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Full-Text Articles in Biomedical Engineering and Bioengineering

Reconstructing Genome-Wide Regulatory Network Of E. Coli Using Transcriptome Data And Predicted Transcription Factor Activities, Yao Fu, Laura R. Jarboe, Julie A. Dickerson Jun 2011

Reconstructing Genome-Wide Regulatory Network Of E. Coli Using Transcriptome Data And Predicted Transcription Factor Activities, Yao Fu, Laura R. Jarboe, Julie A. Dickerson

Chemical and Biological Engineering Publications

Background: Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Understanding the connections and the activity levels of regulators is important for the research of gene regulatory networks. While relevance score based algorithms that reconstruct gene regulatory networks from transcriptome data can infer genome-wide gene regulatory networks, they are unfortunately prone to false positive results. Transcription factor activities (TFAs) quantitatively reflect the ability of the transcription factor to regulate target genes. However, classic relevance score based gene regulatory network reconstruction algorithms use models do not include the ...


Engineering Ethanologenic Escherichia Coli For Levoglucosan Utilization, Donovan S. Layton, Avanthi Ajjarapu, Dong Won Choi, Laura R. Jarboe Jan 2011

Engineering Ethanologenic Escherichia Coli For Levoglucosan Utilization, Donovan S. Layton, Avanthi Ajjarapu, Dong Won Choi, Laura R. Jarboe

Chemical and Biological Engineering Publications

Levoglucosan is a major product of biomass pyrolysis. While this pyrolyzed biomass, also known as bio-oil, contains sugars that are an attractive fermentation substrate, commonly-used biocatalysts, such as Escherichia coli, lack the ability to metabolize this anhydrosugar. It has previously been shown that recombinant expression of the levoglucosan kinase enzyme enables use of levoglucosan as carbon and energy source. Here, ethanologenic E. coli KO11 was engineered for levoglucosan utilization by recombinant expression of levoglucosan kinase from Lipomyces starkeyi. Our engineering strategy uses a codon-optimized gene that has been chromosomally integrated within the pyruvate to ethanol (PET) operon and does not ...


An Extended Data Mining Method For Identifying Differentially Expressed Assay-Specific Signatures In Functional Genomic Studies, Derrick K. Rollins Sr., Ai-Ling Teh Jan 2010

An Extended Data Mining Method For Identifying Differentially Expressed Assay-Specific Signatures In Functional Genomic Studies, Derrick K. Rollins Sr., Ai-Ling Teh

Chemical and Biological Engineering Publications

Background: Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and ...


Unleashing Biocatalysis/Chemical Catalysis Synergies For Efficient Biomass Conversion, Brent H. Shanks Jan 2007

Unleashing Biocatalysis/Chemical Catalysis Synergies For Efficient Biomass Conversion, Brent H. Shanks

Chemical and Biological Engineering Publications

The goal of incorporating renewable carbon into the fuel and chemical enterprise will most likely be successful when combined systems of biocatalysts and chemical catalysts are exploited. Significant efforts in the biocatalytic release of sugars from biomass are being pursued for subsequent use in fermentation. Two recent papers demonstrate an alternative approach to converting these sugars to a liquid fuel by using chemical catalysts.


A Novel Data Mining Method To Identify Assay-Specific Signatures In Functional Genomic Studies, Derrick K. Rollins Sr., Dongmei Zhai, Alrica L. Joe, Jack W. Guidarelli, Abhishek Murarka, Ramon Gonzalez Jan 2006

A Novel Data Mining Method To Identify Assay-Specific Signatures In Functional Genomic Studies, Derrick K. Rollins Sr., Dongmei Zhai, Alrica L. Joe, Jack W. Guidarelli, Abhishek Murarka, Ramon Gonzalez

Chemical and Biological Engineering Publications

Background: The highly dimensional data produced by functional genomic (FG) studies makes it difficult to visualize relationships between gene products and experimental conditions (i.e., assays). Although dimensionality reduction methods such as principal component analysis (PCA) have been very useful, their application to identify assay-specific signatures has been limited by the lack of appropriate methodologies. This article proposes a new and powerful PCA-based method for the identification of assay-specific gene signatures in FG studies. Results: The proposed method (PM) is unique for several reasons. First, it is the only one, to our knowledge, that uses gene contribution, a product of ...