930 resultados para Protein Array Analysis -- methods


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The Iota, Kappa and Lambda commercial carrageenans are rarely pure and normally contain varying amounts of the other types of carrageenans. The exact amount of impurity depends on the seaweed source and extraction procedure. Then, different analysis methods have been applied for determination of the main constituents of carrageenans because these three carrageenans are extensively used in food, cosmetic and pharmaceutical industry. The electrophoresis of these compounds proved that the carrageenans are constituted by sulfated polysaccharides. These compounds were characterized by colorimetric methods and was observed that the Lambda carrageenan shown the greater value (33.38%) of sulfate. These polymers were examined by means of 13C NMR spectroscopy and infrared spectra. The polysaccharides consisted mainly of units alternating of sulfated galactoses and anhydrogalactoses. The aim of the study was also to test the inflammatory action of these different polysaccharides. A suitable model of inflammation is acute sterile inflammation of the rat hind limb induced by carrageenan. Paw edema was induced by injecting carrageenans (κ, ι and λ) in saline into the hind paw of a male Wistar rats (175–200 g). The pathway to acute inflammation by carrageenan (kappa, iota and lambda) were expressed as time-edema dependence and measured by paw edema volume. For this purpose, was used an apparatus (pakymeter), which makes it possible to measure the inflammation (swelling of the rat foot) with sufficient accuracy. The results showed that κ-carrageenan (1%) have an edema of 3.7 mm and the paw edema increase was time and dose dependent; the ι-carrageenan (0.2%) caused an edema of 4 mm and the λ-carrageenan (1%) caused an edema of 3.6 mm. Other model was used in this study based in the inflammation of pleura for comparatives studies. Injection of carrageenans into the pleural cavity of rat induced an acute inflammatory response characterized by fluid accumulation in the pleural cavity, a large number of neutrophils and raised NO production. The levels of NO were measured by Griess reactive. The ι-carrageenan caused the greater inflammation, because it has high concentration of nitrite/nitrate (63.478 nmoles/rat), exudato volume (1.52 ml) and PMNs (4902 x 103 cells). Quantitative evaluation of inflammations of rats is a useful and important parameter for the evaluation of the efficacy of anti-inflammatory drugs

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This document introduces the planned new search for the neutron Electric Dipole Moment at the Spallation Neutron Source at the Oak Ridge National Laboratory. A spin precession measurement is to be carried out using Ultracold neutrons diluted in a superfluid Helium bath at T = 0.5 K, where spin polarized 3He atoms act as detector of the neutron spin polarization. This manuscript describes some of the key aspects of the planned experiment with the contributions from Caltech to the development of the project.

Techniques used in the design of magnet coils for Nuclear Magnetic Resonance were adapted to the geometry of the experiment. Described is an initial design approach using a pair of coils tuned to shield outer conductive elements from resistive heat loads, while inducing an oscillating field in the measurement volume. A small prototype was constructed to test the model of the field at room temperature.

A large scale test of the high voltage system was carried out in a collaborative effort at the Los Alamos National Laboratory. The application and amplification of high voltage to polished steel electrodes immersed in a superfluid Helium bath was studied, as well as the electrical breakdown properties of the electrodes at low temperatures. A suite of Monte Carlo simulation software tools to model the interaction of neutrons, 3He atoms, and their spins with the experimental magnetic and electric fields was developed and implemented to further the study of expected systematic effects of the measurement, with particular focus on the false Electric Dipole Moment induced by a Geometric Phase akin to Berry’s phase.

An analysis framework was developed and implemented using unbinned likelihood to fit the time modulated signal expected from the measurement data. A collaborative Monte Carlo data set was used to test the analysis methods.

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© 2014 Cises This work is distributed with License Creative Commons Attribution-Non commercial-No derivatives 4.0 International (CC BY-BC-ND 4.0)

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This research aims to study dimensions of urban life in the contemporaneous city. It is an effort to understand the functioning of the contemporary city as an artifact that somehow affects social relations. The study focuses on the limits and possibilities of urbanity in the city today, understanding urbanity as a set of factors that favor wealth, diversity and spontaneity of public life. The research aims to show that cities today tend to criate fragmented urban life into at least one of the three urbanity dimensions: spatial dimension, social and temporal dimension. The study involves the analysis of two public spaces in Fortaleza (Praça do Ferreira and the open urban public spaces of the Centro Cultural Dragão do Mar), using Space Syntax Analysis methods and for Post Occupancy Evaluation procedures. Research shows that temporal dimension of urbanity is limited in the public spaces studied. In Praça do Ferreira, spatial and social dimensions are present, but their effects are limited by the temporal dimension. The Dragão do Mar, on the other hand, the spatial and social dimensions of urban life are more limited and more concentrated in time

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Ecomorphology is a science based on the idea that morphological differences among species could be associated with distinct biological and environmental pressures suffered by them. These differences can be studied employing morphological and biometric indexes denominated Ecomorphological attributes , representing standards that express characteristics of the individual in relation to its environment, and can be interpreted as indicators of life habits or adaptations suffered due its occupation of different habitats. This work aims to contribute for the knowledge of the ecomorphology of the Brazilian marine ichthyofauna, specifically from Galinhos, located at Rio Grande do Norte state. 10 different species of fish were studied, belonging the families Gerreidae (Eucinostomus argenteus), Haemulidae (Orthopristis ruber,Pomadasyscorvinaeformis,Haemulonaurolineatum,Haemulonplumieri,Haemulonsteindachneri), Lutjanidae (Lutjanus synagris), Paralichthyidae (Syaciummicrurum), Bothidae (Bothus ocellatus) and Tetraodontidae (Sphoeroidestestudineus), which were obtained during five collections, in the period time of September/2004 to April/2005, utilizing three special nets. The ecomorphological study was performed at the laboratory. Eight to ten samples of each fish specie were measured. Fifteen morphological aspects were considered to calculate twelve ecomorphological attributes. Multivariate statistical analysis methods such as Principal Component Analysis (PCA) and Cluster Analysis were done to identify ecmorphological patterns to describe the data set obtained. As results, H.aurolineatumwas the most abundant specie found (23,03%) and S.testudineusthe less one with 0,23%. The 1st Principal component showed variation of 60,03% with influence of the ecomorphological attribute related to body morphology, while the 2nd PC with 23,25% variation had influence of the ecomorphological attribute related to oral morphology. The Cluster Analiysis promoted the identification of three distinct groups Perciformes, Pleuronectiformes and Tetraodontiformes. Based on the obtained data, considering morphological characters differences among the species studied, we suggest that all of them live at the medium (E.argenteus,O.rubber, P.corvinaeformis,H.aurolineatum,H.plumieri,H.steindachneri,L.synagris) and bottom (S.micrurum,B.ocellatus,S.testudineus) region of column water.

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In the presented thesis work, meshfree method with distance fields is applied to create a novel computational approach which enables inclusion of the realistic geometric models of the microstructure and liberates Finite Element Analysis(FEA) from thedependance on and limitations of meshing of fine microstructural feature such as splats and porosity.Manufacturing processes of ceramics produce materials with complex porosity microstructure.Geometry of pores, their size and location substantially affect macro scale physical properties of the material. Complex structure and geometry of the pores severely limit application of modern Finite Element Analysis methods because they require construction of spatial grids (meshes) that conform to the geometric shape of the structure. As a result, there are virtually no effective tools available for predicting overall mechanical and thermal properties of porous materials based on their microstructure. This thesis is a separate handling and controls of geometric and physical computational models that are seamlessly combined at solution run time. Using the proposedapproach we will determine the effective thermal conductivity tensor of real porous ceramic materials featuring both isotropic and anisotropic thermal properties. This work involved development and implementation of numerical algorithms, data structure, and software.

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Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite’s Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.

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Objectives: People with obesity experience a range of physical and psychological ill-health outcomes. This study examined patients’ experiences of a group-based programme for the management of morbid obesity delivered within the UK National Health Service. The focus of the study was on the emerging dynamic of the group and patients’ perceptions of its impact on health outcomes. Design: A qualitative interview study was conducted and involved patients recruited from a Tier 3 bariatric service in South West England. Verbatim transcripts were analysed using thematic analysis. Methods: Twenty patients (12 females) with a BMI ≥ 35 kg/m2 participated in a semi-structured one-to-one interview. Participants had been registered with the bariatric service for at least 6 months. None of the participants had had bariatric surgery. Results: Most participants felt that they had benefited from participating in the group programme and talked about the group as a resource for lifestyle change. Participants’ narratives centred on the emergence of a sense of self based upon their participation in the group: establishing psychological connections to other patients, or shared social identity, was regarded as a key mechanism through which the programme's educational material was accessed, and underpinned the experience of social support within the group. Through interaction with other patients, involving the sharing of personal experiences and challenges, participants came to experience their weight ‘problem’ through a collective lens that they felt empowered them to initiate and sustain individual lifestyle change. Discussion: Bariatric care groups have the potential to support lifestyle change and weight loss and may help address the psychological needs of patients. Nurturing a sense of shared social identity amongst patients with morbid obesity should be a core aim of the care pathway and may provide the foundation for successful translation of dietetic content in group programmes.

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Mycobacteria of the Mycobacterium tuberculosis complex (MTBC) greatly affect humans and animals worldwide. The life cycle of mycobacteria is complex and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood. Recently, comparative genomics analyses have provided new insights into the evolution and adaptation of the MTBC to survive inside the host. However, most of this information has been obtained using M. tuberculosis but not other members of the MTBC such as M. bovis and M. caprae. In this study, the genome of three M. bovis (MB1, MB3, MB4) and one M. caprae (MB2) field isolates with different lesion score, prevalence and host distribution phenotypes were sequenced. Genome sequence information was used for whole-genome and protein-targeted comparative genomics analysis with the aim of finding correlates with phenotypic variation with potential implications for tuberculosis (TB) disease risk assessment and control. At the whole-genome level the results of the first comparative genomics study of field isolates of M. bovis including M. caprae showed that as previously reported for M. tuberculosis, sequential chromosomal nucleotide substitutions were the main driver of the M. bovis genome evolution. The phylogenetic analysis provided a strong support for the M. bovis/M. caprae clade, but supported M. caprae as a separate species. The comparison of the MB1 and MB4 isolates revealed differences in genome sequence, including gene families that are important for bacterial infection and transmission, thus highlighting differences with functional implications between isolates otherwise classified with the same spoligotype. Strategic protein-targeted analysis using the ESX or type VII secretion system, proteins linking stress response with lipid metabolism, host T cell epitopes of mycobacteria, antigens and peptidoglycan assembly protein identified new genetic markers and candidate vaccine antigens that warrant further study to develop tools to evaluate risks for TB disease caused by M. bovis/M.caprae and for TB control in humans and animals.

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Methicillin-resistant Staphylococcus aureus (MRSA) Sequence Type (ST)1, Clonal Complex(CC)1, SCCmec V is one of the major Livestock-Associated (LA-) lineages in pig farming industry in Italy and is associated with pigs in other European countries. Recently, it has been increasingly detected in Italian dairy cattle herds. The aim of this study was to analyse the differences between ST1 MRSA and methicillin-susceptible S. aureus (MSSA) from cattle and pig herds in Italy and Europe and human isolates. Sixty-tree animal isolates from different holdings and 20 human isolates were characterized by pulsed-field gel electrophoresis (PFGE), spa-typing, SCCmec typing, and by micro-array analysis for several virulence, antimicrobial resistance, and strain/host-specific marker genes. Three major PFGE clusters were detected. The bovine isolates shared a high (≥90% to 100%) similarity with human isolates and carried the same SCCmec type IVa. They often showed genetic features typical of human adaptation or present in human-associated CC1: Immune evasion cluster (IEC) genes sak and scn, or sea; sat and aphA3-mediated aminoglycoside resistance. Contrary, typical markers of porcine origin in Italy and Spain, like erm(A) mediated macrolide-lincosamide-streptograminB, and of vga(A)-mediated pleuromutilin resistance were always absent in human and bovine isolates. Most of ST(CC)1 MRSA from dairy cattle were multidrug-resistant and contained virulence and immunomodulatory genes associated with full capability of colonizing humans. As such, these strains may represent a greater human hazard than the porcine strains. The zoonotic capacity of CC1 LA-MRSA from livestock must be taken seriously and measures should be implemented at farm-level to prevent spill-over.

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Conventional rockmass characterization and analysis methods for geotechnical assessment in mining, civil tunnelling, and other excavations consider only the intact rock properties and the discrete fractures that are present and form blocks within rockmasses. Field logging and classification protocols are based on historically useful but highly simplified design techniques, including direct empirical design and empirical strength assessment for simplified ground reaction and support analysis. As modern underground excavations go deeper and enter into more high stress environments with complex excavation geometries and associated stress paths, healed structures within initially intact rock blocks such as sedimentary nodule boundaries and hydrothermal veins, veinlets and stockwork (termed intrablock structure) are having an increasing influence on rockmass behaviour and should be included in modern geotechnical design. Due to the reliance on geotechnical classification methods which predate computer aided analysis, these complexities are ignored in conventional design. Given the comparatively complex, sophisticated and powerful numerical simulation and analysis techniques now practically available to the geotechnical engineer, this research is driven by the need for enhanced characterization of intrablock structure for application to numerical methods. Intrablock structure governs stress-driven behaviour at depth, gravity driven disintegration for large shallow spans, and controls ultimate fragmentation. This research addresses the characterization of intrablock structure and the understanding of its behaviour at laboratory testing and excavation scales, and presents new methodologies and tools to incorporate intrablock structure into geotechnical design practice. A new field characterization tool, the Composite Geological Strength Index, is used for outcrop or excavation face evaluation and provides direct input to continuum numerical models with implicit rockmass structure. A brittle overbreak estimation tool for complex rockmasses is developed using field observations. New methods to evaluate geometrical and mechanical properties of intrablock structure are developed. Finally, laboratory direct shear testing protocols for interblock structure are critically evaluated and extended to intrablock structure for the purpose of determining input parameters for numerical models with explicit structure.

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Predicting the evolution of a coastal cell requires the identification of the key drivers of morphology. Soft coastlines are naturally dynamic but severe storm events and even human intervention can accelerate any changes that are occurring. However, when erosive events such as barrier breaching occur with no obvious contributory factors, a deeper understanding of the underlying coastal processes is required. Ideally conclusions on morphological drivers should be drawn from field data collection and remote sensing over a long period of time. Unfortunately, when the Rossbeigh barrier beach in Dingle Bay, County Kerry, began to erode rapidly in the early 2000’s, eventually leading to it breaching in 2008, no such baseline data existed. This thesis presents a study of the morphodynamic evolution of the Inner Dingle Bay coastal system. The study combines existing coastal zone analysis approaches with experimental field data collection techniques and a novel approach to long term morphodynamic modelling to predict the evolution of the barrier beach inlet system. A conceptual model describing the long term evolution of Inner Dingle Bay in 5 stages post breaching was developed. The dominant coastal processes driving the evolution of the coastal system were identified and quantified. A new methodology of long term process based numerical modelling approach to coastal evolution was developed. This method was used to predict over 20 years of coastal evolution in Inner Dingle Bay. On a broader context this thesis utilised several experimental coastal zone data collection and analysis methods such as ocean radar and grain size trend analysis. These were applied during the study and their suitability to a dynamic coastal system was assessed.

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The rise in population growth, as well as nutrient mining, has contributed to low agricultural productivity in Sub-Saharan Africa (SSA). A plethora of technologies to boost agricultural production have been developed but the dissemination of these agricultural innovations and subsequent uptake by smallholder farmers has remained a challenge. Scientists and philanthropists have adopted the Integrated Soil Fertility Management (ISFM) paradigm as a means to promote sustainable intensification of African farming systems. This comparative study aimed: 1) To assess the efficacy of Agricultural Knowledge and Innovation Systems (AKIS) in East (Kenya) and West (Ghana) Africa in the communication and dissemination of ISFM (Study I); 2) To investigate how specifically soil quality, and more broadly socio-economic status and institutional factors, influence farmer adoption of ISFM (Study II); and 3) To assess the effect of ISFM on maize yield and total household income of smallholder farmers (Study III). To address these aims, a mixed methodology approach was employed for study I. AKIS actors were subjected to social network analysis methods and in-depth interviews. Structured questionnaires were administered to 285 farming households in Tamale and 300 households in Kakamega selected using a stratified random sampling approach. There was a positive relationship between complete ISFM awareness among farmers and weak knowledge ties to both formal and informal actors at both research locations. The Kakamega AKIS revealed a relationship between complete ISFM awareness among farmers and them having strong knowledge ties to formal actors implying that further integration of formal actors with farmers’ local knowledge is crucial for the agricultural development progress. The structured questionnaire was also utilized to answer the query pertaining to study II. Soil samples (0-20 cm depth) were drawn from 322 (Tamale, Ghana) and 459 (Kakamega, Kenya) maize plots and analysed non-destructively for various soil fertility indicators. Ordinal regression modeling was applied to assess the cumulative adoption of ISFM. According to model estimates, soil carbon seemed to preclude farmers from intensifying input use in Tamale, whereas in Kakamega it spurred complete adoption. This varied response by farmers to soil quality conditions is multifaceted. From the Tamale perspective, it is consistent with farmers’ tendency to judiciously allocate scarce resources. Viewed from the Kakamega perspective, it points to a need for farmers here to intensify agricultural production in order to foster food security. In Kakamega, farmers with more acidic soils were more likely to adopt ISFM. Other household and farm-level factors necessary for ISFM adoption included off-farm income, livestock ownership, farmer associations, and market inter-linkages. Finally, in study III a counterfactual model was used to calculate the difference in outcomes (yield and household income) of the treatment (ISFM adoption) in order to estimate causal effects of ISFM adoption. Adoption of ISFM contributed to a yield increase of 16% in both Tamale and Kakamega. The innovation affected total household income only in Tamale, where ISFM adopters had an income gain of 20%. This may be attributable to the different policy contexts under which the two sets of farmers operate. The main recommendations underscored the need to: (1) improve the functioning of AKIS, (2) enhance farmer access to hybrid maize seed and credit, (3) and conduct additional multi-locational studies as farmers operate under varying contexts.

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Neisseria meningitidis serogroup B is the major etiological agent of meningitis and life-threatening sepsis, against which two vaccines are licensed. The 4CMenB vaccine is composed of three major protein antigens (fHbp, NHBA and NadA) and detergent-extracted outer membrane vesicles (DOMV) from the NZ98/254 strain. DOMV are safe, immunogenic and able to raise bactericidal antibodies, mainly attributed to the immunodominant PorA protein. Nevertheless, DOMV offer a complex reservoir of potentially immunogenic proteins, whose relative contribution in protection is still poorly characterized. By testing antisera from vaccinated infants in serum bactericidal assay, we observed that the addition of DOMV in the vaccine formulation enhanced breadth of coverage compared to recombinant proteins alone against a panel of 11 meningococcal strains mismatched for the vaccine antigens. To unravel the DOMV components involved in such protection, 30 DOMV antigens were cloned and expressed in Escherichia coli as recombinant proteins and/or in vesicles to maintain their native conformation. Samples obtained were both included in tailor-made protein-microarrays to immunoprofile the antibody repertoire raised by DOMV-containing formulations and were individually used for mouse immunization studies to assess their ability to induce bactericidal antibodies. The protein-array immunosignature of mouse DOMV/4CMenB antisera unveiled a subset of 8 DOMV-reactive proteins potentially responsible for the additional protective responses. The antisera derived from mouse immunizations showed high levels of antibodies and recognized the corresponding antigen across different meningococcal strains. Among the protein-array reactive antigens, OpcA, NspA and PorB induced antibodies able to kill 10 of the 11 genetically diverse meningococcal strains and the specificity of the protective role of OpcA and PorB was also confirmed in 4CMenB infant vaccinee sera. In conclusion, we identified additional PorA-independent antigens within DOMV involved in broadening the coverage of 4CMenB, thus supporting the key role played by vesicles in this multivalent formulation.

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The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.