Journal of Proteomics & Bioinformatics
Open Access

International Conference on Omics Studies

September 04-05, 2013 Holiday Inn Orlando International Airport, Orlando, FL, USA

Accepted Abstracts

• Therapeutic monitoring of amphotericin B in Saudi ICU patients using HUPLC MS/MS assay

  Al-Quadeib and Bushra

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• Comparative proteomics of dehydration-responsive changes in the nucleus reveals genotypespecific adaptation

  Doel Ray, Asis Datta, Subhra Chakraborty and Niranjan Chakraborty

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• Bioinformatics analysis of NGS data - current applications on biomedical research

  Jorge Andrade

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• PWCT - Pan-Cellular Whole-organism MicroCT as a foundation for computational phenomics

  Keith C. Cheng

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• N-glycan cryptic sugar moieties as potential biomarkers of aggressive prostate cancer

  Denong Wang

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• “Characterization of 3’ untranslated regions for optimization of gene expression in yeast”

  Nebeyu Yosef

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• In-Silico combination of docking, QM/MM analysis and MD simulations for tetrahydrobiopterin analogous: Binding towards non-heme active site of phenylalanine hydroxylase and a313t mutant type for neurological cascades

  Nidhi Chadha1, 2, Anjani Kumar Tiwari1, Marilyn Daisy Milton2 and Anil Kumar Mishra1

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• Molecular dissection of flavonoid biosynthetic pathway in a nutraceutical food crop (Fagopyrum spp.)

  Nidhi Gupta and Rajinder S Chauhan

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• Multiplexed proteomics using ultra dielectrophoresis (uDEP)

  Sam Emaminejad, Mehdi Javanmard, Robert W. Dutton and Ronald W. Davis

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• PostGWAS knowledge miner- An integrative resource for cardiovascular post-GWAS research

  Seraya Maouche

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• Predicting synergistic drug targets in cancer through molecular networks

  Uma Shankavaram and Kevin Camphausen

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• The use of multi-parameter systematic strategies to predict, prevent, and personalized treatment for cancer

  Xianquan Zhan

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• MicroRNA and messenger RNA profiling reveals new biomarkers and mechanisms for rdx induced neurotoxicity

  Youping Deng, Junmei Ai, Xin Guan, Zhaohui Wang and Edward J. Perkins

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• Three meta-analyses define a set of commonly overexpressed genes from microarray datasets on astrocytomas

  Zhongyu Liu

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