A copula-based method for synthetic microarray data generation

In this work, we propose a copula-based method to generate synthetic gene expression data that account for marginal and joint probability distributions features captured from real data. Our method allows us to implant significant genes in the synthetic dataset in a controlled manner, giving the possibility of testing new detection algorithms under more realistic environments.

Stationarity analysis of historical flood series in France and Spain (14th-20th centuries)

Interdisciplinary frameworks for studying natural hazards and their temporal trends have an important potential in data generation for risk assessment, land use planning, and therefore the sustainable management of resources. This paper focuses on the adjustments required because of the wide variety of scientific fields involved in the reconstruction and characterisation of flood events for the past 1000 years. The aim of this paper is to describe various methodological aspects of the study of flood events in their historical dimension, including the critical evaluation of old documentary and instrumental sources, flood-event classification and hydraulic modelling, and homogeneity and quality control tests. Standardized criteria for flood classification have been defined and applied to the Isère and Drac floods in France, from 1600 to 1950, and to the Ter, the Llobregat and the Segre floods, in Spain, from 1300 to 1980. The analysis on the Drac and Isère data series from 1600 to the present day showed that extraordinary and catastrophic floods were not distributed uniformly in time. However, the largest floods (general catastrophic floods) were homogeneously distributed in time within the period 1600¿1900. No major flood occurred during the 20th century in these rivers. From 1300 to the present day, no homogeneous behaviour was observed for extraordinary floods in the Spanish rivers. The largest floods were uniformly distributed in time within the period 1300-1900, for the Segre and Ter rivers.

Estimating slope and level change in N=1 designs

The current study proposes a new procedure for separately estimating slope change and level change between two adjacent phases in single-case designs. The procedure eliminates baseline trend from the whole data series prior to assessing treatment effectiveness. The steps necessary to obtain the estimates are presented in detail, explained, and illustrated. A simulation study is carried out to explore the bias and precision of the estimators and compare them to an analytical procedure matching the data simulation model. The experimental conditions include two data generation models, several degrees of serial dependence, trend, level and/or slope change. The results suggest that the level and slope change estimates provided by the procedure are unbiased for all levels of serial dependence tested and trend is effectively controlled for. The efficiency of the slope change estimator is acceptable, whereas the variance of the level change estimator may be problematic for highly negatively autocorrelated data series.

Towards an emotion-driven interactive music system: ridging the gaps between affect, physiology and sound generation

Report for the scientific sojourn at the Stanford University from January until June 2007. Music is well known for affecting human emotional states, yet the relationship between specific musical parameters and emotional responses is still not clear. With the advent of new human-computer interaction (HCI) technologies, it is now possible to derive emotion-related information from physiological data and use it as an input to interactive music systems. Providing such implicit musical HCI will be highly relevant for a number of applications including music therapy, diagnosis, nteractive gaming, and physiologically-based musical instruments. A key question in such physiology-based compositions is how sound synthesis parameters can be mapped to emotional states of valence and arousal. We used both verbal and heart rate responses to evaluate the affective power of five musical parameters. Our results show that a significant correlation exists between heart rate and the subjective evaluation of well-defined musical parameters. Brightness and loudness showed to be arousing parameters on subjective scale while harmonicity and even partial attenuation factor resulted in heart rate changes typically associated to valence. This demonstrates that a rational approach to designing emotion-driven music systems for our public installations and music therapy applications is possible.

"Next-generation" Sequencing (NGS): The new genomic revolution

In the past 5 years "Next-generation" Sequencing (NGS) technologies have transformed genomics by delivering fast, inexpensive and accurate genomeinformation changing the way we think about scientific approaches in basic,applied and clinical research. The inexpensive production of large volumes ofsequence data is the main advantage over the automated Sanger method,making this new technology useful for many applications. In this chapter, a brieftechnical review of NGS technologies is given, along with the keys to NGSsuccess and a broad range of applications for NGS technologies.

Nanoparticles in SiH4-Ar plasma: Modelling and comparison with experimental data

Experimental and theoretical investigations for growth of silicon nanoparticles (4 to 14 nm) in radio frequency discharge were carried out. Growth processes were performed with gas mixtures of SiH4 and Ar in a plasma chemical reactor at low pressure. A distinctive feature of presented kinetic model of generation and growth of nanoparticles (compared to our earlier model) is its ability to investigate small"critical" dimensions of clusters, determining the rate of particle production and taking into account the influence of SiH2 and Si2Hm dimer radicals. The experiments in the present study were extended to high pressure (≥20 Pa) and discharge power (≥40 W). Model calculations were compared to experimental measurements, investigating the dimension of silicon nanoparticles as a function of time, discharge power, gas mixture, total pressure, and gas flow.

The Besançon Galaxy Model renewed. I. Constraints on the Galactic thin disc evolution from Tycho data

Context. The understanding of Galaxy evolution can be facilitated by the use of population synthesis models, which allow to test hypotheses on the star formation history, star evolution, as well as chemical and dynamical evolution of the Galaxy. Aims. The new version of the Besanc¸on Galaxy Model (hereafter BGM) aims to provide a more flexible and powerful tool to investigate the Initial Mass Function (IMF) and Star Formation Rate (SFR) of the Galactic disc. Methods. We present a new strategy for the generation of thin disc stars which assumes the IMF, SFR and evolutionary tracks as free parameters. We have updated most of the ingredients for the star count production and, for the first time, binary stars are generated in a consistent way. We keep in this new scheme the local dynamical self-consistency as in Bienayme et al (1987). We then compare simulations from the new model with Tycho-2 data and the local luminosity function, as a first test to verify and constrain the new ingredients. The effects of changing thirteen different ingredients of the model are systematically studied. Results. For the first time, a full sky comparison is performed between BGM and data. This strategy allows to constrain the IMF slope at high masses which is found to be close to 3.0, excluding a shallower slope such as Salpeter"s one. The SFR is found decreasing whatever IMF is assumed. The model is compatible with a local dark matter density of 0.011 M pc−3 implying that there is no compelling evidence for significant amount of dark matter in the disc. While the model is fitted to Tycho2 data, a magnitude limited sample with V<11, we check that it is still consistent with fainter stars. Conclusions. The new model constitutes a new basis for further comparisons with large scale surveys and is being prepared to become a powerful tool for the analysis of the Gaia mission data.

Analysis of the mitochondrial DNA of Schizophrenia patients by next generation sequencing

Mitochondrial DNA (mtDNA), a maternally inherited 16.6-Kb molecule crucial for energy production, is implicated in numerous human traits and disorders. It has been hypothesized that the presence of mutations in the mtDNA may contribute to the complex genetic basis of schizophreniadisease, due to the evidence of maternal inheritance and the presence of schizophrenia symptoms in patients affected of a mitochondrial disorder related to a mtDNA mutation. The present project aims to study the association of variants of mitochondrial DNA (mtDNA), and an increased risk of schizophrenia in a cohort of patients and controls from the same population. The entire mtDNA of 55 schizophrenia patients with an apparent maternal transmission of the disease and 38 controls was sequenced by Next Generation Sequencing (Ion Torrent PGM, Life Technologies) and compared to the reference sequence. The current method for establishing mtDNA haplotypes is Sanger sequencing, which is laborious, timeconsuming, and expensive. With the emergence of Next Generation Sequencing technologies, this sequencing process can be much more quickly and cost-efficiently. We have identified 14 variants that have not been previously reported. Two of them were missense variants: MTATP6 p.V113M and MTND5 p.F334L ,and also three variants encoding rRNA and one variant encoding tRNA. Not significant differences have been found in the number of variants between the two groups. We found that the sequence alignment algorithm employed to align NGS reads played a significant role in the analysis of the data and the resulting mtDNA haplotypes. Further development of the bioinformatics analysis and annotation step would be desirable to facilitate the application of NGS in mtDNA analysis.

The Besançon Galaxy Model renewed. I. Constraints on the Galactic thin disc evolution from Tycho data

Context. The understanding of Galaxy evolution can be facilitated by the use of population synthesis models, which allow to test hypotheses on the star formation history, star evolution, as well as chemical and dynamical evolution of the Galaxy. Aims. The new version of the Besanc¸on Galaxy Model (hereafter BGM) aims to provide a more flexible and powerful tool to investigate the Initial Mass Function (IMF) and Star Formation Rate (SFR) of the Galactic disc. Methods. We present a new strategy for the generation of thin disc stars which assumes the IMF, SFR and evolutionary tracks as free parameters. We have updated most of the ingredients for the star count production and, for the first time, binary stars are generated in a consistent way. We keep in this new scheme the local dynamical self-consistency as in Bienayme et al (1987). We then compare simulations from the new model with Tycho-2 data and the local luminosity function, as a first test to verify and constrain the new ingredients. The effects of changing thirteen different ingredients of the model are systematically studied. Results. For the first time, a full sky comparison is performed between BGM and data. This strategy allows to constrain the IMF slope at high masses which is found to be close to 3.0, excluding a shallower slope such as Salpeter"s one. The SFR is found decreasing whatever IMF is assumed. The model is compatible with a local dark matter density of 0.011 M pc−3 implying that there is no compelling evidence for significant amount of dark matter in the disc. While the model is fitted to Tycho2 data, a magnitude limited sample with V<11, we check that it is still consistent with fainter stars. Conclusions. The new model constitutes a new basis for further comparisons with large scale surveys and is being prepared to become a powerful tool for the analysis of the Gaia mission data.

Copy number variations of colorectal cancer by whole exome sequencing data

Colorectal cancer (CRC) is the third most common cancer and the fourth leading cause of cancer death worldwide. About 85% of the cases of CRC are known to have chromosomal instability, an allelic imbalance at several chromosomal loci, and chromosome amplification and translocation. The aim of this study is to determine the recurrent copy number variant (CNV) regions present in stage II of CRC through whole exome sequencing, a rapidly developing targeted next-generation sequencing (NGS) technology that provides an accurate alternative approach for accessing genomic variations. 42 normal-tumor paired samples were sequenced by Illumina Genome Analyzer. Data was analyzed with Varscan2 and segmentation was performed with R package R-GADA. Summary of the segments across all samples was performed and the result was overlapped with DEG data of the same samples from a previous study in the group1. Major and more recurrent segments of CNV were: gain of chromosome 7pq(13%), 13q(31%) and 20q(75%) and loss of 8p(25%), 17p(23%), and 18pq(27%). This results are coincident with the known literature of CNV in CRC or other cancers, but our methodology should be validated by array comparative genomic hybridisation (aCGH) profiling, which is currently the gold standard for genetic diagnosis of CNV.