Intégration de méthodes de data mining dans le renseignement criminel : analyse par des structures issues de la théorie des graphes dans le profilage des stupéfiants

Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.

An ultra performance liquid chromatography-tandem MS assay for tamoxifen metabolites profiling in plasma: first evidence of 4'-hydroxylated metabolites in breast cancer patients.

There is increasing evidence that the clinical efficacy of tamoxifen, the first and most widely used targeted therapy for estrogen-sensitive breast cancer, depends on the formation of the active metabolites 4-hydroxy-tamoxifen and 4-hydroxy-N-desmethyl-tamoxifen (endoxifen). Large inter-individual variability in endoxifen plasma concentrations has been observed and related both to genetic and environmental (i.e. drug-induced) factors altering CYP450s metabolizing enzymes activity. In this context, we have developed an ultra performance liquid chromatography-tandem mass spectrometry method (UPLC-MS/MS) requiring 100 μL of plasma for the quantification of tamoxifen and three of its major metabolites in breast cancer patients. Plasma is purified by a combination of protein precipitation, evaporation at room temperature under nitrogen, and reconstitution in methanol/20 mM ammonium formate 1:1 (v/v), adjusted to pH 2.9 with formic acid. Reverse-phase chromatographic separation of tamoxifen, N-desmethyl-tamoxifen, 4-hydroxy-tamoxifen and 4-hydroxy-N-desmethyl-tamoxifen is performed within 13 min using elution with a gradient of 10 mM ammonium formate and acetonitrile, both containing 0.1% formic acid. Analytes quantification, using matrix-matched calibration samples spiked with their respective deuterated internal standards, is performed by electrospray ionization-triple quadrupole mass spectrometry using selected reaction monitoring detection in the positive mode. The method was validated according to FDA recommendations, including assessment of relative matrix effects variability, as well as tamoxifen and metabolites short-term stability in plasma and whole blood. The method is precise (inter-day CV%: 2.5-7.8%), accurate (-1.4 to +5.8%) and sensitive (lower limits of quantification comprised between 0.4 and 2.0 ng/mL). Application of this method to patients' samples has made possible the identification of two further metabolites, 4'-hydroxy-tamoxifen and 4'-hydroxy-N-desmethyl-tamoxifen, described for the first time in breast cancer patients. This UPLC-MS/MS assay is currently applied for monitoring plasma levels of tamoxifen and its metabolites in breast cancer patients within the frame of a clinical trial aiming to assess the impact of dose increase on tamoxifen and endoxifen exposure.

Desenvolupament d’una biblioteca per a la generació de diagrames vectorials basat en l’entorn gràfic de JAVA2D i aplicació d’aquesta biblioteca per a la implementació d’una eina per al desenvolupament de diagrames d’E/R

En aquest projecte es vol implementar una llibreria en Java, que proporcioni leseines necessàries per a crear diagrames i esquemes. Es vol proporcionar a la llibreria unconjunt d’objectes bàsics, també mètodes i funcionalitats suficients per a gestionaraquests objectes. Per altra part, es vol implementar una aplicació per a dissenyar diagrames Entitat-Relació que utilitzi aquesta llibreria

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

Transcriptional profiling of Gram-positive Arthrobacter in the phyllosphere: induction of pollutant degradation genes by natural plant phenolic compounds.

Arthrobacter chlorophenolicus A6 is a Gram-positive, 4-chlorophenol-degrading soil bacterium that was recently shown to be an effective colonizer of plant leaf surfaces. The genetic basis for this phyllosphere competency is unknown. In this paper, we describe the genome-wide expression profile of A.chlorophenolicus on leaves of common bean (Phaseolus vulgaris) compared with growth on agar surfaces. In phyllosphere-grown cells, we found elevated expression of several genes known to contribute to epiphytic fitness, for example those involved in nutrient acquisition, attachment, stress response and horizontal gene transfer. A surprising result was the leaf-induced expression of a subset of the so-called cph genes for the degradation of 4-chlorophenol. This subset encodes the conversion of the phenolic compound hydroquinone to 3-oxoadipate, and was shown to be induced not only by 4-chlorophenol but also hydroquinone, its glycosylated derivative arbutin, and phenol. Small amounts of hydroquinone, but not arbutin or phenol, were detected in leaf surface washes of P.vulgaris by gas chromatography-mass spectrometry. Our findings illustrate the utility of genomics approaches for exploration and improved understanding of a microbial habitat. Also, they highlight the potential for phyllosphere-based priming of bacteria to stimulate pollutant degradation, which holds promise for the application of phylloremediation.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Gene expression profiling of human glioblastomas for the identification of predictive factors and characterisation of molecular mechanism implicated in response to therapy and outcome

ABSTRACT Poor outcome for glioblastoma patients is largely due to resistance to chemoradiation therapy. While epigenetic inactivation of MGMT mediated DNA repair is highly predictive for benefit from the alkylating agent therapy Temozolomide, additional mechanisms for resistance associated with molecular alterations exist. Furthermore, new concepts in cancer suggest that resistance to treatment may be linked to cancer stem cells that escape therapy and act as source for tumour recurrence. We determined gene expression signatures associated with outcome in glioblastoma patients enrolled in a phase II and phase III clinical trial establishing the new combination therapy of radiation plus concomitant and adjuvant Temozolomide. Correlating stable gene clusters emerging from unsupervised analysis with survival of 42 treated patients identified a number of biological processes associated with outcome. Most prominent, a gene cluster dominated by HOX genes and comprising PROM1, was associated with resistance. PROM1 encodes CD133, a marker for a subpopulation of tumour cells enriched for glioblastoma stem- like cells. The core of this correlated HOX cluster was comprised in the top genes of a "self-renewal signature" defined in a mouse model for MLL-AF9 initiated leukaemia. The association of the HOX gene cluster with tumour resistance was confirmed in two external data sets of 146 malignant glioma As additional resistance factors we identified over-expression of the epidermal growth factor receptor gene, EGFR, while increased gene expression related to biological features of tumour host interaction, including markers for tumour vascular and cell adhesion, and innate immune response, were associated with better outcome. The "self-renewal" signature associated with resistance to the new combination chemoradiation therapy provides first clinical evidence that glioma stem like cells may implicated in resistance in a uniformly treated cohort of glioblastoma patients. This study underlines the need to target the tumour stem cell compartment, and provides some testable hypothesis for biological mechanisms relevant for malignant behaviour of glioblastoma that may be targeted in new treatment approaches. Résumé Le glioblastome, tumeur cérébrale primaire maligne la plus fréquente, est connue pour son mauvais pronostique. Des avancées chimiothérapeutiques récentes avec des agents alkylants comme le témozolomide (TMZ), ont permis une amélioration notable dans la survie de certains patients. Les bénéficiaires ont la caractéristique commune de présenter une particularité génétique, la methylation du MGMT (methylguanine methyltransferase). Néanmoins, d'autres mécanismes de résistance en fonction des aberrations moléculaires existent. Nous avons établi les profils d'expressions génétiques des patients traités par irradiation et TMZ dans des études cliniques de phase II et III. En combinant des méthodes non-supervisées et supervisées, de l'étude de la cohorte des patients traités nous avons découvert des groupes de gènes associés à la survie. Un ensemble de gènes contenant les gènes Hox semble lié au mécanisme de résistance au traitement. Récemment, les gènes Hox ont été décrits comme faisant partie d"une signature d'autorenouvellement (self-renewal) des cellules souches cancéreuses de la leucémie. L'autorenouvellement est un processus grâce auquel les cellules souches se maintiennent tout au long de la vie. Cette association à la résistance est confirmée dans deux autres études indépendantes. Un autre facteur de résistance au traitement est la surexpression du gène EGFR. D'autre part, deux groupes de gènes associés à la relation entre hôte-tumeur tels que les marqueurs des vaisseaux tumoraux et de la réponse immunitaire innée s'avèrent avoir un effet positif sur la survie des patients traités. La découverte de la signature d'autorenouvellement comme facteur de résistance à la nouvelle chimio-radiothérapie offre une preuve clinique que les cellules souches cancéreuses sont impliquées dans la résistance au traitement. If est donc logique de penser que le traitement ciblé contre des cellules souches cancéreuses va dans l'avenir permettre des thérapies anticancéreuses plus performantes.

Current approaches and challenges for the metabolite profiling of complex natural extracts.

Metabolite profiling is critical in many aspects of the life sciences, particularly natural product research. Obtaining precise information on the chemical composition of complex natural extracts (metabolomes) that are primarily obtained from plants or microorganisms is a challenging task that requires sophisticated, advanced analytical methods. In this respect, significant advances in hyphenated chromatographic techniques (LC-MS, GC-MS and LC-NMR in particular), as well as data mining and processing methods, have occurred over the last decade. Together, these tools, in combination with bioassay profiling methods, serve an important role in metabolomics for the purposes of both peak annotation and dereplication in natural product research. In this review, a survey of the techniques that are used for generic and comprehensive profiling of secondary metabolites in natural extracts is provided. The various approaches (chromatographic methods: LC-MS, GC-MS, and LC-NMR and direct spectroscopic methods: NMR and DIMS) are discussed with respect to their resolution and sensitivity for extract profiling. In addition the structural information that can be generated through these techniques or in combination, is compared in relation to the identification of metabolites in complex mixtures. Analytical strategies with applications to natural extracts and novel methods that have strong potential, regardless of how often they are used, are discussed with respect to their potential applications and future trends.

MyHits: improvements to an interactive resource for analyzing protein sequences.

The MyHits web site (http://myhits.isb-sib.ch) is an integrated service dedicated to the analysis of protein sequences. Since its first description in 2004, both the user interface and the back end of the server were improved. A number of tools (e.g. MAFFT, Jacop, Dotlet, Jalview, ESTScan) were added or updated to improve the usability of the service. The MySQL schema and its associated API were revamped and the database engine (HitKeeper) was separated from the web interface. This paper summarizes the current status of the server, with an emphasis on the new services.

Computer Tips and Tricks Newsletter, May, 2007

Performance & Development Solutions (PDS) publishes a variety of newsletters that include some great information about our programs and services. Some of the topics you may find include: Upcoming Seminars Current events or news related to training Recognition of achievements How-to section

Computer Tips and Tricks Newsletter, December, 2005

Performance & Development Solutions (PDS) publishes a variety of newsletters that include some great information about our programs and services. Some of the topics you may find include: Upcoming Seminars Current events or news related to training Recognition of achievements How-to section

Computer Tips and Tricks Newsletter, January, 2006

Performance & Development Solutions (PDS) publishes a variety of newsletters that include some great information about our programs and services. Some of the topics you may find include: Upcoming Seminars Current events or news related to training Recognition of achievements How-to section

Computer Tips and Tricks Newsletter, February, 2006

Performance & Development Solutions (PDS) publishes a variety of newsletters that include some great information about our programs and services. Some of the topics you may find include: Upcoming Seminars Current events or news related to training Recognition of achievements How-to section