Digital Commons Network^™

Metabolic Engineering Of A Thermophilic Bacterium To Produce Ethanol At High Yield, A. Joe Shaw, Kara K. Podkaminer, Sunil G. Desai, John S. Bardsley, Stephen R. Rogers, Philip G. Thorne, David A. Hogsett, Lee R. Lynd

Dartmouth Scholarship

We report engineering Thermoanaerobacterium saccharolyticum, a thermophilic anaerobic bacterium that ferments xylan and biomass-derived sugars, to produce ethanol at high yield. Knockout of genes involved in organic acid formation (acetate kinase, phosphate acetyltransferase, and L-lactate dehydrogenase) resulted in a strain able to produce ethanol as the only detectable organic product and substantial changes in electron flow relative to the wild type. Ethanol formation in the engineered strain (ALK2) utilizes pyruvate:ferredoxin oxidoreductase with electrons transferred from ferredoxin to NAD(P), a pathway different from that in previously described microbes with a homoethanol fermentation. The homoethanologenic phenotype was stable for >150 generations …

Clustering Of High-Dimensional Gene Expression Data With Feature Filtering Methods And Diffusion Maps, Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challenges in the computational analysis of such data is the curse of dimensionality, due to the overwhelming number of measures of gene expression levels versus the small number of samples. Here, we use a two-step method to reduce the dimension of gene expression data. At first, we extract a subset of genes based on the statistical characteristics of their corresponding gene expression measurements. For further dimensionality reduction, we then apply diffusion maps, …

Applications Of Diffusion Maps In Gene Expression Data-Based Cancer Diagnosis Analysis, Rui Xu, Donald C. Wunsch, Steven Damelin

Electrical and Computer Engineering Faculty Research & Creative Works

Early detection of a tumor's site of origin is particularly important for cancer diagnosis and treatment. The employment of gene expression profiles for different cancer types or subtypes has already shown significant advantages over traditional cancer classification methods. One of the major problems in cancer type recognition-oriented gene expression data analysis is the overwhelming number of measures of gene expression levels versus the small number of samples, which causes the curse of dimension issue. Here, we use diffusion maps, which interpret the eigenfunctions of Markov matrices as a system of coordinates on the original data set in order to obtain …

Sheep Updates 2007 - Part 2, Ian Mcfarland, Catherine Stockman, Anne Barnes, David Pethick, Jenny Davis, Brett Thompson, Ron Leng, Sally Pieruzzini, Elizabeth Jackson, Mohammed Quaddus, Nazrul Islam, John Stanton, Melanie Dowling

Sheep Updates

This session covers six papers from different authors:

CONCURRENT SESSIONS

FINISHING LAMB AND BEEF

1. Precision Feedlot Lamb, Ian McFarland, Department of Agriculture and Food, Western Australia

2. Feeding sheep under high heat load did not decrease intake of feedlot rations, Catherine Stockman, Department of Agriculture and Food, Western Australia & Murdoch University, Anne Barnes, Murdoch University David Pethick, Murdoch University

3. Taking the stress out of fifishing lambs and cattle - EasyFeed solutions, Jenny Davis, Brett Thomson, Milne AgriGroup, Welshpool WA, Ron Leng, Emeritus Professor, University of New England, Armidale, NSW

WOOL

4. DAFWA …

Fpga Acceleration Of Gene Rearrangement Analysis, Jason D. Bakos

Faculty Publications

In this paper we present our work toward FPGA acceleration of phylogenetic reconstruction, a type of analysis that is commonly performed in the fields of systematic biology and comparative genomics. In our initial study, we have targeted a specific application that reconstructs maximum-parsimony (MP) phylogenies for gene-rearrangement data. Like other prevalent applications in computational biology, this application relies on a control-dependent, memory-intensive, and non-arithmetic combinatorial optimization algorithm. To achieve hardware acceleration, we developed an FPGA core design that implements the application's primary bottleneck computation. Because our core is lightweight, we are able to synthesize multiple cores on a single FPGA. …

A Genetic Algorithms Approach To Non-Coding Rna Gene Searches, Jennifer A. Smith

Electrical and Computer Engineering Faculty Publications and Presentations

A genetic algorithm is proposed as an alternative to the traditional linear programming method for scoring covariance models in non-coding RNA (ncRNA) gene searches. The standard method is guaranteed to find the best score, but it is too slow for general use. The observation that most of the search space investigated by the linear programming method does not even remotely resemble any observed sequence in real sequence data can be used to motivate the use of genetic algorithms (GAs) to quickly reject regions of the search space. A search space with many local minima makes gradient decent an unattractive alternative. …

Gene Expression Data For Dlbcl Cancer Survival Prediction With A Combination Of Machine Learning Technologies, Rui Xu, Xindi Cai, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Gene expression profiles have become an important and promising way for cancer prognosis and treatment. In addition to their application in cancer class prediction and discovery, gene expression data can be used for the prediction of patient survival. Here, we use particle swarm optimization (PSO) to address one of the major challenges in gene expression data analysis, the curse of dimensionality, in order to discriminate high risk patients from low risk patients. A discrete binary version of PSO is used for gene selection and dimensionality reduction, and a probabilistic neural network (PNN) is implemented as the classifier. The experimental results …

Genome-Wide Requirements For Resistance To Functionally Distinct Dna-Damaging Agents, Patrick Flaherty

Mathematics and Statistics Department Faculty Publication Series

The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of ;4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNAdamage-response pathways as well as genes whose role in the DNA-damage …

A Latent Variable Model For Chemogenomic Profiling, Patrick Flaherty

Mathematics and Statistics Department Faculty Publication Series

Motivation: In haploinsufficiency profiling data, pleiotropic genes are often misclassified by clustering algorithms that impose the constraint that a gene or experiment belong to only one cluster. We have developed a general probabilistic model that clusters genes and experiments without requiring that a given gene or drug only appear in one cluster. The model also incorporates the functional annotation of known genes to guide the clustering procedure. Results: We applied our model to the clustering of 79 chemogenomic experiments in yeast. Known pleiotropic genes PDR5 and MAL11 are more accurately represented by the model than by a clustering procedure that …

Gene Regulatory Networks Inference With Recurrent Neural Network Models, Rui Xu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Large-scale time series gene expression data generated from DNA microarray experiments provide us a new means to reveal fundamental cellular processes, investigate functions of genes, and understand their relations and interactions. To infer gene regulatory networks from these data with effective computational tools has attracted intensive efforts from artificial intelligence and machine learning. Here, we use a recurrent neural network (RNN), trained with particle swarm optimization (PSO), to investigate the behaviors of regulatory networks. The experimental results, on a synthetic data set and a real data set, show that the proposed model and algorithm can effectively capture the dynamics of …

Multi-Class Cancer Classification By Semi-Supervised Ellipsoid Artmap With Gene Expression Data, Rui Xu, Donald C. Wunsch, Georgios C. Anagnostopoulos

Electrical and Computer Engineering Faculty Research & Creative Works

To accurately identify the site of origin of a tumor is crucial to cancer diagnosis and treatment. With the emergence of DNA microarray technologies, constructing gene expression profiles for different cancer types has already become a promising means for cancer classification. In addition to binary classification, the discrimination of multiple tumor types is also important semi-supervised ellipsoid ARTMAP (ssEAM) is a novel neural network architecture rooted in adaptive resonance theory suitable for classification tasks. ssEAM can achieve fast, stable and finite learning and create hyper-ellipsoidal clusters inducing complex nonlinear decision boundaries. Here, we demonstrate the capability of ssEAM to discriminate …

Final Report: Engineering Design Of Stable Immobilized Enzymes For The Hydrolysis And Transesterification Of Triglycerides, Dr.Hossein Noureddini, Gustavo F. Larsen

Department of Chemical and Biomolecular Engineering: Funded Proposals

Enzyme Immobilization. Work will continue in the area of enzymatic transesterification reaction (biodiesel). Both methyl and ethyl esters will be used in this study. Unlike the chemical reaction where methanol has a clear advantage over ethanol, ethanol can be used as easily as methanol in the enzymatic reaction.
Sol/Gel Structure Modification. Work will concentrate on the effect of the vacuum procedure on pore size and distribution for the transesterification reaction. Additives such as glucose have been very effective in the hydrolysis reaction and will be explored further in the transesterification reaction.
Characterization. The developed material will be characterized for the …

Changes In Pulmonary Arterial Wall Mechanical Properties And Lumenal Architecture With Induced Vascular Remodeling, Robert C. Molthen, Amy Heinrich, Steven Thomas Haworth, Christopher A. Dawson

Biomedical Engineering Faculty Research and Publications

To explore and quantify pulmonary arterial remodeling we used various methods including micro-CT, high-resolution 3-dimensional x-ray imaging, to examine the structure and function of intact pulmonary vessels in isolated rat lungs. The rat is commonly used as an animal model for studies of pulmonary hypertension (PH) and the accompanying vascular remodeling, where vascular remodeling has been defined primarily by changes in the vessel wall composition in response to hypertension inducing stimuli such as chronic hypoxic exposure (CHE) or monocrotaline (MCT) injection. Little information has been provided as to how such changes affect the vessel wall mechanical properties or the lumenal …

Chemogenomic Profiling: Identifying The Functional Interactions Of Small Molecules In Yeast, Patrick Flaherty

Mathematics and Statistics Department Faculty Publication Series

We demonstrate the efficacy of a genome-wide protocol in yeast that allows the identification of those gene products that functionally interact with small molecules and result in the inhibition of cellular proliferation. Here we present results from screening 10 diverse compounds in 80 genome-wide experiments against the complete collection of heterozygous yeast deletion strains. These compounds include anticancer and antifungal agents, statins, alverine citrate, and dyclonine. In several cases, we identified previously known interactions; furthermore, in each case, our analysis revealed novel cellular interactions, even when the relationship between a compound and its cellular target had been well established. In …

Inference Of Genetic Regulatory Networks With Recurrent Neural Network Models, Rui Xu, Xiao Hu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Large-scale gene expression data coming from microarray experiments provide us a new means to reveal fundamental cellular processes, investigate functions of genes, and understand relations and interactions among them. To infer genetic regulatory networks from these data with effective computational tools has become increasingly important Several mathematical models, including Boolean networks, Bayesian networks, dynamic Bayesian networks, and linear additive regulation models, have been used to explore the behaviors of regulatory networks. In this paper, we investigate the inference of genetic regulatory networks from time series gene expression in the framework of recurrent neural network model.

Genome-Wide Screening For Trait Conferring Genes Using Dna Microarrays, R. T. Gill, S. Wildt, Y. T. Yang, S. Ziesman, G. Stephanopoulos

Dartmouth Scholarship

We report a DNA microarray-based method for genome-wide monitoring of competitively grown transformants to identify genes whose overexpression confers a specific cellular phenotype. Whereas transcriptional profiling identifies differentially expressed genes that are correlated with particular aspects of the cellular phenotype, this functional genomics approach determines genes that result in a specific physiology. This parallel gene-trait mapping method consists of transforming a strain with a genomic library, enriching the cell population in transformants containing the trait conferring gene(s), and finally using DNA microarrays to simultaneously isolate and identify the enriched gene inserts. Various methods of enrichment can be used; here, genes …

Functional Profiling Of The Saccharomyces Cerevisiae Genome, Patrick Flaherty

Mathematics and Statistics Department Faculty Publication Series

Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth …

Abnormal Cell Detection Using The Choquet Integral, R. Joe Stanley, James M. Keller, Charles William Caldwell, Paul D. Gader

Electrical and Computer Engineering Faculty Research & Creative Works

Automated Giemsa-banded chromosome image research has been largely restricted to classification schemes associated with isolated chromosomes within metaphase spreads. In normal human metaphase spreads, there are 46 chromosomes occurring in homologous pairs for the autosomal classes 1-22 and the X chromosome for females. Many genetic abnormalities are directly linked to structural and/or numerical aberrations of chromosomes within metaphase spreads. Cells with the Philadelphia chromosome contain an abnormal chromosome for class 9 and for class 22, leaving a single normal chromosome for each class. A data-driven homologue matching technique is applied to recognizing normal chromosomes from classes 9 and 22. Homologue …

Studies On The Formation Of Dna-Cationic Lipid Composite Films And Dna Hybridization In The Composites, Murali Sastry, Vidya Ramakrishnan, Mrunalini Pattarkine, Krishna N. Ganesh

Faculty Works

The formation of composite films of double-stranded DNA and cationic lipid molecules (octadecylamine, ODA) and the hybridization of complementary single-stranded DNA molecules in such composite films are demonstrated. The immobilization of DNA is accomplished by simple immersion of a thermally evaporated ODA film in the DNA solution at close to physiological pH. The entrapment of the DNA molecules in the cationic lipid film is dominated by attractive electrostatic interaction between the negatively charged phosphate backbone of the DNA molecules and the protonated amine molecules in the thermally evaporated film and has been quantified using quartz crystal microgravimetry (QCM). Fluorescence studies …

Hybridization Of Dna By Sequential Immobilization Of Oligonucleotides At The Air-Water Interface, Murali Sastry, Vidya Ramakrishnan, Mrunalini Pattarkine, Anand Gole, K. N. Ganesh

Faculty Works

The hybridization of DNA by sequential electrostatic and hydrogen-bonding immobilization of single-stranded complementary oligonucleotides at the air-water interface with cationic Langmuir monolayers is demonstrated. The complexation of the single-stranded DNA molecules with octadecylamine (ODA) Langmuir monolayers was followed in time by monitoring the pressure-area isotherms. A large (and slow) expansion of the ODA monolayer was observed during each stage of complexation in the following sequence: primary single-stranded DNA followed by complementary single-stranded DNA followed by the intercalator, ethidium bromide. Langmuir-Blodgett (LB) films of the ODA-DNA complex were formed on different substrates and characterized using quartz-crystal microgravimetry (QCM), Fourier transform infrared …

Data-Driven Homologue Matching For Chromosome Identification, R. Joe Stanley, James M. Keller, Paul D. Gader, Charles William Caldwell

Electrical and Computer Engineering Faculty Research & Creative Works

Karyotyping involves the visualization and classification of chromosomes into standard classes. In "normal" human metaphase spreads, chromosomes occur in homologous pairs for the autosomal classes 1-22, and X chromosome for females. Many existing approaches for performing automated human chromosome image analysis presuppose cell normalcy, containing 46 chromosomes within a metaphase spread with two chromosomes per class. This is an acceptable assumption for routine automated chromosome image analysis. However, many genetic abnormalities are directly linked to structural or numerical aberrations of chromosomes within the metaphase spread. Thus, two chromosomes per class cannot be assumed for anomaly analysis. This paper presents the …

Explorations, Vol. 1, No. 1, R. D. Blake, Katherine Carter, David Mackinnon Ebitz, Carole J. Bombard, Stephen A. Norton

Explorations — A Journal of Research

Welcome to the first issue of Explorations, A Journal of Research at the University of Maine at Orono.

Join us as we explore a representative selection of the pure and applied research of our faculty. At UMO, we believe that research can capture the imagination and invigorate the mind, as well as contribute directly to the quality of life of the citizens we serve.

In this first issue, we have selected four areas of research that span the disciplines of biological and environmental sciences and the arts. This is but a small part of the research conducted by the faculty …