For Libraries For Publication Open Access Downloads About Us Contact Us
Paper Titles
An Efficient Site-Directed Mutagenesis Method In Vivo in Escherichia Coli
p.407
Enzymatic Synthesis of Ferulyl Oleins and their Inhibition Effects on Nitrosamine
p.412
Evaluation of Causal Influences in Model of Motor Control in Left Hands Movement-Readiness State
p.418
The Influence of UVB Radiation on Proliferation and Youngs Modulus of Dermal Fibroblasts
p.424
Mining the Bioinformation of Differentially Expressed Genes in Obese Mice Treated with Chronic Intermittent Hypoxia Based on the Bioinformatics Methods
p.429
Protein Folding Prediction Based on Levy Flight Particle Swarm Optimization
p.435
Freeze-Drying Investigations of Antlers
p.441
The Changes of Tissue-Type Plasminogen Activator and Matrix Metalloproteinases in Neonatal Mice with Hypoxic-Ischemic Encephalopathy
p.447
DNA Vaccines Co-Expressing Containing Hsp70 and GP5/M Protein of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) Display Enhanced Immunogenicity
p.452

Mining the Bioinformation of Differentially Expressed Genes in Obese Mice Treated with Chronic Intermittent Hypoxia Based on the Bioinformatics Methods

Article Preview

Abstract:

Objective: To analyze the differentially expressed genes expressed genes in obese mice that treated with chronic intermittent hypoxia (CIH) for getting better understanding of the molecular characteristics in the obese mice caused by CIH. Methods: Got the microarray hybridization data from the Gene Expression Omnibus (GEO) database. Identified the differentially expressed genes expressed genes in CIH obese mice and the patterns of their regulation using public bioinformatics software and database, such as BRB-Arraytools, Genecodis and DAVID, KEGG. Results and Conclusion: We found the Peroxisome proliferator activated receptors (PPARs) pathway involved in the down-regulated genes. These data mining findings between room air and CIH mice by bioinformatics methods could provide better understanding of the molecular activity change in obese caused by CIH.

You might also be interested in these eBooks
Mechanical Engineering and Intelligent Systems View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 195-196)

Pages:

429-434

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.195-196.429

Citation:

Cite this paper

Online since:

August 2012

Authors:

De Bi, Hua Jun Xiao, Cui Hong Zhou, Jun Zhou

Keywords:

Bioinformatics, Data Mining (DM), Database, Gene, Hypoxia, Obese

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] Tanya Barrett, Dennis B. Troup, Stephen E. Wilhite, Pierre Ledoux, Dmitry Rudnev, et al. NCBI GEO: mining tens of millions of expression profiles-database and tools update. Nucleic Acids Research, vol. 35, pp.760-765, (2007).

DOI: 10.1093/nar/gkl887

Google Scholar

[2] Tanya Barrett, Dennis B. Troup, Stephen E. Wilhite, Pierre Ledoux, Dmitry Rudnev. NCBI GEO: archive for high-throughput functional genomic data. Nucleic Acids Research, Vol. 37, pp.885-890, (2009).

DOI: 10.1093/nar/gkn764

Google Scholar

[3] Ron Edgar and Tanya Barrett. NCBI GEO standards and services for microarray data. Nat Biotechnol, vol. 24(12), pp.1471-1472, (2006).

DOI: 10.1038/nbt1206-1471

Google Scholar

[4] Tanya Barrett and Ron Edgar. Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval, and analysis. Methods Enzymol, vol. 411, pp: 352-369, (2006).

DOI: 10.1016/s0076-6879(06)11019-8

Google Scholar

[5] Khoi Q. Tran, Deborah A. Swartz-Basile, Attila Nakeeb, and Henry A. Pitt. Gallbladder Motility in Agouti-Yellow and Leptin-Resistant Obese Mice. Journal of Surgical Research, vol. 113, pp: 56-61, (2003).

DOI: 10.1016/s0022-4804(03)00157-4

Google Scholar

[6] Akio Inui. Feeding and body-weight regulation by hypothalamic neuropeptides-mediation of the actions of leptin. Trends Neurosci, vol. 22, pp: 62-67, (1999).

DOI: 10.1016/s0166-2236(98)01292-2

Google Scholar

[7] M. Friedman-Einata, L. Camoinb, Z. Faltinc, C.I. Rosenblumd,V. Kalioutaa, et al. Serum leptin activity in obese and lean patients, Regulatory Peptides , vol. 111, pp: 77-82, (2003).

DOI: 10.1016/s0167-0115(02)00259-8

Google Scholar

[8] Considine RV, Sinha K, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR, et al. Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med, vol. 334, pp: 292-295, (1996).

DOI: 10.1056/nejm199602013340503

Google Scholar

[9] Alexandra Grosfeld, Jocelyne Andre , Sylvie Hauguel-de Mouzon , Edurne Berra, Jacques Pouysse gur , and Michele Guerre-Millo. ypoxia-inducible Factor 1 Transactivates the Human Leptin Gene Promoter. The Journal of Biological Chemistry, vol. 277, p.42953–42957, (2002).

DOI: 10.1074/jbc.m206775200

Google Scholar

[10] Wang GL, Jiang B-H, Rue EA, Semenza GL. Hypoxia-inducible factor 1 is a basic-helix-loop-helix-PAS heterodimer regulated by cellular O2 tension. Proc Natl Acad Sci , vol. 92, pp: 5510-5514, (1995).

DOI: 10.1073/pnas.92.12.5510

Google Scholar

[11] Jiang B-H, Semenza GL, Bauer C, Marti HH. Hypoxia-inducible factor 1 levels vary exponentially over a physiologically relevant range of O2 tension. Am J Physiol, vol. 271, pp: 1172-1180, (1996).

DOI: 10.1152/ajpcell.1996.271.4.c1172

Google Scholar

[12] Gregg L Semenza. HIF-1 and mechanisms of hypoxia sensing. Current Opinion in Cell Biology, vol. 13, pp: 167-171, (2001).

DOI: 10.1016/s0955-0674(00)00194-0

Google Scholar

[13] Jianguo Li, Dmitry N. Grigoryev, Shui Qing Ye, Laura Thorne, Alan R. Schwartz, et al. Chronic intermittent hypoxia upregulates genes of lipid biosynthesis in obese mice. J Appl Physio, vol. 99, pp: 1643-1648, (2005).

DOI: 10.1152/japplphysiol.00522.2005

Google Scholar

[14] Zhao Y and Simon R. BRB ArrayTools Data Archive for Human Cancer Gene Expression: A Unique and Efficient Data Sharing Resource. Cancer Informatics, vol. 6, pp: 9-15, (2008).

DOI: 10.4137/cin.s448

Google Scholar

[15] Nogales-Cadenas R, Carmona-Saez P, Vazquez M, Vicente C, Yang X, Tirado F, Carazo JM, Pascual-Montano A: GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information. Nucleic Acids Research, vol. 37(Web Server issue): W317-22. (2009).

DOI: 10.1093/nar/gkp416

Google Scholar

[16] Carmona-Saez P, Chagoyen M, Tirado F, Carazo JM, Pascual-Montano A: GENECODIS: A web-based tool for finding significant concurrent annotations in gene lists. Genome Biology, 8(1): R3 , (2007).

DOI: 10.1186/gb-2007-8-1-r3

Google Scholar

[17] Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protoc, vol4(1), pp: 44-45, (2009).

DOI: 10.1038/nprot.2008.211

Google Scholar

[18] Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA.  DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol, vol. 4(5), p.3, (2003).

DOI: 10.1186/gb-2003-4-9-r60

Google Scholar

[19] Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., and Hirakawa, M.; KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res, vol. 38, pp: 355-360, (2010).

DOI: 10.1093/nar/gkp896

Google Scholar

[20] Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., and Hirakawa, M.; From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res, vol. 34, pp.354-357, (2006).

DOI: 10.1093/nar/gkj102

Google Scholar

[21] Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res, vol. 28, pp: 27-30, (2000).

DOI: 10.1093/nar/28.1.27

Google Scholar

[22] Mangelsdorf DJ, Evans RM. The RXR heterodimers and orphan receptors. Cell, vol. 83, pp: 841-850, (1995).

DOI: 10.1016/0092-8674(95)90200-7

Google Scholar

[23] Timothy M Willson and Walter Wahlit. Peroxisome proliferator-activated receptor agonists. Current Opinion in Chemical Biology, vol. 1, pp: 235-241, (1997).

DOI: 10.1016/s1367-5931(97)80015-4

Google Scholar

[24] Liang Guo, Reza Tabrizchi. Peroxisome proliferator-activated receptor gamma as a drug target in the pathogenesis of insulin resistance. Pharmacology & Therapeutics, vol. 111, pp: 145 -173, (2006).

DOI: 10.1016/j.pharmthera.2005.10.009

Google Scholar

[25] P. Escher, W. Wahli. Peroxisome proliferator-activated receptors: insight into multiple cellular functions. Mutat. Res, vol. 448, pp: 121-138, (2000).

DOI: 10.1016/s0027-5107(99)00231-6

Google Scholar

[26] Yajun Zhou, Xin Jia, Mingming Zhou, Jie Liu. Egr-1 is involved in the inhibitory effect of leptin on PPARγ expression in hepatic stellate cell in vitro. Life Sciences, vol. 84 544-551, (2009).

DOI: 10.1016/j.lfs.2009.01.018

Google Scholar

[27] Alexandra Grosfelda, Sophie Turbana, Jocelyne Andre, Michele Cauzac, et al. Transcriptional eject of hypoxia on placental leptin. FEBS Letters, vol. 502, pp: 122-126, (2001).

DOI: 10.1016/s0014-5793(01)02673-4

Google Scholar

[28] Sander Kersten. Peroxisome proliferator activated receptors and obesity. European Journal of Pharmacology, vol. 440, pp: 223-234, (2002).

DOI: 10.1016/s0014-2999(02)01431-0

Google Scholar

[29] Seth S. Martin, Atif Qasim, Muredach P. Reilly. Leptin Resistance: A Possible Interface of Inflammationand Metabolism in Obesity-Related Cardiovascular Disease. Journal of the American College of Cardiology, Vol. 52, pp: 1201-1210, (2008).

DOI: 10.1016/j.jacc.2008.05.060

Google Scholar

© 2025 Trans Tech Publications Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For open access content, terms of the Creative Commons licensing CC-BY are applied.
Scientific.Net is a registered trademark of Trans Tech Publications Ltd.