Thesis (M.S.)--University of California, San Francisco, 2009. / Source: Masters Abstracts International, Volume: 48-02, page: 0876. Adviser: Andrej Sali.

<p>Understanding the cold acclimation process in plants may help us develop genetically engineered plants that are resistant to cold. The key factor in understanding this process is to study the genes and thus the gene regulatory network that is involved in the cold acclimation process. Most of the existing approaches1-8 in deriving regulatory networks rely only on the gene expression data. Since the expression data is usually noisy and sparse the networks generated by these approaches are usually incoherent and incomplete. Hence a new approach is proposed here that analyzes the promoter regions along with the expression data in inferring the regulatory networks. In this approach genes are grouped into sets if they contain similar over-represented motifs or motif pairs in their promoter regions and if their expression pattern follows the expression pattern of the regulating gene. The network thus derived is evaluated using known literature evidence, functional annotations and from statistical tests.</p>

<p>Coryneform bacteria are largely distributed in nature and are rod like, aerobic soil bacteria capable of growing on a variety of sugars and organic acids. Corynebacterium glutamicum is a nonpathogenic species of Coryneform bacteria used for industrial production of amino acids. There are three main publicly available genome annotations, Cg, Cgl and NCgl for C. glutamicum. All these three annotations have different numbers of protein coding genes and varying numbers of overlaps of similar genes. The original data is only available in text files. In this format of genome data, it was not easy to search and compare the data among different annotations and it was impossible to make an extensive multidimensional customized formal search against different protein parameters. Comparison of all genome annotations for construction deletion, over-expression mutants, graphical representation of genome information, such as gene locations, neighboring genes, orientation (direct or complementary strand), overlapping genes, gene lengths, graphical output for structure function relation by comparison of predicted trans-membrane domains (TMD) and functional protein domains protein motifs was not possible when data is inconsistent and redundant on various publicly available biological database servers. There was therefore a need for a system of managing the data for mutants and experimental setups. In spite of the fact that the genome sequence is known, until now no databank providing such a complete set of information has been available. We solved these problems by developing a standalone relational database software application covering data processing, protein-DNA sequence extraction and</p><p>management of lab data. The result of the study is an application named, CORYNEBASE, which is a software that meets our aims and objectives.</p>

No description available.

<p>Endometrial adenocarcinoma (EAC) is the fourth leading cause of carcinoma in woman worldwide, but not much is known about genetic factors involved in this complex disease. During the EAC process, it is well known that losses and gains of chromosomal regions do not occur completely at random, but partly through some flow of causality. In this work, we used three different algorithms based on frequency of genomic alterations to construct 27 tree models of oncogenesis. So far, no study about applying pathway models to microsatellite marker data had been reported. Data from genome–wide scans with microsatellite markers were classified into 9 data sets, according to two biological approaches (solid tumor cell and corresponding tissue culture) and three different genetic backgrounds provided by intercrossing the susceptible rat BDII strain and two normal rat strains. Compared to previous study, similar conclusions were drawn from tree models that three main important regions (I, II and III) and two subordinate regions (IV and V) are likely to be involved in EAC development. Further information about these regions such as their likely order and relationships was produced by the tree models. A high consistency in tree models and the relationship among p19, Tp53 and Tp53 inducible</p><p>protein genes provided supportive evidence for the reliability of results.</p>

<p>QuantitativeTraitLocus (QTL) is a statistical method used to restrict genomic regions contributing to specific phenotypes. To further localize genes in such regions a web tool called “Candidate Gene Capture” (CGC) was developed by Andersson et al. (2005). The CGC tool was based on the textual description of genes defined in the human phenotype database OMIM. Even though the CGC tool works well, the tool was limited by a number of inconsistencies in the underlying database structure, static web pages and some gene descriptions without properly defined function in the OMIM database. Hence, in this work the CGC tool was improved by redesigning its database structure, adding dynamic web pages and improving the prediction of unknown gene function by using exon analysis. The changes in database structure diminished the number of tables considerably, eliminated redundancies and made data retrieval more efficient. A new method for prediction of gene function was proposed, based on the assumption that similarity between exon sequences is associated with biochemical function. Using Blast with 20380 exon protein sequences and a threshold E-value of 0.01, 639 exon groups were obtained with an average of 11 exons per group. When estimating the functional similarity, it was found that on the average 72% of the exons in a group had at least one Gene Ontology (GO) term in common.</p>

<p>Feature extraction by digital image analysis and cell classification is an important task for cell culture automation. In High Throughput Screening (HTS) where thousands of data points are generated and processed at once, features will be extracted and cells will be classified to make a decision whether the cell-culture is going on smoothly or not. The culture is restarted if a problem is detected. In this thesis project HeLa cells, which are human epithelial cancer cells, are selected for the experiment. The purpose is to classify two types of HeLa cells in culture: Cells in cleavage that are round floating cells (stressed or dead cells are also round and floating) and another is, normal growing cells that are attached to the substrate. As the number of cells in cleavage will always be smaller than the number of cells which are growing normally and attached to the substrate, the cell-count of attached cells should be higher than the round cells. There are five different HeLa cell images that are used. For each image, every single cell is obtained by image segmentation and isolation. Different mathematical features are found for each cell. The feature set for this experiment is chosen in such a way that features are robust, discriminative and have good generalisation quality for classification. Almost all the features presented in this thesis are rotation, translation and scale invariant so that they are expected to perform well in discriminating objects or cells by any classification algorithm. There are some new features added which are believed to improve the classification result. The feature set is considerably broad rather than in contrast with the restricted sets which have been used in previous work. These features are used based on a common interface so that the library can be extended and integrated into other applications. These features are fed into a machine learning algorithm called Linear Discriminant Analysis (LDA) for classification. Cells are then classified as ‘Cells attached to the substrate’ or Cell Class A and ‘Cells in cleavage’ or Cell Class B. LDA considers features by leaving and adding shape features for increased performance. On average there is higher than ninety five percent accuracy obtained in the classification result which is validated by visual classification.</p>

<p>Background: Computational simulation of complex biological networks lies at the heart of systems biology since it can confirm the conclusions drawn by experimental studies of biological networks and guide researchers to produce fresh hypotheses for further experimental validation. Since this iterative process helps in development of more realistic system models a variety of computational tools have been developed. In the absence of a common format for representation of models these tools were developed in different formats. As a result these tools became unable to exchange models amongst them, leading to development of SBML, a standard exchange format for computational models of biochemical networks. Here the formats of SBML and one of the commercial tools of systems biology are being compared to study the issues which may arise during conversion between their respective formats. A tool StoP has been developed to convert the format of SBML to the format of the selected tool.</p><p>Results: The basic format of SBML representation which is in the form of listings of various elements of a biochemical reaction system differs from the representation of the selected tool which is location oriented. In spite of this difference the various components of biochemical pathways including multiple compartments, global parameters, reactants, products, modifiers, reactions, kinetic formulas and reaction parameters could be converted from the SBML representation to the representation of the selected tool. The MathML representation of the kinetic formula in an SBML model can be converted to the string format of the selected tool. Some features of the SBML are not present in the selected tool. Similarly, the ability of the selected tool to declare parameters for locations, which are global to those locations and their children, is not present in the SBML.</p><p>Conclusions: Differences in representations of pathway models may include differences in terminologies, basic architecture, differences in capabilities of software’s, and adoption of different standards for similar things. But the overall similarity of domain of pathway models enables us to interconvert these representations. The selected tool should develop support for unit definitions, events and rules. Development of facility for parameter declaration at compartment level by SBML and facility for function declaration by the selected tool is recommended.</p>

Experiments were performed using a modification of the technique developed by Spanner and Prebble 1962 to monitor the translocation of tracers along the petiole of Nymohoides peltata. Three tracers were used, Br and Na and at least three experiments were performed using each isotope. A very complete record of tracer distribution in time and space was obtained for each isotope. Computer simulation of translocation was developed based on a physical model consisting of a centrally located conducting channel in which a mass flow occurs and a surrounding non-conducting ground tissue. Reversible lateral exchange takes place between these two. The simulation is characterised by an inputfunction and three dimensionless parameters, V, R and K which are related to the velocities of longitudinal flow and reversible lateral leakage and which can be varied with both time and distance. The simulation is possessed of considerable versatility and in this way has many advantages over existing mathematical models. The information it provides is useful in its own right and suggests that the importance accorded the linear nature of the semi-logarithmic profiles in the past is unwarrented. In association with the above simulation a simple direct search optimisation programme was developed based on the least squares criterion to match the simulation to the experimental data. It was found that an acceptable match to the experiments could only be obtained if the time course accumulation of activity in the root-stock was reduced by an arbitrary factor. Although this part of the work failed in its main objective of obtaining estimates of the translocation parameters, it at least suggested a way in which they may be estimated and is encouraging for future work.

Quantitative structure-activity relationships (QSAR) rationalize interrelation between molecular structure and biological response in terms of either physicochemical parameters, as in linear free energy relationships (LFER), or via purely empirical parameters, as is the case for De Novo schemes. In LFER the leading process is often the partitioning of a compound between two solvent phases, taken to represent the transfer of a drug molecule across a biological membrane. This study has investigated the partitioning behaviour of three series of hydroxybenzoate esters, viz. o-, m- and predominantly p-esters, the latter being preservatives in pharmaceutical formulations. The thermodynamic parameters AH, AG and AS for the transfer process were derived in an attempt to establish a QSAR. on a fundamental thermodynamic basis. Such parameters have identifiable physicochemical meaning and lend themselves more readily to interpretation. This facilitates application to alternative systems. A new Gibbs function factor analysis was developed and utilized to obtain thermodynamic contributions for parent and incremental methylene group portions of thestudy molecules. The empirical Collander equation for interrelation of various solute/solvent systems was also rationalized on a thermodynamic basis. Further extension of the Gibbs function factor analysis allowed scaling of "solvent" systems including chromatographic packings, solvents and liposomes. The scheme indicated capacity for optimized selection of bulk solvent systems to mimic biological membranes. A novel analytical procedure for direct measurement of biological response was developed. The bioassay appeared capable of discrimination i) between the closely related structural homologues, ii) between gram-negative and gram-positive bacteria, and further, iii) between certain cell batches of the same bacteria type. Also, the bioassay demonstrated a Collander interrelation between the two bacteria types. Flow microcalorimetry was the technique employed to measure thermal response of respiring E. coli and Staph, aur. bacteria. The modification of biological response with drug concentration was quantitated and a log dose max term was derived for each homologue. The results indicated potential for a predictive, additive structure-activity scheme based on assessment of biological response (BR) direct rather than through f(BR) via physicochemical or empirical parameters.