Ingrid Fischer

A quantitative comparison of the subgraph miners mofa, gspan, FFSM, and gaston

Several new miners for frequent subgraphs have been published recently. Whereas new approaches are presented in detail, the quantitative evaluations are often of limited value: only the performance on a small set of graph databases is discussed and the new algorithm is often only compared to a single competitor based on an executable. It remains unclear, how the algorithms work on bigger/other graph databases and which of their distinctive features is best suited for which database. We have re-implemented the subgraph miners MoFa, gSpan, FFSM, and Gaston within a common code base and with the same level of programming expertise and optimization effort. This paper presents the results of a comparative benchmarking that ran the algorithms on a comprehensive set of graph databases.

Computational Life Sciences II

Come with us to read a new book that is coming recently. Yeah, this is a new coming book that many people really want to read will you be one of them? Of course, you should be. It will not make you feel so hard to enjoy your life. Even some people think that reading is a hard to do, you must be sure that you can do it. Hard will be felt when you have no ideas about what kind of book to read. Or sometimes, your reading material is not interesting enough.Systems Biology.- Structural Protein Interactions Predict Kinase-Inhibitor Interactions in Upregulated Pancreas Tumour Genes Expression Data.- Biochemical Pathway Analysis via Signature Mining.- Recurrent Neuro-fuzzy Network Models for Reverse Engineering Gene Regulatory Interactions.- Data Analysis and Integration.- Some Applications of Dummy Point Scatterers for Phasing in Macromolecular X-Ray Crystallography.- BioRegistry: A Structured Metadata Repository for Bioinformatic Databases.- Robust Perron Cluster Analysis for Various Applications in Computational Life Science.- Structural Biology.- Multiple Alignment of Protein Structures in Three Dimensions.- Protein Annotation by Secondary Structure Based Alignments (PASSTA).- MAPPIS: Multiple 3D Alignment of Protein-Protein Interfaces.- Genomics.- Frequent Itemsets for Genomic Profiling.- Gene Selection Through Sensitivity Analysis of Support Vector Machines.- The Breakpoint Graph in Ciliates.- Computational Proteomics.- ProSpect: An R Package for Analyzing SELDI Measurements Identifying Protein Biomarkers.- Algorithms for the Automated Absolute Quantification of Diagnostic Markers in Complex Proteomics Samples.- Detection of Protein Assemblies in Crystals.- Molecular Informatics.- Molecular Similarity Searching Using COSMO Screening Charges (COSMO/3PP).- Increasing Diversity in In-silico Screening with Target Flexibility.- Multiple Semi-flexible 3D Superposition of Drug-Sized Molecules.- Molecular Structure Determination and Simulation.- Efficiency Considerations in Solving Smoluchowski Equations for Rough Potentials.- Fast and Accurate Structural RNA Alignment by Progressive Lagrangian Optimization.- Visual Analysis of Molecular Conformations by Means of a Dynamic Density Mixture Model.- Distributed Data Mining.- Distributed BLAST in a Grid Computing Context.- Parallel Tuning of Support Vector Machine Learning Parameters for Large and Unbalanced Data Sets.- The Architecture of a Proteomic Network in the Yeast.

The ParMol Package for Frequent Subgraph Mining

Mining for frequent subgraphs in a graph database has become a popular topic in the last years. Algorithms to solve this problem are used in chemoinformatics to find common molecular fragments in a database of molecules represented as two-dimensional graphs. However, the search process in arbitrary graph structures includes costly graph and subgraph isomorphism tests. In our ParMol package we have implemented four of the most popular frequent subgraph miners using a common infrastructure: MoFa, gSpan, FFSM, and Gaston. Besides the pure re-implementation, we have added additional functionality to some of the algorithms like parallel search, mining directed graphs, and mining in one big graph instead of a graph database. Also a 2D-visualizer for molecules has been integrated.

Mining Molecular Datasets on Symmetric Multiprocessor Systems

Although in the last few years about a dozen sophisticated algorithms for mining frequent fragments in molecular databases have been proposed, searching big databases with 100,000 compounds and more is still a time-consuming process. Even the currently fastest algorithms like gSpan, FFSM, Gaston, or MoFa require hours to complete their tasks. This paper presents thread-based parallel versions of MoFa [5] and gSpan [26] that achieve speedups up to 11 on a shared-memory SMP system using 12 processors. We discuss the design space of the parallelization, the results, and the obstacles that are caused by the irregular search space and by the current state of Java technology.

Parsing String Generating Hypergraph Grammars

A string generating hypergraph grammar is a hyperedge replacement grammar where the resulting language consists of string graphs i.e. hypergraphs modeling strings. With the help of these grammars, string languages like a n b n c n can be modeled that can not be generated by context-free grammars for strings. They are well suited to model discontinuous constituents in natural languages, i.e. constituents that are interrupted by other constituents. For parsing context-free Chomsky grammars, the Earley parser is well known. In this paper, an Earley parser for string generating hypergraph grammars is presented, leading to a parser for natural languages that is able to handle discontinuities.

Graph-Based Procedural Abstraction

Procedural abstraction (PA) extracts duplicate code segments into a newly created method and hence reduces code size. For embedded micro computers the amount of memory is still limited so code reduction is an important issue. This paper presents a novel approach to PA, that is especially targeted towards embedded systems. Earlier approaches of PA are blind with respect to code reordering, i.e., two code segments with the same semantic effect but with different instruction orders were not detected as candidates for PA. Instead of instruction sequences, in our approach the data flow graphs of basic blocks are considered. Compared to known PA techniques more than twice the number of instructions can be saved on a set of binaries, by detecting frequently appearing graph fragments with a graph mining tool based on the well known gSpan algorithm. The detection and extraction of graph fragments is not as straight forward as extracting sequential code fragments. NP-complete graph operations and special rules to decide which parts can be abstracted are needed. However, this effort pays off as smaller sizes significantly reduce costs on mass-produced embedded systems

Local Views on Distributed Systems and Their Communication

Distributed graph transformation has been used to specify static as well as dynamic aspects of distributed systems. To support distributed designs by different developers, local views are introduced. A local view on a distributed system consists of one local system, its import and export interfaces, and connected remote interfaces. The behavior of a local system is specified by a set of graph rules that are applicable only to the local view of the local system. Local systems communicate either synchronously or asynchronously via their import and export interfaces. Asynchronous communication is modeled by sequential application of graph rules, synchronous communication by the amalgamation of graph rules. We compose a distributed system grammar from the rule sets for local systems. The operational semantics of the distributed system is given by distributed transformation sequences.

Modeling Discontinuous Constituents with Hypergraph Grammars

Discontinuous constituents are a frequent problem in natural language analyses. A constituent is called discontinuous if it is interrupted by other constituents. In German they can appear with separable verb prefixes or relative clauses in the Nachfeld. They can not be captured by a context–free Chomsky grammar. A subset of hypergraph grammars are string-graph grammars where the result of a derivation must be formed like a string i.e. terminal edges are connected to two nodes and are lined up in a row. Nonterminal edges do not have to fulfill this property. In this paper it is shown that a context–free string-graph grammar (one hyperedge is replaced at a time) can be used to model discontinuous constituents in natural languages.

Formalizing neural networks using graph transformations

In this paper a unifying framework for the formalization of different types of neural networks and the corresponding algorithms for computation and training is presented. The used graph transformation system offers a formalism to verify properties of the networks and their algorithms. In addition the presented methodology can be used as a tool to visualize and design different types of networks along with all required algorithms. An algorithm that adapts network parameters using standard gradient descent as well as parts of a constructive, topology-changing algorithm for probabilistic neural networks are used to demonstrate the proposed formalism.

Computational Life Sciences II: Second International Symposium, CompLife 2006, Cambridge, UK, September 2006, Proceedings

Genomics.- Improved Robustness in Time Series Analysis of Gene Expression Data by Polynomial Model Based Clustering.- A Hybrid Grid and Its Application to Orthologous Groups Clustering.- Promoter Prediction Using Physico-Chemical Properties of DNA.- Parametric Spectral Analysis of Malaria Gene Expression Time Series Data.- An Efficient Algorithm for Finding Long Conserved Regions Between Genes.- The Reversal Median Problem, Common Intervals, and Mitochondrial Gene Orders.- Data Mining.- Building Structure-Property Predictive Models Using Data Assimilation.- Set-Oriented Dimension Reduction: Localizing Principal Component Analysis Via Hidden Markov Models.- Relational Subgroup Discovery for Descriptive Analysis of Microarray Data.- Applicability of Loop Recombination in Ciliates Using the Breakpoint Graph.- High-Throughput Identification of Chemistry in Life Science Texts.- Beating the Noise: New Statistical Methods for Detecting Signals in MALDI-TOF Spectra Below Noise Level.- Molecular Simulation.- Dynamic Complexity of Chaotic Transitions in High-Dimensional Classical Dynamics: Leu-Enkephalin Folding.- Solvent Effects and Conformational Stability of a Tripeptide.- Grid Assisted Ensemble Molecular Dynamics Simulations of HIV-1 Proteases Reveal Novel Conformations of the Inhibitor Saquinavir.- Molecular Informatics.- A Structure-Based Analysis of Single Molecule Force Spectroscopy (SMFS) Data for Bacteriorhodopsin and Four Mutants.- Classifying the World Anti-Doping Agencys 2005 Prohibited List Using the Chemistry Development Kit Fingerprint.- A Point-Matching Based Algorithm for 3D Surface Alignment of Drug-Sized Molecules.- Systems Biology.- Adaptive Approach for Modelling Variability in Pharmacokinetics.- A New Approach to Flux Coupling Analysis of Metabolic Networks.- Biological Networks / Metabolism.- Software Supported Modelling in Pharmacokinetics.- On the Interpretation of High Throughput MS Based Metabolomics Fingerprints with Random Forest.- Construction of Correlation Networks with Explicit Time-Slices Using Time-Lagged, Variable Interval Standard and Partial Correlation Coefficients.- Computational Neuroscience.- The Language of Cortical Dynamics.- A Simple Method to Simultaneously Track the Numbers of Expressed Channel Proteins in a Neuron.