A realization of this project will result in creation of the innovative anticancer “pro-pharmaceuticals” characterized by high effectivity and selectivity with accompanying minimalized side effects of the foreseen therapy. Research will be focused on designing, obtaining and in vitro validation of recombinant proteins called immunoendotoxins able to selectively binding, internalization and cancerous cells killing. The most important element of each immunoendotoxin will be an effector domain of a human origin thus minimalizing possible immunogenicity of the proteins. Low immunogenicity in association with known benefits of immunotoxins-based strategies will result in very potent anticancer therapeuticals.
…2. Kryterium oceny ofert: • Cena 100% (stawka brutto za roboczogodzinę) 3. Sposób dokonywania oceny: Zamawiający dokona wyboru oferty o najniższej cenie spośród ofert zgodnych z wymogami. W przypadku przedstawienia…
Structural genomics is a wide term describing the determination of a structure representation based on information contained in the genome, and at present is almost exclusively limited to the proteins. Although in common understanding genetic information means “genes and their encoded protein products”, thousands of human genes produce transcripts which are biologically important but they do not produce proteins. Furthermore, even though the sequence of the human DNA is known by now, the meaning of the most of the sequences still remains unknown. It is very likely that a large amount of genes has been highly underestimated, mainly because the actual gene finders work well only for large, highly expressed, evolutionary conserved protein-coding genes. Most of those genome elements encode RNA from which transfer and ribosomal RNAs are the classical examples. But beside these well-known molecules there is a vast unknown world of tiny RNAs that might play a crucial role in a number of cellular processes. Those elements are named Noncoding RNAs (ncRNA) and they perform their function without transcription to the protein product. Here, we propose the development of the integrated bioinformatics platform that is specifically addressed for detecting, verifying, and classifying noncoding RNAs. This complex approach to “computational RNomics” will provide a pipeline which will be capable of detecting RNA motifs with low sequence conservation. It will also integrate the RNA motif prediction which should significantly improve the quality of the RNA homologues searching.
Deciphering the information on genome sequences in terms of the biological function of the genes and proteins is a major challenge of the post-genomic era. Currently, the bulk of function assignments for newly sequenced genomes is performed using bioinformatics tools that infer the function of a gene on the basis of sequence similarity with other genes of known function. It is now well recognised that these primary, sequence similarity-based function annotation procedures are frequently inaccurate and error prone. Continuing to use them without clearly defining the limits of their applicability would lead to an unmanageable propagation of errors that could jeopardise progress in Biology. On the other hand, various novel bodies of data and resources are becoming available. These provide information on context-based aspects of the biological function of genes, namely on physical and functional interactions between genes and proteins, and on whole networks and processes. In parallel structural genomics efforts world wide are providing a much better coverage of the structural motifs adopted by proteins and on their interactions. The availability of these additional and novel data offers an unprecedented opportunity for the development of methods for incorporating higher-level functional features into the annotation pipeline.
The GeneFun project aims at addressing these two important issues. The issue of annotation errors will de addressed by developing criteria for evaluating the reliability of the annotations currently available in databases. These criteria will be used to assign reliability scores to these annotations and will be incorporated into standard annotation pipelines, for future use. The issue of incorporating higher-level features into functional annotations will be addressed by combining sequence and structure information in order to identify non-linear functional features (e.g. interaction sites), and by integrating available and newly developed methods for inferring function from higher-level and context-based information (protein domain architecture, protein-protein interaction, genomic context such as gene order etc.).
To achieve these aims several European groups with strong track record in developing novel methods and analyses in comparative genomics, structural- and systems- oriented bioinformatics, and in information technology, have teamed up with an experimental group from Canada, which is well known for its outstanding achievements in the field of structural and functional proteomics. The expected output of the GeneFun project is: improved procedures for inferring function on the basis of sequence similarity, a set of procedures for predicting non-linear functional features from sequence and 3D structure in a more automated way, and benchmarked procedures for predicting context-based functional features. Major efforts will be devoted to devising protocols that optimally combine the results from several methods. In particular Web-based servers to the individual and combined procedures will be developed, and made available to the scientific community. The community will be introduced to these new tools through open workshops and training sessions.
This project concerns the design of cryptographic schemes that are secure even if implemented on not-secure devices. The motivation for this work comes from an observation that most of the real-life attacks on cryptographic devices do not break their mathematical foundations, but exploit vulnerabilities of their implementations. This concerns both the cryptographic software executed on PCs (that can be attacked by viruses), and the implementations on hardware (that can be subject to the side-channel attacks). Typically, fixing this problem was left to the practitioners, since it was a common belief that theory cannot be of any help here. However, new exciting results in cryptography suggest that this view was too pessimistic: there exist methods to design cryptographic protocols in such a way that they are secure even if the hardware on which they are executed cannot be fully trusted. The goal of this project is to investigate these methods further, unify them in a solid mathematical theory (many of them were developed independently), and propose new ideas in this area. The project will be mostly theoretical (although some practical experiments may be performed). Our main interest lies within the theory of private circuits, bounded-retrieval model, physically-observable cryptography, and human-assisted cryptography. We view these theories just as the point of departure, since the field is largely unexplored and we expect to witness completely new ideas soon.
Enzymes are extremely powerful natural catalysts able to perform almost any type of chemical reaction while being mild by nature and highly specific. In fact, the delicate functioning of enzymes forms the basis of every living creature. The catalytic potential of enzymes is more and more appreciated by the industry as many industrial processes rely on these sophisticated catalysts. However, the number of reactions catalyzed by enzymes is restricted as enzymes only have evolved to catalyze reactions that are physiologically relevant. Furthermore, enzymes have adapted to the direct (cellular) environment in which they have to function (e.g. operative at ambient temperature, resilient towards proteolysis, catalytic turnover rate should fit with metabolic enzyme partners). This excludes the existence of enzymes that do not fit within boundaries set by nature. It is a great challenge to go beyond these natural boundaries and develop methodologies to design ‘unnatural’ tailor-made enzymes. Ideally it should become possible to (re)design enzymes to convert pre-defined substrates. Such designer enzymes could theoretically exhibit unsurpassed catalytic properties and, obviously, will be of significant interest for industrial biotechnology. The OXYGREEN project aims at the design and construction of novel oxygenating enzymes (designer oxygenases) for the production of compounds that can be used in medicine, food and agriculture and the development of novel powerful and generic enzyme redesign tools for this purpose. The enzymes and whole-cell biocatalysts that will be developed should catalyze the specific incorporation of oxygen to afford synthesis of bioactive compounds in a selective and clean way, with minimal side products and with no use of toxic materials. For this, generic platform technologies (novel high-throughput methodology and methods for engineering dedicated host cells) will be developed that allow effective structure-inspired directed evolution of enzyme.
High intelligence quotient, exaggerated social and political awareness and libertarian ethical principles are incompatible with the environment of slowly developing countries with widespread corruption and general lack of perspectives. Individuals suffering from this incompatibility syndrome search for and find relief in substance abuse of which regular Marijuana consumption is by far the mildest. The objective of the project is to assess whether Marijuana consumption is an effective method to reduce IQ and frustration and improve compatibility with the environment. As part of the project we will follow selected adult individuals from Polish scientific and cultural elites and monitor their mental and psychological development. We will also provide access to Marijuana produced under strict quality control to prevent intoxication with black market products that could negatively affect the reliability of our analysis of effects of THC consumption. More at thc.bioinfo.pl.