Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Find my office: Navigating real space from semantic descriptions

This paper shows that by using only symbolic language phrases, a mobile robot can purposefully navigate to specified rooms in previously unexplored environments. The robot intelligently organises a symbolic language description of the unseen environment and “imagines” a representative map, called the abstract map. The abstract map is an internal representation of the topological structure and spatial layout of symbolically defined locations. To perform goal-directed exploration, the abstract map creates a high-level semantic plan to reason about spaces beyond the robot’s known world. While completing the plan, the robot uses the metric guidance provided by a spatial layout, and grounded observations of door labels, to efficiently guide its navigation. The system is shown to complete exploration in unexplored spaces by travelling only 13.3% further than the optimal path.

On the expressive power of behavioral profiles

Behavioral profiles have been proposed as a behavioral abstraction of dynamic systems, specifically in the context of business process modeling. A behavioral profile can be seen as a complete graph over a set of task labels, where each edge is annotated with one relation from a given set of binary behavioral relations. Since their introduction, behavioral profiles were argued to provide a convenient way for comparing pairs of process models with respect to their behavior or computing behavioral similarity between process models. Still, as of today, there is little understanding of the expressive power of behavioral profiles. Via counter-examples, several authors have shown that behavioral profiles over various sets of behavioral relations cannot distinguish certain systems up to trace equivalence, even for restricted classes of systems represented as safe workflow nets. This paper studies the expressive power of behavioral profiles from two angles. Firstly, the paper investigates the expressive power of behavioral profiles and systems captured as acyclic workflow nets. It is shown that for unlabeled acyclic workflow net systems, behavioral profiles over a simple set of behavioral relations are expressive up to configuration equivalence. When systems are labeled, this result does not hold for any of several previously proposed sets of behavioral relations. Secondly, the paper compares the expressive power of behavioral profiles and regular languages. It is shown that for any set of behavioral relations, behavioral profiles are strictly less expressive than regular languages, entailing that behavioral profiles cannot be used to decide trace equivalence of finite automata and thus Petri nets.

Learning with a mutualistic teacher

The concept of a “mutualistic teacher” is introduced for unsupervised learning of the mean vectors of the components of a mixture of multivariate normal densities, when the number of classes is also unknown. The unsupervised learning problem is formulated here as a multi-stage quasi-supervised problem incorporating a cluster approach. The mutualistic teacher creates a quasi-supervised environment at each stage by picking out “mutual pairs” of samples and assigning identical (but unknown) labels to the individuals of each mutual pair. The number of classes, if not specified, can be determined at an intermediate stage. The risk in assigning identical labels to the individuals of mutual pairs is estimated. Results of some simulation studies are presented.

Spectral Values

This series of drawings takes a diagrammatically creative approach to understanding the economic theories and personalities at the centre of the Global Financial Crisis. Mimicking the form of US currency, the work removes labels from common economic diagrams and portrays financial titans in repose as a way to express a personal and ambivalent experience of contemporary capitalism.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

Surface cathepsin B protects cytotoxic lymphocytes from self-destruction after degranulation.

The granule exocytosis cytotoxicity pathway is the major molecular mechanism for cytotoxic T lymphocyte (CTL) and natural killer (NK) cytotoxicity, but the question of how these cytotoxic lymphocytes avoid self-destruction after secreting perforin has remained unresolved. We show that CTL and NK cells die within a few hours if they are triggered to degranulate in the presence of nontoxic thiol cathepsin protease inhibitors. The potent activity of the impermeant, highly cathepsin B-specific membrane inhibitors CA074 and NS-196 strongly implicates extracellular cathepsin B. CTL suicide in the presence of cathepsin inhibitors requires the granule exocytosis cytotoxicity pathway, as it is normal with CTLs from gld mice, but does not occur in CTLs from perforin knockout mice. Flow cytometry shows that CTLs express low to undetectable levels of cathepsin B on their surface before degranulation, with a substantial rapid increase after T cell receptor triggering. Surface cathepsin B eluted from live CTL after degranulation by calcium chelation is the single chain processed form of active cathepsin B. Degranulated CTLs are surface biotinylated by the cathepsin B-specific affinity reagent NS-196, which exclusively labels immunoreactive cathepsin B. These experiments support a model in which granule-derived surface cathepsin B provides self-protection for degranulating cytotoxic lymphocytes.

The supermarket of the future: Directions for Australia

Supermarkets are scrambling to effect change across stores in order to meet the needs of a changing consumer and stay ahead of their competition. If the UK, US and European market is anything to go by, our Australian supermarkets of the future will offer less choice and engagement, but more private labels, greater convenience and solutions.

Sukupolvien ongelma : Tutkielmia sukupolven käsitteestä, sukupolvitietoisuudesta ja suurista ikäluokista

The aims of the thesis are (1) to present a systematic evaluation of generation and its relevance as a sociological concept, (2) to reflect on how generational consciousness, i.e. generation as an object of collective identification that has social significance, can emerge and take shape, (3) to analyze empirically the generational experiences and consciousness of one specific generation, namely Finnish baby boomers (b. 1945 1950). The thesis contributes to the discussion on the social (as distinct from its genealogical) meaning of the concept of generation, launched by Karl Mannheim s classic Das Problem der Generationen (1928), in which the central idea is that a certain group of people is bonded together by a shared experience and that this bonding can result in a distinct self-consciousness. The thesis is comprised of six original articles and an extensive summarizing chapter. In the empirical articles, the baby boomers are studied on the basis of nationally representative survey data (N = 2628) and narrative life-story interviews (N = 38). In the article that discusses the connection of generations and social movements, the analysis is based on the member survey of Attac Finland (N = 1096). Three main themes were clarified in the thesis. (1) In the social sense the concept of generation is a modern, problematic, and ultimately a political concept. It served the interests of the intellectuals who developed the concept in the early 20th century and provided them, as an alternative to the concept of social class, a new way of think about social change and progress. The concept of generation is always coupled with the concept of Zeitgeist or some other controversial way of defining what is essential, i.e. what creates generations, in a given culture. Thus generation is, as a product of definition and classification struggles, a contested concept. The concept also clearly implies elitist connotations; the idea of some kind of vanguard (the elite) that represents an entire generation by proclaiming itself as its spokesman automatically creates a counterpart, namely the others in the peer group who are thought to be represented (the masses). (2) Generational consciousness cannot emerge as a result of any kind of automatic process or endogenously; it must be made. There has to be somebody who represents the generation in order for that generation to exist in people s minds and as an object of identification; generational experiences and their meanings must be articulated. Hence, social generations are, in a fundamental manner, discursively constructed. The articulations of generational experiences (speeches, writings, manifests, labels etc.) can be called as the discursive dimension of social generations, and through this notion, how public discourse shapes people s generational consciousness can be seen. Another important element in the process is collective memory, as generational consciousness often takes form only retrospectively. (3) Finnish baby boomers are not a united or homogeneous generation but are divided into many smaller sections with specific generational experiences and consciousnesses. The content of the generational consciousness of the baby boomers is heavily politically charged. A salient dividing line inside the age group is formed by individual attitudes towards so-called 1960s radicalism. Identification with the 1960s generation functions today as a positive self-definition of a certain small leftist elite group, and the values and characteristics usually connected with the idea of the 1960s generation do not represent the whole age group. On the contrary, among some of the members of the baby boomers, the generational identification is still directed by the experience of how traditional values were disgraced in the 1960s. As objects of identification, the neutral term baby boomers and the charged 1960s generation are totally different things, and therefore they should not be used as synonyms. Although the significance of the group of the 1960s generation is often overestimated, they are however special with respect to generational consciousness because they have presented themselves as the voice of the entire generation. Their generational interpretations have spread through the media with the help of certain iconic images of the generation insomuch that 1960s radicalism has become an indirect generational experience for other parts of the baby boom cohort as well.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

Fast in-memory XPath search using compressed indexes

A large fraction of an XML document typically consists of text data. The XPath query language allows text search via the equal, contains, and starts-with predicates. Such predicates can be efficiently implemented using a compressed self-index of the document's text nodes. Most queries, however, contain some parts querying the text of the document, plus some parts querying the tree structure. It is therefore a challenge to choose an appropriate evaluation order for a given query, which optimally leverages the execution speeds of the text and tree indexes. Here the SXSI system is introduced. It stores the tree structure of an XML document using a bit array of opening and closing brackets plus a sequence of labels, and stores the text nodes of the document using a global compressed self-index. On top of these indexes sits an XPath query engine that is based on tree automata. The engine uses fast counting queries of the text index in order to dynamically determine whether to evaluate top-down or bottom-up with respect to the tree structure. The resulting system has several advantages over existing systems: (1) on pure tree queries (without text search) such as the XPathMark queries, the SXSI system performs on par or better than the fastest known systems MonetDB and Qizx, (2) on queries that use text search, SXSI outperforms the existing systems by 1-3 orders of magnitude (depending on the size of the result set), and (3) with respect to memory consumption, SXSI outperforms all other systems for counting-only queries.

Phenomenological Ginzburg-Landau-like theory for superconductivity in the cuprates

We propose and develop here a phenomenological Ginzburg-Landau-like theory of cuprate high-temperature superconductivity. The free energy of a cuprate superconductor is expressed as a functional F of the complex spin-singlet pair amplitude psi(ij) equivalent to psi(m) = Delta(m) exp(i phi(m)), where i and j are nearest-neighbor sites of the square planar Cu lattice in which the superconductivity is believed to primarily reside, and m labels the site located at the center of the bond between i and j. The system is modeled as a weakly coupled stack of such planes. We hypothesize a simple form FDelta, phi] = Sigma(m)A Delta(2)(m) + (B/2)Delta(4)(m)] + C Sigma(< mn >) Delta(m) Delta(n) cos(phi(m) - phi(n)) for the functional, where m and n are nearest-neighbor sites on the bond-center lattice. This form is analogous to the original continuum Ginzburg-Landau free-energy functional; the coefficients A, B, and C are determined from comparison with experiments. A combination of analytic approximations, numerical minimization, and Monte Carlo simulations is used to work out a number of consequences of the proposed functional for specific choices of A, B, and C as functions of hole density x and temperature T. There can be a rapid crossover of from small to large values as A changes sign from positive to negative on lowering T; this crossover temperature T-ms(x) is identified with the observed pseudogap temperature T*(x). The thermodynamic superconducting phase-coherence transition occurs at a lower temperature T-c(x), and describes superconductivity with d-wave symmetry for positive C. The calculated T-c(x) curve has the observed parabolic shape. The results for the superfluid density rho(s)(x, T), the local gap magnitude , the specific heat C-v(x, T) (with and without a magnetic field), as well as vortex properties, all obtained using the proposed functional, are compared successfully with experiments. We also obtain the electron spectral density as influenced by the coupling between the electrons and the correlation function of the pair amplitude calculated from the functional, and compare the results successfully with the electronic spectrum measured through angle resolved photoemission spectroscopy (ARPES). For the specific heat, vortex structure, and electron spectral density, only some of the final results are reported here; the details are presented in subsequent papers.

Conformational changes of the chaperone SecB upon binding to a model substrate - bovine pancreatic trypsin inhibitor (BPTI)

SecB is a homotetrameric cytosolic chaperone that forms part of the protein translocation machinery in E. coli. Due to SecB, nascent polypeptides are maintained in an unfolded translocation-competent state devoid of tertiary structure and thus are guided to the translocon. In vitro SecB rapidly binds to a variety of ligands in a non-native state. We have previously investigated the bound state conformation of the model substrate bovine pancreatic trypsin inhibitor (BPTI) as well as the conformation of SecB itself by using proximity relationships based on site-directed spin labeling and pyrene fluorescence methods. It was shown that SecB undergoes a conformational change during the process of substrate binding. Here, we generated SecB mutants containing but a single cysteine per subunit or an exposed highly reactive new cysteine after removal of the nearby intrinsic cysteines. Quantitative spin labeling was achieved with the methanethiosulfonate spin label (MTS) at positions C97 or E90C, respectively. Highfield (W-band) electron paramagnetic resonance (EPR) measurements revealed that with BPTI present the spin labels are exposed to a more polar/hydrophilic environment. Nanoscale distance measurements with double electron-electron resonance (DEER) were in excellent agreement with distances obtained by molecular modeling. Binding of BPTI also led to a slight change in distances between labels at C97 but not at E90C. While the shorter distance in the tetramer increased, the larger diagonal distance decreased. These findings can be explained by a widening of the tetrameric structure upon substrate binding much like the opening of two pairs of scissors.

MAPS: midline analysis and propagation of segmentation

Scenic word images undergo degradations due to motion blur, uneven illumination, shadows and defocussing, which lead to difficulty in segmentation. As a result, the recognition results reported on the scenic word image datasets of ICDAR have been low. We introduce a novel technique, where we choose the middle row of the image as a sub-image and segment it first. Then, the labels from this segmented sub-image are used to propagate labels to other pixels in the image. This approach, which is unique and distinct from the existing methods, results in improved segmentation. Bayesian classification and Max-flow methods have been independently used for label propagation. This midline based approach limits the impact of degradations that happens to the image. The segmented text image is recognized using the trial version of Omnipage OCR. We have tested our method on ICDAR 2003 and ICDAR 2011 datasets. Our word recognition results of 64.5% and 71.6% are better than those of methods in the literature and also methods that competed in the Robust reading competition. Our method makes an implicit assumption that degradation is not present in the middle row.

Effect of signal peptide on stability and folding of escherichia coli thioredoxin

The signal peptide plays a key role in targeting and membrane insertion of secretory and membrane proteins in both prokaryotes and eukaryotes. In E. coli, recombinant proteins can be targeted to the periplasmic space by fusing naturally occurring signal sequences to their N-terminus. The model protein thioredoxin was fused at its N-terminus with malE and pelB signal sequences. While WT and the pelB fusion are soluble when expressed, the malE fusion was targeted to inclusion bodies and was refolded in vitro to yield a monomeric product with identical secondary structure to WT thioredoxin. The purified recombinant proteins were studied with respect to their thermodynamic stability, aggregation propensity and activity, and compared with wild type thioredoxin, without a signal sequence. The presence of signal sequences leads to thermodynamic destabilization, reduces the activity and increases the aggregation propensity, with malE having much larger effects than pelB. These studies show that besides acting as address labels, signal sequences can modulate protein stability and aggregation in a sequence dependent manner.