EuroPhenome: a repository for high-throughput mouse phenotyping data.

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.

Fuzzy logic algorithm to extract specific interaction forces from atomic force microscopy data

The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.

Maintenance of polymorphism : a theoretical approach using multilocus systems

Résumé La thématique de cette thèse peut être résumée par le célèbre paradoxe de biologie évolutive sur le maintien du polymorphisme face à la sélection et par l'équation du changement de fréquence gamétique au cours du temps dû, à la sélection. La fréquence d'un gamète xi à la génération (t + 1) est: !!!Equation tronquée!!! Cette équation est utilisée pour générer des données utlisée tout au long de ce travail pour 2, 3 et 4 locus dialléliques. Le potentiel de l'avantage de l'hétérozygote pour le maintien du polymorphisme est le sujet de la première partie. La définition commune de l'avantage de l'hétérozygote n'etant applicable qu'a un locus ayant 2 allèles, cet avantage est redéfini pour un système multilocus sur les bases de précédentes études. En utilisant 5 définitions différentes de l'avantage de l'hétérozygote, je montre que cet avantage ne peut être un mécanisme général dans le maintien du polymorphisme sous sélection. L'étude de l'influence de locus non-détectés sur les processus évolutifs, seconde partie de cette thèse, est motivée par les travaux moléculaires ayant pour but de découvrir le nombre de locus codant pour un trait. La plupart de ces études sous-estiment le nombre de locus. Je montre que des locus non-détectés augmentent la probabilité d'observer du polymorphisme sous sélection. De plus, les conclusions sur les facteurs de maintien du polymorphisme peuvent être trompeuses si tous les locus ne sont pas détectés. Dans la troisième partie, je m'intéresse à la valeur attendue de variance additive après un goulot d'étranglement pour des traits sélectionés. Une études précédente montre que le niveau de variance additive après goulot d'étranglement augmente avec le nombre de loci. Je montre que le niveau de variance additive après un goulot d'étranglement augmente (comparé à des traits neutres), mais indépendamment du nombre de loci. Par contre, le taux de recombinaison a une forte influence, entre autre en regénérant les gamètes disparus suite au goulot d'étranglement. La dernière partie de ce travail de thèse décrit un programme pour le logiciel de statistique R. Ce programme permet d'itérer l'équation ci-dessus en variant les paramètres de sélection, recombinaison et de taille de populations pour 2, 3 et 4 locus dialléliques. Cette thèse montre qu'utiliser un système multilocus permet d'obtenir des résultats non-conformes à ceux issus de systèmes rnonolocus (la référence en génétique des populations). Ce programme ouvre donc d'intéressantes perspectives en génétique des populations. Abstract The subject of this PhD thesis can be summarized by one famous paradox of evolu-tionary biology: the maintenance of polymorphism in the face of selection, and one classical equation of theoretical population genetics: the changes in gametic frequencies due to selection and recombination. The frequency of gamete xi at generation (t + 1) is given by: !!! Truncated equation!!! This equation is used to generate data on selection at two, three, and four diallelic loci for the different parts of this work. The first part focuses on the potential of heterozygote advantage to maintain genetic polymorphism. Results of previous studies are used to (re)define heterozygote advantage for multilocus systems, since the classical definition is for one diallelic locus. I use 5 different definitions of heterozygote advantage. And for these five definitions, I show that heterozygote advantage is not a general mechanism for the maintenance of polymorphism. The study of the influence of undetected loci on evolutionary processes (second part of this work) is motivated by molecular works which aim at discovering the loci coding for a trait. For most of these works, some coding loci remains undetected. I show that undetected loci increases the probability of maintaining polymorphism under selection. In addition, conclusions about the factor that maintain polymorphism can be misleading if not all loci are considered. This is, therefore, only when all loci are detected that exact conclusions on the level of maintained polymorphism or on the factor(s) that maintain(s) polymorphism could be drawn. In the third part, the focus is on the expected release of additive genetic variance after bottleneck for selected traits. A previous study shows that the expected release of additive variance increases with an increase in the number of loci. I show that the expected release of additive variance after bottleneck increases for selected traits (compared with neutral), but this increase is not a function of the number of loci, but function of the recombination rate. Finally, the last part of this PhD thesis is a description of a package for the statistical software R that implements the Equation given above. It allows to generate data for different scenario regarding selection, recombination, and population size. This package opens perspectives for the theoretical population genetics that mainly focuses on one locus, while this work shows that increasing the number of loci leads not necessarily to straightforward results.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.

Reliable selfing rate estimates from imperfect population genetic data.

Genotypic frequencies at codominant marker loci in population samples convey information on mating systems. A classical way to extract this information is to measure heterozygote deficiencies (FIS) and obtain the selfing rate s from FIS = s/(2 - s), assuming inbreeding equilibrium. A major drawback is that heterozygote deficiencies are often present without selfing, owing largely to technical artefacts such as null alleles or partial dominance. We show here that, in the absence of gametic disequilibrium, the multilocus structure can be used to derive estimates of s independent of FIS and free of technical biases. Their statistical power and precision are comparable to those of FIS, although they are sensitive to certain types of gametic disequilibria, a bias shared with progeny-array methods but not FIS. We analyse four real data sets spanning a range of mating systems. In two examples, we obtain s = 0 despite positive FIS, strongly suggesting that the latter are artefactual. In the remaining examples, all estimates are consistent. All the computations have been implemented in a open-access and user-friendly software called rmes (robust multilocus estimate of selfing) available at http://ftp.cefe.cnrs.fr, and can be used on any multilocus data. Being able to extract the reliable information from imperfect data, our method opens the way to make use of the ever-growing number of published population genetic studies, in addition to the more demanding progeny-array approaches, to investigate selfing rates.

Quantification of Myocardial Perfusion Using 13N-ammonia PET: a Cross-Comparison Study on Analysis Software Packages - Carimas, PMOD and FlowQuant

Aim. Several software packages (SWP) and models have been released for quantification of myocardial perfusion (MP). Although they all are validated against something, the question remains how well their values agree. The present analysis focused on cross-comparison of three SWP for MP quantification of 13N-ammonia PET studies. Materials & Methods. 48 rest and stress MP 13N-ammonia PET studies of hypertrophic cardiomyopathy (HCM) patients (Sciagrà et al., 2009) were analysed with three SW packages - Carimas, PMOD, and FlowQuant - by three observers blinded to the results of each other. All SWP implement the one-tissue-compartment model (1TCM, DeGrado et al. 1996), and first two - the two-tissue-compartment model (2TCM, Hutchins et al. 1990) as well. Linear mixed model for the repeated measures was fitted to the data. Where appropriate we used Bland-Altman plots as well. The reproducibility was assessed on global, regional and segmental levels. Intraclass correlation coefficients (ICC), differences between the SWPs and between models were obtained. ICC≥0.75 indicated excellent reproducibility, 0.4≤ICC<0.75 indicated fair to good reproducibility, ICC<0.4 - poor reproducibility (Rosner, 2010). Results. When 1TCM MP values were compared, the SW agreement on global and regional levels was excellent, except for Carimas vs. PMOD at RCA: ICC=0.715 and for PMOD vs. FlowQuant at LCX:ICC=0.745 which were good. In segmental analysis in five segments: 7,12,13, 16, and 17 the agreement between all SWP was excellent; in the remaining 12 segments the agreement varied between the compared SWP. Carimas showed excellent agreement with FlowQuant in 13 segments and good in four - 1, 5, 6, 11: 0.687≤ICCs≤0.73; Carimas had excellent agreement with PMOD in 11 segments, good in five_4, 9, 10, 14, 15: 0.682≤ICCs≤0.737, and poor in segment 3: ICC=0.341. PMOD had excellent agreement with FlowQuant in eight segments and substantial-to-good in nine_1, 2, 3, 5, 6,8-11: 0.585≤ICCs≤0.738. Agreement between Carimas and PMOD for 2TCM was good at a global level: ICC=0.745, excellent at LCX (0.780) and RCA (0.774), good at LAD (0.662); agreement was excellent for ten segments, fair-to-substantial for segments 2, 3, 8, 14, 15 (0.431≤ICCs≤0.681), poor for segments 4 (0.384) and 17 (0.278). Conclusions. The three SWP used by different operators to analyse 13N-ammonia PET MP studies provide results that agree well at a global level, regional levels, and mostly well even at a segmental level. Agreement is better for 1TCM. Poor agreement at segments 4 and 17 for 2TCM needs further clarification.

Monitoring of noninvasive ventilation by built-in software of home bilevel ventilators: a bench study.

BACKGROUND: Current bilevel positive-pressure ventilators for home noninvasive ventilation (NIV) provide physicians with software that records items important for patient monitoring, such as compliance, tidal volume (Vt), and leaks. However, to our knowledge, the validity of this information has not yet been independently assessed. METHODS: Testing was done for seven home ventilators on a bench model adapted to simulate NIV and generate unintentional leaks (ie, other than of the mask exhalation valve). Five levels of leaks were simulated using a computer-driven solenoid valve (0-60 L/min) at different levels of inspiratory pressure (15 and 25 cm H(2)O) and at a fixed expiratory pressure (5 cm H(2)O), for a total of 10 conditions. Bench data were compared with results retrieved from ventilator software for leaks and Vt. RESULTS: For assessing leaks, three of the devices tested were highly reliable, with a small bias (0.3-0.9 L/min), narrow limits of agreement (LA), and high correlations (R(2), 0.993-0.997) when comparing ventilator software and bench results; conversely, for four ventilators, bias ranged from -6.0 L/min to -25.9 L/min, exceeding -10 L/min for two devices, with wide LA and lower correlations (R(2), 0.70-0.98). Bias for leaks increased markedly with the importance of leaks in three devices. Vt was underestimated by all devices, and bias (range, 66-236 mL) increased with higher insufflation pressures. Only two devices had a bias < 100 mL, with all testing conditions considered. CONCLUSIONS: Physicians monitoring patients who use home ventilation must be aware of differences in the estimation of leaks and Vt by ventilator software. Also, leaks are reported in different ways according to the device used.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

AltitudeOmics : impaired pulmonary gas exchange efficiency and blunted ventilatory acclimatization in humans with patent foramen ovale after 16 days at 5,260 m.

A patent foramen ovale (PFO), present in ∼40% of the general population, is a potential source of right-to-left shunt that can impair pulmonary gas exchange efficiency [i.e., increase the alveolar-to-arterial Po2 difference (A-aDO2)]. Prior studies investigating human acclimatization to high-altitude with A-aDO2 as a key parameter have not investigated differences between subjects with (PFO+) or without a PFO (PFO-). We hypothesized that in PFO+ subjects A-aDO2 would not improve (i.e., decrease) after acclimatization to high altitude compared with PFO- subjects. Twenty-one (11 PFO+) healthy sea-level residents were studied at rest and during cycle ergometer exercise at the highest iso-workload achieved at sea level (SL), after acute transport to 5,260 m (ALT1), and again at 5,260 m after 16 days of high-altitude acclimatization (ALT16). In contrast to PFO- subjects, PFO+ subjects had 1) no improvement in A-aDO2 at rest and during exercise at ALT16 compared with ALT1, 2) no significant increase in resting alveolar ventilation, or alveolar Po2, at ALT16 compared with ALT1, and consequently had 3) an increased arterial Pco2 and decreased arterial Po2 and arterial O2 saturation at rest at ALT16. Furthermore, PFO+ subjects had an increased incidence of acute mountain sickness (AMS) at ALT1 concomitant with significantly lower peripheral O2 saturation (SpO2). These data suggest that PFO+ subjects have increased susceptibility to AMS when not taking prophylactic treatments, that right-to-left shunt through a PFO impairs pulmonary gas exchange efficiency even after acclimatization to high altitude, and that PFO+ subjects have blunted ventilatory acclimatization after 16 days at altitude compared with PFO- subjects.

Adjusting for the environment in DEA: a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.