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Date of Conference: 25-29 June 2005 Conference name: Thirteenth International Conference on Intelligent Systems for Molecular Biology, ISMB 2005 PATIKAweb provides a Web service for retrieving and analyzing biological pathways in PATIKA database, which currently contains data integrated from popular public pathway databases like Reactome. It features a user-friendly interface, dynamic visualization, advanced graph-theoretic queries for extracting biologically important phenomena and exporting facilities to various exchange formats.

Date of Conference: 31 July - 4 August 2004 Conference name: Twelfth International Conference on Intelligent Systems for Molecular Biology/Third European Conference on Computational Biology 2004 The PATIKA Project aims for an informatics infrastructure to cope with the inherently complex cellular pathway data and provides software tools with sophisticated visualization technology around a central database using an extensive ontology and data integration mechanisms. It also features advanced database querying, microarray data analysis, and automatic layout components.

Motivation: Microarray technology provides cell-scale expression data; however, analyzing this data is notoriously difficult. It is becoming clear that system-oriented methods are needed in order to best interpret this data. Combining microarray expression data with previously built pathway models may provide useful insight about the cellular machinery and reveal mechanisms that govern diseases. Given a qualitative state - transition model of the cellular network and an expression profile of RNA molecules, we would like to infer possible differential activity of the other molecules such as proteins on this network. Results: In this paper an efficient algorithm using a new approach is proposed to attack this problem. Using the regulation relations on the network, we determine possible scenarios that might lead to the expression profile, and qualitatively infer the activity differences of the molecules between test and control samples. Availability: This new analysis method has been implemented as part of a microarray data analysis component within PATIKA (Pathway Analysis Tool for Integration and Knowledge Acquisition), which is a software environment for pathway storage, integration and analysis. Facilities for easy analysis and visualization of the results is also provided. Contact: http://www.patika.org.

Cataloged from PDF version of article. Protein interactions govern most cellular processes, including signal transduction, transcriptional regulation and metabolism. Saccharomyces ceravisae is estimated to have 16,000 protein interactions. Appereantly only a small number of these interactions were formed ab initio (invention), rest of them were formed through gene duplications and exon shuffling (birth). Domains form functional units of a protein and are responsible for most of the interaction births, since they can be recombined and rearranged much more easily compared to innovation. Therefore groups of functionally similar, homologous interactions that evolved through births are expected to have a certain domain signature. Several high throughput techniques can detect interacting protein pairs, resulting in a rapidly growing corpus of protein interactions. Although there are several efforts for computationally integrating this data with literature and other high throughput data such as gene expression, annotation of this corpus is inadaquate for deriving interaction mechanism and outcome. Finding interaction homologies would allow us to annotate an unannotated interaction based on already annotated known interactions, or predict new ones. In this study we propose a probabilistic model for assigning interactions to homologous groups, according to their conserved domain similarities. Based on this model we have developed and implemented an Expectation-Maximization algorithm for finding the most likely grouping of an interaction set. We tested our algorithm with synthetic and real data, and showed that our initial results are very promising. Finally we propose several directions to improve this work Ayaz, Aslı M.S.

Dental fear and anxiety has been a common reaction among dental patients. Most of the patients who are having a fear of pain do try to avoid dental treatment. State-Trait Anxiety Inventory modified by Spielberger in 1964 can be employed to measure the level of dental anxiety which can allow practitioners to practice better on such patients and also enhance the success of dental management for both the practitioners and patients. This review aims to inform practitioners about the different methods to measure patients’ anxiety level in advance, Diş hekimliği pratiğinde hekimlerin korku ve kaygı reaksiyonları ile karşı karşıya kalması oldukça sık karşılaşılan bir durumdur. Hastalar ağrı beklentisi nedeniyle korkar ve dental tedavilerden kaçınırlar. Spielberger tarafından 1964 yılında geliştirilmiş olan Durumluk ve Sürekli Kaygı Envanteri ile bireylerin genel ve anlık kaygı düzeyleri ölçülerek anksiyete dereceleri tahmin edilebilmekte, böylelikle işlem öncesinde hekim hastaya özel önlemler alarak ve gerekli dental girişimlerde bulunarak dental tedavi başarı ve kalitesini hem hasta hem de hekim açısından artırabilmektedir. Bu derlemede hekimlere en sık kullanılan bu kaygı envanteri ile ilgili bilgi verilmesi amaçlanmıştır

During navigation, rodents continually sample the environment with their whiskers. How locomotion modulates neuronal activity in somatosensory cortex, and how it is integrated with whisker-touch remains unclear. Here, we compared neuronal activity in layer 2/3 (L2/3) and L5 of barrel cortex using calcium imaging in mice running in a tactile virtual reality. Both layers increase their activity during running and concomitant whisking, in the absence of touch. Fewer neurons are modulated by whisking alone. Whereas L5 neurons respond transiently to wall-touch during running, L2/3 neurons show sustained activity. Consistently, neurons encoding running-with-touch are more abundant in L2/3 and they encode the run-speed better during touch. Few neurons across layers were also sensitive to abrupt perturbations of tactile flow during running. In summary, locomotion significantly enhances barrel cortex activity across layers with L5 neurons mainly reporting changes in touch conditions and L2/3 neurons continually integrating tactile stimuli with running., Nature Communications, 10 (1), ISSN:2041-1723

Motivation: As the scientific curiosity in genome studies shifts toward identification of functions of the genomes in large scale, data produced about cellular processes at molecular level has been accumulating with an accelerating rate. In this regard, it is essential to be able to store, integrate, access and analyze this data effectively with the help of software tools. Clearly this requires a strong ontology that is intuitive, comprehensive and uncomplicated. Results: We define an ontology for an intuitive, comprehensive and uncomplicated representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information via collaboration, and supports manipulation of the stored data. In addition, it facilitates concurrent modifications to the data while maintaining its validity and consistency. Furthermore, novel structures for representation of multiple levels of abstraction for pathways and homologies is provided. Lastly, our ontology supports efficient querying of large amounts of data. We have also developed a software tool named pathway analysis tool for integration and knowledge acquisition (PATIKA) providing an integrated, multi-user environment for visualizing and manipulating network of cellular events. PATIKA implements the basics of our ontology. Availability: PATIKA version 1.0 beta is available upon request at http://www.patika.org