Analysis tenascin-C for suppression of Human Brain Tumor with Interference RNA

Glioblastoma multiforme (GBM) accounts for approximately 12-15% of intracranial neoplasms. The GBM remains refractory to therapy because of tumor heterogenity, local invasion, and non-uniform vascular permeability to drugs. Patients with GBM have the median survival of approximately 8-10 months, and for those cases where tumor recurs, the average time of tumor progression after therapy is only eight weeks. A combination of different treatment modes as surgery and chemo- or/and radiotherapy extend survival only for a short time, if any. Recently, tenascin-C (TN-C) as a dominant epitope in glioblastoma has been discovered. Tenascin-C is a multidomain large extracellular matrix glycoprotein composed of six monomers. The size of tenascin-C monomers (180-250kDa) varies as a result of an alternative splicing of the fibronectin repeats at the pre-mRNA level. For the first time we applied bioinformatic and molecular modeling procedures, for detailed analysis of the organization of tenascin-C and we performed bioinformatic analysis of tenascin-C gene. We showed the higher level of tenascin-C in the human tumor tissues: brain, intestine and breast. These results suggested a new role of tenascin-C as the potential tumor marker and drug target.

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Continous integration with PHP and Jenkins

Overview Continuous integration (CI) is a development practice which allows testing, building and checking the quality of the application in automated way without manual developer intervention. It requires developers to integrate code into a shared repository several times a day or every commit/merge to the given branch of the repository. Each check-in is then verified by an automated build, allowing teams to detect problems early. While PHP Continuous Integration (PHPCI) does not require the the code compilation as build” one can understand the set of task like testing and quality checks which are performed in timely manner or when the certain conditions are met. PHPCI can be performed on Jenkins Server. The detailed description of jenkins server configuration in is presented here. PHPCI requires PHing package which can be provided into application by Composer.

International Supercomputing Conference, Hamburg, Germany 23th June 2009

The International Supercomputing Conference is the Europe’s premier HPC event. The attendance allows observing trends science and technology of High Performance Computing for whole next year. 2009 edition achieved record numbers of attendees and exhibitors, a level of success even more impressive given the international economic crisis. With its move to Hamburg, ISC’09 reached a significantly higher level of attendance, bringing 1,670 HPC industry leaders. Research labs demonstrated their scientific applications of supercomputing in most recent fields such us GPGPU accelerators, clouds and green computing. Furthermore, this, ISC’09 also welcomed several first-time exhibitors. The exhibition brought countless highlights such as the demo of both the IS5000 40 Gb/s infniband switches and low-latency 10 Gigabit Ethernet. The attendance on ISC’09 allows to anticipate future development of ATLAS system and to present current achievements’ of ToK4nEDA team. Jakub Paś Jakub Paś Ja

Application and implementation of probabilistic profile-profile comparison methods for protein fold recognition

Fold recognition is a method of fold detecting and protein tertiary structure prediction applied for proteins lacking homologues sequences of known fold and structure deposited in the Protein Data Bank. They are based on assumption that there is strictly limited number of different protein folds in nature, mostly as a result of evolution and due to basic physical and chemical constraints of polypeptide chains. Fold recognition methods are useful for protein structure prediction, evolutionary analysis, metabolic pathways and enzymatic efficiency prediction, molecular docking and drug design. Currently there are about 1300 discovered and characterized protein folds in SCOP and CATH databases. Every newly discovered protein sequence has significant chances to be classified into one of those folds. Many different approaches have been proposed for finding the correct fold for a new sequence and it is often useful to include evolutionary information for query as well as for target proteins.

Jakub Paś

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