CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature and linked to an improved annotation system

Résumé: L'automatisation du séquençage et de l'annotation des génomes, ainsi que l'application à large échelle de méthodes de mesure de l'expression génique, génèrent une quantité phénoménale de données pour des organismes modèles tels que l'homme ou la souris. Dans ce déluge de données, il devient très difficile d'obtenir des informations spécifiques à un organisme ou à un gène, et une telle recherche aboutit fréquemment à des réponses fragmentées, voir incomplètes. La création d'une base de données capable de gérer et d'intégrer aussi bien les données génomiques que les données transcriptomiques peut grandement améliorer la vitesse de recherche ainsi que la qualité des résultats obtenus, en permettant une comparaison directe de mesures d'expression des gènes provenant d'expériences réalisées grâce à des techniques différentes. L'objectif principal de ce projet, appelé CleanEx, est de fournir un accès direct aux données d'expression publiques par le biais de noms de gènes officiels, et de représenter des données d'expression produites selon des protocoles différents de manière à faciliter une analyse générale et une comparaison entre plusieurs jeux de données. Une mise à jour cohérente et régulière de la nomenclature des gènes est assurée en associant chaque expérience d'expression de gène à un identificateur permanent de la séquence-cible, donnant une description physique de la population d'ARN visée par l'expérience. Ces identificateurs sont ensuite associés à intervalles réguliers aux catalogues, en constante évolution, des gènes d'organismes modèles. Cette procédure automatique de traçage se fonde en partie sur des ressources externes d'information génomique, telles que UniGene et RefSeq. La partie centrale de CleanEx consiste en un index de gènes établi de manière hebdomadaire et qui contient les liens à toutes les données publiques d'expression déjà incorporées au système. En outre, la base de données des séquences-cible fournit un lien sur le gène correspondant ainsi qu'un contrôle de qualité de ce lien pour différents types de ressources expérimentales, telles que des clones ou des sondes Affymetrix. Le système de recherche en ligne de CleanEx offre un accès aux entrées individuelles ainsi qu'à des outils d'analyse croisée de jeux de donnnées. Ces outils se sont avérés très efficaces dans le cadre de la comparaison de l'expression de gènes, ainsi que, dans une certaine mesure, dans la détection d'une variation de cette expression liée au phénomène d'épissage alternatif. Les fichiers et les outils de CleanEx sont accessibles en ligne (http://www.cleanex.isb-sib.ch/). Abstract: The automatic genome sequencing and annotation, as well as the large-scale gene expression measurements methods, generate a massive amount of data for model organisms. Searching for genespecific or organism-specific information througout all the different databases has become a very difficult task, and often results in fragmented and unrelated answers. The generation of a database which will federate and integrate genomic and transcriptomic data together will greatly improve the search speed as well as the quality of the results by allowing a direct comparison of expression results obtained by different techniques. The main goal of this project, called the CleanEx database, is thus to provide access to public gene expression data via unique gene names and to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and crossdataset comparisons. A consistent and uptodate gene nomenclature is achieved by associating each single gene expression experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of genes from model organisms, such as human and mouse. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing crossreferences to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resources, such as cDNA clones or Affymetrix probe sets. The Affymetrix mapping files are accessible as text files, for further use in external applications, and as individual entries, via the webbased interfaces . The CleanEx webbased query interfaces offer access to individual entries via text string searches or quantitative expression criteria, as well as crossdataset analysis tools, and crosschip gene comparison. These tools have proven to be very efficient in expression data comparison and even, to a certain extent, in detection of differentially expressed splice variants. The CleanEx flat files and tools are available online at: http://www.cleanex.isbsib. ch/.

A prospective observational study comparing a non-operator dependent automatic PWV analyser to pulse pressure, in assessing arterial stiffness in hemodialysis.

BACKGROUND: Chronic kidney disease (CKD) accelerates vascular stiffening related to age. Arterial stiffness may be evaluated measuring the carotid-femoral pulse wave velocity (PWV) or more simply, as recommended by KDOQI, monitoring pulse pressure (PP). Both correlate to survival and incidence of cardiovascular disease. PWV can also be estimated on the brachial artery using a Mobil-O-Graph; a non-operator dependent automatic device. The aim was to analyse whether, in a dialysis population, PWV obtained by Mobil-O-Graph (MogPWV) is more sensitive for vascular aging than PP. METHODS: A cohort of 143 patients from 4 dialysis units has been followed measuring MogPWV and PP every 3 to 6 months and compared to a control group with the same risk factors but an eGFR > 30 ml/min. RESULTS: MogPWV contrarily to PP did discriminate the dialysis population from the control group. The mean difference translated in age between the two populations was 8.4 years. The increase in MogPWV, as a function of age, was more rapid in the dialysis group. 13.3% of the dialysis patients but only 3.0% of the control group were outliers for MogPWV. The mortality rate (16 out of 143) was similar in outliers and inliers (7.4 and 8.0%/year). Stratifying patients according to MogPWV, a significant difference in survival was seen. A high parathormone (PTH) and to be dialysed for a hypertensive nephropathy were associated to a higher baseline MogPWV. CONCLUSIONS: Assessing PWV on the brachial artery using a Mobil-O-Graph is a valid and simple alternative, which, in the dialysis population, is more sensitive for vascular aging than PP. As demonstrated in previous studies PWV correlates to mortality. Among specific CKD risk factors only PTH is associated with a higher baseline PWV. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02327962.

Automatic target validation based on neuroscientific literature mining for tractography.

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Papaya seedlings growth using a low-cost, automatic watering controller

The study assessed growth and physiological parameters of 'Sunrise Golden' and 'Tainung 01' papaya seedlings grown in 280mL plastic tubes and watered using a low-cost automatic irrigation system adjusted to operate at substrate water tension for starting irrigation (STI) of 3.0, 6.0 or 9.0 kPa. The water depths applied by the dripping system and drainage were monitored during germination and seedling growth. Germination, emergence velocity index (EVI), leaf area, plant height, shoot and root dry weight, stomatal conductance, relative water content (RWC) and relative chlorophyll content (RCC) were evaluated. Soil nutrient levels were determined by electrical conductivity (EC). Water use efficiency (WUE) corresponded to the ratio of plant dry mass to depth of water applied. STI settings did not affect papaya germination or EVI. System configuration to 3.0 and 6.0 kPa STI exhibited the highest drainage and lowest EC and RCC, indicating soil nutrient loss and plant nutrient deficiency. Drainage was greater in tubes planted with the 'Tainung 01' variety, which developed smaller root systems and lower stomatal conductance than 'Sunrise Golden' seedlings. The highest values for shoot dry weight and WEU were obtained at 6.0 kPa STI for 'Sunrise Golden' (0.62 g and 0.69 g L-1) and at 9.0 kPa in 'Tainung 01' (0.35 g and 0.82 g L-1). RWC at 9.0 kPa STI was lower than at 3.0 kPa in both varieties. The results indicate that the low-cost technology developed for irrigation automation is promising. Even so, new studies are needed to evaluate low-flow irrigation systems as well as the nutrient and water needs of different papaya varieties.

Alzheimer Disease Diagnosis based on Automatic Spontaneous Speech Analysis

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to improvement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Search Interfaces on the Web: Querying and Characterizing

Current-day web search engines (e.g., Google) do not crawl and index a significant portion of theWeb and, hence, web users relying on search engines only are unable to discover and access a large amount of information from the non-indexable part of the Web. Specifically, dynamic pages generated based on parameters provided by a user via web search forms (or search interfaces) are not indexed by search engines and cannot be found in searchers’ results. Such search interfaces provide web users with an online access to myriads of databases on the Web. In order to obtain some information from a web database of interest, a user issues his/her query by specifying query terms in a search form and receives the query results, a set of dynamic pages that embed required information from a database. At the same time, issuing a query via an arbitrary search interface is an extremely complex task for any kind of automatic agents including web crawlers, which, at least up to the present day, do not even attempt to pass through web forms on a large scale. In this thesis, our primary and key object of study is a huge portion of the Web (hereafter referred as the deep Web) hidden behind web search interfaces. We concentrate on three classes of problems around the deep Web: characterization of deep Web, finding and classifying deep web resources, and querying web databases. Characterizing deep Web: Though the term deep Web was coined in 2000, which is sufficiently long ago for any web-related concept/technology, we still do not know many important characteristics of the deep Web. Another matter of concern is that surveys of the deep Web existing so far are predominantly based on study of deep web sites in English. One can then expect that findings from these surveys may be biased, especially owing to a steady increase in non-English web content. In this way, surveying of national segments of the deep Web is of interest not only to national communities but to the whole web community as well. In this thesis, we propose two new methods for estimating the main parameters of deep Web. We use the suggested methods to estimate the scale of one specific national segment of the Web and report our findings. We also build and make publicly available a dataset describing more than 200 web databases from the national segment of the Web. Finding deep web resources: The deep Web has been growing at a very fast pace. It has been estimated that there are hundred thousands of deep web sites. Due to the huge volume of information in the deep Web, there has been a significant interest to approaches that allow users and computer applications to leverage this information. Most approaches assumed that search interfaces to web databases of interest are already discovered and known to query systems. However, such assumptions do not hold true mostly because of the large scale of the deep Web – indeed, for any given domain of interest there are too many web databases with relevant content. Thus, the ability to locate search interfaces to web databases becomes a key requirement for any application accessing the deep Web. In this thesis, we describe the architecture of the I-Crawler, a system for finding and classifying search interfaces. Specifically, the I-Crawler is intentionally designed to be used in deepWeb characterization studies and for constructing directories of deep web resources. Unlike almost all other approaches to the deep Web existing so far, the I-Crawler is able to recognize and analyze JavaScript-rich and non-HTML searchable forms. Querying web databases: Retrieving information by filling out web search forms is a typical task for a web user. This is all the more so as interfaces of conventional search engines are also web forms. At present, a user needs to manually provide input values to search interfaces and then extract required data from the pages with results. The manual filling out forms is not feasible and cumbersome in cases of complex queries but such kind of queries are essential for many web searches especially in the area of e-commerce. In this way, the automation of querying and retrieving data behind search interfaces is desirable and essential for such tasks as building domain-independent deep web crawlers and automated web agents, searching for domain-specific information (vertical search engines), and for extraction and integration of information from various deep web resources. We present a data model for representing search interfaces and discuss techniques for extracting field labels, client-side scripts and structured data from HTML pages. We also describe a representation of result pages and discuss how to extract and store results of form queries. Besides, we present a user-friendly and expressive form query language that allows one to retrieve information behind search interfaces and extract useful data from the result pages based on specified conditions. We implement a prototype system for querying web databases and describe its architecture and components design.

Question Waves: A multicast query routing algorithm for social search

This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted

Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.

A conceptual model for grid learning services automatic composition

Peer-reviewed

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

Technological solution for the automatic replacement of the catalytic filaments in HWCVD

The degradation of the catalytic filaments is the main factor limiting the industrial implementation of the hot wire chemical vapor deposition (HWCVD) technique. Up to now, no solution has been found to protect the catalytic filaments used in HWCVD without compromising their catalytic activity. Probably, the definitive solution relies on the automatic replacement of the catalytic filaments. In this work, the results of the validation tests of a new apparatus for the automatic replacement of the catalytic filaments are reported. The functionalities of the different parts have been validated using a 0.2 mm diameter tungsten filament under uc-Si:H deposition conditions.

Automatic meter reading – benefits and applications

In liberalized electricity markets, which have taken place in many countries over the world, the electricity distribution companies operate in the competitive conditions. Therefore, accurate information about the customers’ energy consumption plays an essential role for the budget keeping of the distribution company and for correct planning and operation of the distribution network. This master’s thesis is focused on the description of the possible benefits for the electric utilities and residential customers from the automatic meter reading system usage. Major benefits of the AMR, illustrated in the thesis, are distribution network management, power quality monitoring, load modelling, and detection of the illegal usage of the electricity. By the example of the power system state estimation, it was illustrated that even the partial installation of the AMR in the customer side leads to more accurate data about the voltage and power levels in the whole network. The thesis also contains the description of the present situation of the AMR integration in Russia.