BISON: bio-interface for the semi-global analysis of network patterns

BACKGROUND: The large amount of genomics data that have accumulated over the past decade require extensive data mining. However, the global nature of data mining, which includes pattern mining, poses difficulties for users who want to study specific questions in a more local environment. This creates a need for techniques that allow a localized analysis of globally determined patterns. RESULTS: We developed a tool that determines and evaluates global patterns based on protein property and network information, while providing all the benefits of a perspective that is targeted at biologist users with specific goals and interests. Our tool uses our own data mining techniques, integrated into current visualization and navigation techniques. The functionality of the tool is discussed in the context of the transcriptional network of regulation in the enteric bacterium Escherichia coli. Two biological questions were asked: (i) Which functional categories of proteins (identified by hidden Markov models) are regulated by a regulator with a specific domain? (ii) Which regulators are involved in the regulation of proteins that contain a common hidden Markov model? Using these examples, we explain the gene-centered and pattern-centered analysis that the tool permits. CONCLUSION: In summary, we have a tool that can be used for a wide variety of applications in biology, medicine, or agriculture. The pattern mining engine is global in the way that patterns are determined across the entire network. The tool still permits a localized analysis for users who want to analyze a subportion of the total network. We have named the tool BISON (Bio-Interface for the Semi-global analysis Of Network patterns)

Relating gene expression data on two-component systems to functional annotations in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionally, this has been done in two consecutive steps. The first step identifies important genes through clustering or statistical techniques, while the second step assigns biological functions to the identified groups. Recently, techniques have been developed that identify such relationships in a single step.</p> <p>Results</p> <p>We have developed an algorithm that relates patterns of gene expression in a set of microarray experiments to functional groups in one step. Our only assumption is that patterns co-occur frequently. The effectiveness of the algorithm is demonstrated as part of a study of regulation by two-component systems in <it>Escherichia coli</it>. The significance of the relationships between expression data and functional annotations is evaluated based on density histograms that are constructed using product similarity among expression vectors. We present a biological analysis of three of the resulting functional groups of proteins, develop hypotheses for further biological studies, and test one of these hypotheses experimentally. A comparison with other algorithms and a different data set is presented.</p> <p>Conclusion</p> <p>Our new algorithm is able to find interesting and biologically meaningful relationships, not found by other algorithms, in previously analyzed data sets. Scaling of the algorithm to large data sets can be achieved based on a theoretical model.</p

CHEM3240-CC.Analytical Chemistry.Sp15.Besemann,Daniel

Goals: To introduce and develop the theoretical concepts and laboratory practices of quantitative chemical analysis. Content: Theory and practice in classical analytical methods and instrumentation; emphasis on ionic equilibria and electrochemistry and their relevance to chemical analysis; application of computers and statistics to analytical problems. Taught: Annually, spring. Prerequisite: CHEM 1140 or CHEM 1500 (grade of C- or better). Credits: 4 credit

CHEM1130-A4.LAB: General Chemistry I.F15.Besemann,Daniel

Goals: To introduce and develop the fundamental principles of analytical, biological, inorganic, organic and physical chemistry. To provide instruction in fundamental laboratory techniques and to encourage the development of interpretive and problem-solving skills. Content: Scientific measurement, stoichiometry, energy changes, physical behavior of gases, electronic structure of atoms, periodicity, bonding models including valence bond, molecular orbital and hybridization, molecular geometry, intermolecular forces, properties of solutions, liquids and solids, nomenclature, and chemistry of familiar elements. Gravimetric, volumetric and calorimetric measurements; graphical data analysis. Taught: Annually Prerequisite: Higher algebra; high school chemistry is highly recommended NOTE: Students must concurrently register for a lecture and a corresponding 0-credit lab section of this course. Credits:

Differential association rule mining for the study of protein-protein interaction networks

christopher.besemann Protein-protein interactions are of great interest to biologists. A variety of high-throughput techniques have been devised, each of which leads to a separate definition of an interaction network. The concept of differential association rule mining is introduced to study the annotations of proteins in the context of one or more interaction networks. Differences among items across edges of a network are explicitly targeted. As a second step we identify differences between networks that are separately defined on the same set of nodes. The technique of differential association rule mining is applied to the comparison of protein annotations within an interaction network and between different interaction networks. In both cases we were able to find rules that explain known properties of protein interaction networks as well as rules that show promise for advanced study. General Terms association rule mining, protein interactions, relational data mining, graph-based data mining, redundant rules 1

CHEM1130-A8.LAB: General Chemistry I.F15.Besemann,Daniel

Goals: To introduce and develop the fundamental principles of analytical, biological, inorganic, organic and physical chemistry. To provide instruction in fundamental laboratory techniques and to encourage the development of interpretive and problem-solving skills. Content: Scientific measurement, stoichiometry, energy changes, physical behavior of gases, electronic structure of atoms, periodicity, bonding models including valence bond, molecular orbital and hybridization, molecular geometry, intermolecular forces, properties of solutions, liquids and solids, nomenclature, and chemistry of familiar elements. Gravimetric, volumetric and calorimetric measurements; graphical data analysis. Taught: Annually Prerequisite: Higher algebra; high school chemistry is highly recommended NOTE: Students must concurrently register for a lecture and a corresponding 0-credit lab section of this course. Credits:

CHEM1140-A5.LAB: General Chemistry II.Sp17.Besemann,Daniel

Goals: To further develop the fundamental principles of analytical, biological, inorganic, physical and organic chemistry. Emphasis on the development of problem-solving techniques. The laboratory focuses on inorganic qualitative analysis. Content: Spontaneity and rates of chemical reactions; equilibrium involving gases, acids, bases and salts; acid-base theories; titration theory and practice, electrochemistry, nuclear chemistry, biochemistry, the chemical and physical properties of metals, non-metals and coordination compounds. Taught: Annually. Prerequisite: CHEM 1130 (grade C- or better). NOTE: Students must concurrently register for a lecture and a corresponding 0-credit lab section of this course. Credits:

CHEM1130-A6.LAB: General Chemistry I.F13.Besemann,Daniel

Goals: To introduce and develop the fundamental principles of analytical, biological, inorganic, organic and physical chemistry. To provide instruction in fundamental laboratory techniques and to encourage the development of interpretive and problem-solving skills. Content: Scientific measurement, stoichiometry, energy changes, physical behavior of gases, electronic structure of atoms, periodicity, bonding models including valence bond, molecular orbital and hybridization, molecular geometry, intermolecular forces, properties of solutions, liquids and solids, nomenclature, and chemistry of familiar elements. Gravimetric, volumetric and calorimetric measurements; graphical data analysis. Application of modern spectroscopic techniques to structure determination. Taught: Annually. Prerequisite: Higher algebra. High school chemistry is highly recommended