by lipid infiltration of the intima, was...

Cite
Hutsell TC, Quackenbush FW. Reduction of atherogenicity of natural fats by small additions of ethyl linoleate in the diet of the rat. Lipids. 1967;2(4):342-4doi: 10.1007/BF02532123.
Hutsell, T. C., & Quackenbush, F. W. (1967). Reduction of atherogenicity of natural fats by small additions of ethyl linoleate in the diet of the rat. Lipids, 2(4), 342-4. https://doi.org/10.1007/BF02532123
Hutsell, T C, and Quackenbush, F W. "Reduction of atherogenicity of natural fats by small additions of ethyl linoleate in the diet of the rat." Lipids vol. 2,4 (1967): 342-4. doi: https://doi.org/10.1007/BF02532123
Hutsell TC, Quackenbush FW. Reduction of atherogenicity of natural fats by small additions of ethyl linoleate in the diet of the rat. Lipids. 1967 Jul;2(4):342-4. doi: 10.1007/BF02532123. PMID: 17805763.
Copy Download .nbib Format: NLM
The Inheritance of Carotenoid Pigment Systems in the Tomato.

Genetics

Tomes ML, Quackenbush FW, Nelson OE, North B.
PMID: 17247427
Genetics. 1953 Mar;38(2):117-27. doi: 10.1093/genetics/38.2.117.

No abstract available.

Cite
Tomes ML, Quackenbush FW, Nelson OE, et al. The Inheritance of Carotenoid Pigment Systems in the Tomato. Genetics. 1953;38(2):117-27doi: 10.1093/genetics/38.2.117.
Tomes, M. L., Quackenbush, F. W., Nelson, O. E., & North, B. (1953). The Inheritance of Carotenoid Pigment Systems in the Tomato. Genetics, 38(2), 117-27. https://doi.org/10.1093/genetics/38.2.117
Tomes, M L, et al. "The Inheritance of Carotenoid Pigment Systems in the Tomato." Genetics vol. 38,2 (1953): 117-27. doi: https://doi.org/10.1093/genetics/38.2.117
Tomes ML, Quackenbush FW, Nelson OE, North B. The Inheritance of Carotenoid Pigment Systems in the Tomato. Genetics. 1953 Mar;38(2):117-27. doi: 10.1093/genetics/38.2.117. PMID: 17247427; PMCID: PMC1209592.
Copy Download .nbib Format: NLM
Career issues.

Science (New York, N.Y.)

Quackenbush J.
PMID: 17772824
Science. 1994 Nov 25;266(5189):1306. doi: 10.1126/science.266.5189.1306.

No abstract available.

Cite
Quackenbush J. Career issues. Science. 1994;266(5189):1306doi: 10.1126/science.266.5189.1306.
Quackenbush, J. (1994). Career issues. Science (New York, N.Y.), 266(5189), 1306. https://doi.org/10.1126/science.266.5189.1306
Quackenbush, J. "Career issues." Science (New York, N.Y.) vol. 266,5189 (1994): 1306. doi: https://doi.org/10.1126/science.266.5189.1306
Quackenbush J. Career issues. Science. 1994 Nov 25;266(5189):1306. doi: 10.1126/science.266.5189.1306. PMID: 17772824.
Copy Download .nbib Format: NLM
Weighing our measures of gene expression.

Molecular systems biology

Quackenbush J.
PMID: 17102808
Mol Syst Biol. 2006;2:63. doi: 10.1038/msb4100096. Epub 2006 Nov 14.

No abstract available.

Cite
Quackenbush J. Weighing our measures of gene expression. Mol Syst Biol. 2006;2:63doi: 10.1038/msb4100096.
Quackenbush, J. (2006). Weighing our measures of gene expression. Molecular systems biology, 263. https://doi.org/10.1038/msb4100096
Quackenbush, John. "Weighing our measures of gene expression." Molecular systems biology vol. 2 (2006): 63. doi: https://doi.org/10.1038/msb4100096
Quackenbush J. Weighing our measures of gene expression. Mol Syst Biol. 2006;2:63. doi: 10.1038/msb4100096. Epub 2006 Nov 14. PMID: 17102808; PMCID: PMC1682020.
Copy Download .nbib Format: NLM
Walleye dermal sarcoma virus: molecular biology and oncogenesis.

Viruses

Rovnak J, Quackenbush SL.
PMID: 21994717
Viruses. 2010 Sep;2(9):1984-99. doi: 10.3390/v2091984. Epub 2010 Sep 22.

Retroviruses have been detected in most vertebrate species and are etiologic agents of a variety of neoplastic diseases. The study of retroviruses has been instrumental in uncovering the molecular mechanisms responsible for oncogenesis. Retroviruses have been isolated from three...

Cite
Rovnak J, Quackenbush SL. Walleye dermal sarcoma virus: molecular biology and oncogenesis. Viruses. 2010;2(9):1984-99doi: 10.3390/v2091984.
Rovnak, J., & Quackenbush, S. L. (2010). Walleye dermal sarcoma virus: molecular biology and oncogenesis. Viruses, 2(9), 1984-99. https://doi.org/10.3390/v2091984
Rovnak, Joel, and Quackenbush, Sandra L. "Walleye dermal sarcoma virus: molecular biology and oncogenesis." Viruses vol. 2,9 (2010): 1984-99. doi: https://doi.org/10.3390/v2091984
Rovnak J, Quackenbush SL. Walleye dermal sarcoma virus: molecular biology and oncogenesis. Viruses. 2010 Sep;2(9):1984-99. doi: 10.3390/v2091984. Epub 2010 Sep 22. PMID: 21994717; PMCID: PMC3185748.
Copy Download .nbib Format: NLM
The kinetic requirements of extreme qPCR.

Biomolecular detection and quantification

Millington AL, Houskeeper JA, Quackenbush JF, Trauba JM, Wittwer CT.
PMID: 31285997
Biomol Detect Quantif. 2019 Mar 13;17:100081. doi: 10.1016/j.bdq.2019.100081. eCollection 2019 Mar.

The kinetic requirements of quantitative PCR were experimentally dissected into the stages of DNA denaturation, primer annealing, and polymerase extension. The temperature/time conditions for 2 stages were kept optimal, while the other was limited until the amplification efficiency decreased...

Cite
Millington AL, Houskeeper JA, Quackenbush JF, et al. The kinetic requirements of extreme qPCR. Biomol Detect Quantif. 2019;17:100081doi: 10.1016/j.bdq.2019.100081.
Millington, A. L., Houskeeper, J. A., Quackenbush, J. F., Trauba, J. M., & Wittwer, C. T. (2019). The kinetic requirements of extreme qPCR. Biomolecular detection and quantification, 17100081. https://doi.org/10.1016/j.bdq.2019.100081
Millington, Adam L, et al. "The kinetic requirements of extreme qPCR." Biomolecular detection and quantification vol. 17 (2019): 100081. doi: https://doi.org/10.1016/j.bdq.2019.100081
Millington AL, Houskeeper JA, Quackenbush JF, Trauba JM, Wittwer CT. The kinetic requirements of extreme qPCR. Biomol Detect Quantif. 2019 Mar 13;17:100081. doi: 10.1016/j.bdq.2019.100081. eCollection 2019 Mar. PMID: 31285997; PMCID: PMC6591793.
Copy Download .nbib Format: NLM
Detecting phenotype-driven transitions in regulatory network structure.

NPJ systems biology and applications

Padi M, Quackenbush J.
PMID: 29707235
NPJ Syst Biol Appl. 2018 Apr 19;4:16. doi: 10.1038/s41540-018-0052-5. eCollection 2018.

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular...

Cite
Padi M, Quackenbush J. Detecting phenotype-driven transitions in regulatory network structure. NPJ Syst Biol Appl. 2018;4:16doi: 10.1038/s41540-018-0052-5.
Padi, M., & Quackenbush, J. (2018). Detecting phenotype-driven transitions in regulatory network structure. NPJ systems biology and applications, 416. https://doi.org/10.1038/s41540-018-0052-5
Padi, Megha, and Quackenbush, John. "Detecting phenotype-driven transitions in regulatory network structure." NPJ systems biology and applications vol. 4 (2018): 16. doi: https://doi.org/10.1038/s41540-018-0052-5
Padi M, Quackenbush J. Detecting phenotype-driven transitions in regulatory network structure. NPJ Syst Biol Appl. 2018 Apr 19;4:16. doi: 10.1038/s41540-018-0052-5. eCollection 2018. PMID: 29707235; PMCID: PMC5908977.
Copy Download .nbib Format: NLM
Showing 1 to 12 of 105 entries