Discovery of Functional Genes for Systemic Acquired Resistance in Arabidopsis Thaliana through Integrated Data Mining

Various data mining techniques combined with sequence motif information in the promoter region of genes were applied to discover functional genes that are involved in the defense mechanism of systemic acquired resistance (SAR) in Arabidopsis thaliana. A series of K-Means clustering with difference-in-shape as distance measure was initially applied. A stability measure was used to validate this clustering process. A decision tree algorithm with the discover-and-mask technique was used to identify a group of most informative genes. Appearance and abundance of various transcription factor binding sites in the promoter region of the genes were studied. Through the combination of these techniques, we were able to identify 24 candidate genes involved in the SAR defense mechanism. The candidate genes fell into 2 highly resolved categories, each category showing significantly unique profiles of regulatory elements in their promoter regions. This study demonstrates the strength of such integration methods and suggests a broader application of this approach.Diff\ue9rentes techniques d'exploration de donn\ue9es, combin\ue9es \ue0 de l'information sur le motif de s\ue9quence dans la r\ue9gion promotrice de g\ue8nes, ont \ue9t\ue9 appliqu\ue9es pour d\ue9couvrir les g\ue8nes fonctionnels qui interviennent dans le m\ue9canisme de d\ue9fense de la r\ue9sistance syst\ue9mique acquise (RSA ou SAR) chez Arabidopsis thaliana. On a initialement utilis\ue9 une s\ue9rie de classifications par les K moyennes et la diff\ue9rence de forme comme mesure de distance. On a utilis\ue9 une mesure de stabilit\ue9 pour valider ce processus de classification, et un algorithme d'arbre de d\ue9cision ainsi que la technique de d\ue9couverte et de masquage pour identifier un groupe de g\ue8nes sup\ue9rieurement informatifs. On a \ue9tudi\ue9 l'apparence et l'abondance de diff\ue9rents sites de liaison de facteurs de transcription dans la r\ue9gion promotrice des g\ue8nes. En combinant ces techniques, nous avons pu identifier 24 g\ue8nes candidats intervenant dans le m\ue9canisme de d\ue9fense de la RSA. Ces g\ue8nes candidats se classaient dans deux cat\ue9gories hautement r\ue9solues, chacune pr\ue9sentant des profils v\ue9ritablement uniques d'\ue9l\ue9ments r\ue9gulateurs dans leurs r\ue9gions promotrices. Cette \ue9tude d\ue9montre le potentiel de pareilles m\ue9thodes d'int\ue9gration et laisse entrevoir une plus vaste application de cette approche.Peer reviewed: YesNRC publication: Ye

Outcomes and Complications of Aggressive Resection Strategy for Pituitary Adenomas in Knosp Grade 4 With Transsphenoidal Endoscopy

Surgery for pituitary adenomas (PAs) with cavernous sinus (CS) invasion in Knosp grade 4 is a great challenge and whether to adopt a conservative or aggressive surgical strategy is controversial. The aim of this study is to provide the outcomes and complications of an aggressive resection strategy for Knosp grade 4 PAs with transsphenoidal endoscopic surgery. Outcomes and complications were retrospectively analyzed in 102 patients with Knosp grade 4 PAs. Among them, primary PAs were seen in 60 patients and recurrent PAs were seen in 42 cases. Gross total resection (GTR) of the entire tumor was achieved in 72 cases (70.6%), subtotal tumor resection (STR) in 18 cases (17.6%), and partial tumor resection (PTR) in 12 cases (11.8%). Additionally, GTR of the tumor within the CS was achieved in 82 patients (80.4%), STR in 17 patients (16.7%), and PTR in 3 patients (2.9%). Statistical analyses showed that both recurrent tumors and firm consistency tumors were adverse factors for complete resection (P<0.05). Patients with GTR of the entire tumor were more likely to have favorable endocrine and visual outcomes than those with incomplete resection (P<0.05). Overall, the most common surgical complication was new cranial nerve palsy (n=7, 6.8%). The incidence of internal carotid artery (ICA) injury and postoperative cerebrospinal fluid (CSF) leakage was 2.0% (n=2) and 5.9% (n=6), respectively. Six patients (5.9%) experienced tumor recurrence postoperatively. For experienced neuroendoscopists, an aggressive tumor resection strategy via transsphenoidal endoscopic surgery may be an effective and safe option for Knosp grade 4 PAs

An Approach to Automated Knowledge Discovery in Bioinformatics

Extensive data mining applications to bioinformatics research have shown that knowledge discovery requires repeated manual interventions, and that conglomerating and summarizing the results would be time consuming and sometimes error prone. To assist in efficiently applying data mining technologies in bioinformatics, we have developed Automation facilities in our data mining software suite. Experiences gained from case studies are extracted and presented as scenarios, which are sets of data processing and analysis operations for specific data mining objectives. Built as sequences of these predefined scenarios, procedures apply previously established data mining strategies to new data sets in an automated way. Automation also highlights the results particularly related to researchers' own areas of interest. We present insights into our automated knowledge discovery and two example scenarios extracted from one case study to demonstrate the usefulness of our approach.De nombreuses applications des techniques de fouille de donn\ue9es dans la recherche en bioinformatique ont d\ue9montr\ue9 que la d\ue9couverte des connaissances n\ue9cessitait des interventions manuelles r\ue9p\ue9t\ue9es, et que le regroupement et la r\ue9duction des r\ue9sultats prenaient beaucoup de temps et \ue9taient parfois sujets \ue0 des erreurs. Afin de faciliter une application efficace des technologies de la fouille de donn\ue9es en bioinformatique, nous avons d\ue9velopp\ue9 des fonctions d'automatisation dans notre suite logicielle de fouille de donn\ue9es. Les exp\ue9riences r\ue9alis\ue9es \ue0 partir d'\ue9tudes de cas sont extraites et pr\ue9sent\ue9es sous la forme de sc\ue9narios, c'est \ue0 dire des ensembles d'op\ue9rations d'analyse et de traitement des donn\ue9es visant des objectifs d'exploration des donn\ue9es sp\ue9cifiques. Construites sous la forme de s\ue9quences de ces sc\ue9narios pr\ue9d\ue9finis, des proc\ue9dures appliquent les strat\ue9gies de fouille de donn\ue9es \ue9tablies ant\ue9rieurement \ue0 de nouveaux ensembles de donn\ue9es, de fa\ue7on automatique. L'automatisation met \ue9galement en \ue9vidence les r\ue9sultats qui concernent plus particuli\ue8rement les domaines d'int\ue9r\ueats du chercheur. Nous pr\ue9sentons un aper\ue7u de nos m\ue9thodes automatis\ue9es de d\ue9couverte des connaissances ainsi que deux sc\ue9narios d'exemple tir\ue9s d'une \ue9tude de cas, afin de d\ue9montrer l'utilit\ue9 de notre approche.NRC publication: Ye

Data Mining: Understanding Data and Disease Modeling *

de l’informatio

An improved prediction method of subsequent commutation failure of an LCC-HVDC considering sequential control response

Abstract Subsequent commutation failure (SCF) can be easily generated during the first commutation failure (CF) recovery process in a line-commutated converter-based high voltage direct-current system. SCF poses a significant threat to the safe and stable operation of power systems, and accurate prediction of CF is thus important. However, SCF is affected by the operating characteristics of the main circuit and the coupling effects of sequential control response in the inverter station. These are difficult to predict accurately. In this paper, a new SCF prediction method considering the control response is proposed based on the physical principle of SCF. The time sequence and switching conditions of the controllers at different stages of the first CF recovery process are described, and the corresponding equations of commutation voltage affected by different controllers are derived. The calculation method of the SCF threshold voltage is proposed, and the prediction method is established. Simulations show that the proposed method can predict SCF accurately and provide useful tools to suppress SCF

A Novel Data Mining Technique for Gene Identification in Time-Series Gene Expression Data

The purpose of this study was to develop a method for identifying useful patterns in gene expression time-series data. We have developed a novel data mining approach that identifies interesting patterns. The method consists of a combination of data pre-processing as well as unsupervised and supervised learning techniques. To evaluate our approach, we have analyzed three time series data sets which investigate the temporal transcriptome changes that occur during: 1) the cell cycle of budding yeast (<em>S. cerevisiae</em>) [3], 2) the epithelial to mesenchymal transition induced by Transforming Growth Factor-?1 in mouse mammary epithelial BRI-JM01 cells, and 3) the program of differentiation induced by retinoic acid in human embryonal teratocarcinoma NT-2 cells. We present the results from all of our experiments, discuss the patterns discovered through the use of our approach and briefly explain future plans and directions for improving our method.La pr\ue9sente \ue9tude visait \ue0 \ue9laborer une m\ue9thode permettant d'identifier les profils utiles dans les s\ue9ries chronologiques de donn\ue9es d'expression de g\ue8nes. Nous avons mis au point une nouvelle approche d'extraction de donn\ue9es qui permet d'identifier les profils dignes d'int\ue9r\ueat. La m\ue9thode consiste en une combinaison de pr\ue9-traitement de donn\ue9es ainsi que de techniques d'apprentissage supervis\ue9 et non supervis\ue9. Pour \ue9valuer notre approche, nous avons analys\ue9 trois s\ue9ries chronologiques d'ensembles de donn\ue9es ayant trait aux variations temporelles du transcriptome qui se produisent durant : 1) le cycle cellulaire de la levure lors du bourgeonnement (<em>S. cerevisiae</em>) [3]; 2) la transition de cellules \ue9pith\ue9liales \ue0 m\ue9senchymateuses que subissent les cellules mammaires BRI JM01 de souris sous l'effet du facteur de croissance transformant ?1; et 3) la diff\ue9renciation induite par l'acide r\ue9tino\uefque chez les cellules NT 2 de t\ue9ratocarcinome humain. Nous pr\ue9sentons les r\ue9sultats de toutes nos exp\ue9riences, discutons des profils d\ue9couverts au moyen de notre approche et expliquons bri\ue8vement nos plans futurs et l'orientation que nous pr\ue9voyons prendre pour perfectionner notre m\ue9thode.NRC publication: Ye

A novel pattern based clustering methodology for time-series microarray data

Identification of co-expressed genes sharing similar biological behaviours is an essential step in functional genomics. Traditional clustering techniques are generally based on overall similarity of expression levels and often generate clusters with mixed profile patterns. A novel pattern recognition method for selecting co-expressed genes based on rate of change and modulation status of gene expression at each time interval is proposed in this paper. This method is capable of identifying gene clusters consisting of highly similar shapes of expression profiles and modulation patterns. Furthermore, we develop a quality index based on the semantic similarity in gene annotations to assess the likelihood of a cluster being a co-regulated group. The effectiveness of the proposed methodology is demonstrated by applying it to the well-known yeast sporulation dataset and an in-house cancer genomics dataset.L'identification de g\ue8nes coexprim\ue9s qui ont des comportements biologiques semblables est une \ue9tape essentielle en g\ue9nomique fonctionnelle. Les techniques classiques de groupement se fondent g\ue9n\ue9ralement sur la similitude globale des niveaux d'expression et g\ue9n\ue8rent souvent des groupes aux profils mixtes. Nous proposons dans cet article une nouvelle m\ue9thode de reconnaissance des profils pour le choix des g\ue8nes coexprim\ue9s d'apr\ue8s le taux de changement et la modulation de l'expression g\ue9nique \ue0 chaque intervalle. Cette m\ue9thode permet d'identifier des groupements de g\ue8nes dont la forme des profils d'expression et des profils de modulation est tr\ue8s similaire. De plus, nous avons \ue9tabli un indice de qualit\ue9 bas\ue9 sur la similarit\ue9 s\ue9mantique dans les annotations g\ue9niques pour \ue9valuer la probabilit\ue9 qu'un groupement soit un groupe cor\ue9gul\ue9. Nous d\ue9montrons l'efficacit\ue9 de la m\ue9thode propos\ue9e en l'appliquant \ue0 l'ensemble bien connu de donn\ue9es sur la sporulation de levures et \ue0 un ensemble de donn\ue9es g\ue9nomiques internes sur le cancer.NRC publication: Ye

A novel pattern based clustering methodology for time-series microarray data

Identification of co-expressed genes sharing similar biological behaviours is an essential step in functional genomics. Traditional clustering techniques are generally based on overall similarity of expression levels and often generate clusters with mixed profile patterns. A novel pattern recognition method for selecting co-expressed genes based on rate of change and modulation status of gene expression at each time interval is proposed in this paper. This method is capable of identifying gene clusters consisting of highly similar shapes of expression profiles and modulation patterns. Furthermore, we develop a quality index based on the semantic similarity in gene annotations to assess the likelihood of a cluster being a co-regulated group. The effectiveness of the proposed methodology is demonstrated by applying it to the well-known yeast sporulation dataset and an in-house cancer genomics dataset.L'identification de g\ue8nes coexprim\ue9s qui ont des comportements biologiques semblables est une \ue9tape essentielle en g\ue9nomique fonctionnelle. Les techniques classiques de groupement se fondent g\ue9n\ue9ralement sur la similitude globale des niveaux d'expression et g\ue9n\ue8rent souvent des groupes aux profils mixtes. Nous proposons dans cet article une nouvelle m\ue9thode de reconnaissance des profils pour le choix des g\ue8nes coexprim\ue9s d'apr\ue8s le taux de changement et la modulation de l'expression g\ue9nique \ue0 chaque intervalle. Cette m\ue9thode permet d'identifier des groupements de g\ue8nes dont la forme des profils d'expression et des profils de modulation est tr\ue8s similaire. De plus, nous avons \ue9tabli un indice de qualit\ue9 bas\ue9 sur la similarit\ue9 s\ue9mantique dans les annotations g\ue9niques pour \ue9valuer la probabilit\ue9 qu'un groupement soit un groupe cor\ue9gul\ue9. Nous d\ue9montrons l'efficacit\ue9 de la m\ue9thode propos\ue9e en l'appliquant \ue0 l'ensemble bien connu de donn\ue9es sur la sporulation de levures et \ue0 un ensemble de donn\ue9es g\ue9nomiques internes sur le cancer.NRC publication: Ye

Proteolysis and multimerization regulate signaling along the two-component regulatory system AdeRS

International audienceBacterial two-component regulatory systems are ubiquitous environment-sensing signal transducers involved in pathogenesis and antibiotic resistance. The Acinetobacter baumannii two-component regulatory system AdeRS is made up of a sensor histidine kinase AdeS and a cognate response regulator AdeR, which together reduce repression of the multidrug-resistant efflux pump AdeABC. Herein we demonstrate that an N-terminal intrinsically disordered tail in AdeR is important for the upregulation of adeABC expression, although it greatly increases the susceptibility of AdeR to proteasome-mediated degradation. We also show that AdeS assembles into a hexameric state that is necessary for its full histidine kinase activity, which appears to occur via cis autophosphorylation. Taken together, this study demonstrates new structural mechanisms through which two-component systems can transduce environmental signals to impact gene expression and enlightens new potential antimicrobial approach by targeting two-component regulatory systems