No description available.

L’Imagerie par Résonance Magnétique (IRM) est une belle application de la physique et constitue sans aucun doute l’une des techniques les plus performantes d’imagerie médicale. Basée sur le phénomène de la Résonance Magnétique Nucléaire (RMN) du proton contenu dans les molécules d’eau, l’IRM permet d’investiguer en coupes les tissus mous du corps, sur base de contrastes différents. La méthode est non-invasive et n’utilise pas de radiations ionisantes. En plus des données morphologiques, l’IRM permet également d’obtenir des informations fonctionnelles et physiologiques. De nos jours, plus de 10 000 unités IRM existent dans le monde et des millions d’examens sont réalisés chaque année. La technique est en constant développement et le domaine de recherches est multidisciplinaire. Il concerne aussi bien les développements méthodologiques (imagerie rapide, imagerie de diffusion, etc.) que technologiques (imagerie à haut champ, systèmes de gradients à commutation rapide, etc.), le point central des recherches étant l’amélioration de la qualité des images et la diminution du temps d’acquisition. Ceci implique l'optimisation des différentes séquences IRM (séries d'impulsions radiofréquence et de gradients de champ magnétique) tenant compte des contraintes imposées par le matériel, ainsi que le développement et l'optimisation du matériel lui-même. Cette thèse est consacrée au design avancé des séquences d’impulsions et contribue donc à l'optimisation des schémas d’acquisition en IRM. En particulier, le présent travail est focalisé sur la compréhension et l’amélioration d’un certain type de séquences rapides, employant des échos de gradients : les séquences Steady-State Free Precession (SSFP) et plus précisément les séquences dites balanced-SSFP. Dans ce genre de schéma d’acquisition, le système est excité rapidement et périodiquement, conduisant à l’établissement d’un état stationnaire de l’aimantation. La première partie de la thèse est consacrée à une analyse approfondie des propriétés du signal dans une séquence balanced-SSFP, à la fois à l’état stationnaire et à l’état transitoire. Ensuite, de nouveaux schémas d’acquisition sont développés sur base de calculs analytiques et de simulations numériques et sont ensuite testés expérimentalement. D’une part, une manipulation de l’état stationnaire est présentée en vue de supprimer le signal de la graisse sur les images (qui peut être gênant pour le diagnostic de certaines lésions ou maladies). D’autre part, l’application d’une phase de préparation en vue d’obtenir un contraste basé sur le degré de diffusion des molécules d’eau dans les tissus est analysée en détails, afin d’améliorer la qualité d’image produite par des séquences de diffusion existantes. La présente thèse constitue donc un travail de recherches théoriques et expérimentales, allant de la conception de nouveaux schémas d’acquisition à leur expérimentation sur volontaires, en passant par leur implémentation sur un imageur IRM. Ce travail a été réalisé au sein de l’Unité d’IRM – Radiologie de l’Hôpital Erasme, sous la direction de Thierry Metens, Docteur en Sciences et Physicien IRM.

Heart failure is a complex clinical syndrome in which the heart cannot pump sufficient blood and nutrients to the organs in the body. Increasingly, alterations in cardiac energetics are being implicated as playing an important role in the pathogenesis of heart failure. An understanding of specific metabolic switches which occur during the development of heart failure in patients would be greatly beneficial as a new diagnostic method and for the development of new therapies for patients with failing hearts. This thesis deals with the non-invasive assessment of metabolism in the heart. New magnetic resonance imaging (MRI) methods for metabolic characterization of the heart using hyperpolarized carbon-13 MRI are presented. Spatially resolved images of hyperpolarized 13C substrates and their downstream products can provide insight into real-time metabolic processes occurring in vivo, within minutes of injection of a pre-polarized 13C-labeled substrate. Conventional 3D spectroscopic acquisitions require in excess of 100 excitations, making it challenging to acquire full cardiac and respiratory-gated, whole-heart metabolic volumes. Each of the developments described in this thesis is intended to advance cardiac hyperpolarized 13C metabolic imaging towards a routine, clinical exam which can be used for prognosis and treatment optimization in patients with cardiovascular disease. The major technical development is a new interleaved-frequency, time-resolved MRI pulse sequence that can provide robust and reliable measurements of cardiac metabolic signals. The technique was applied to several realistic pre-clinical models of cardiac disease and the work presented will hopefully lead towards significant improvement in the management of patients with heart failure.

Heart failure is a complex clinical syndrome in which the heart cannot pump sufficient blood and nutrients to the organs in the body. Increasingly, alterations in cardiac energetics are being implicated as playing an important role in the pathogenesis of heart failure. An understanding of specific metabolic switches which occur during the development of heart failure in patients would be greatly beneficial as a new diagnostic method and for the development of new therapies for patients with failing hearts. This thesis deals with the non-invasive assessment of metabolism in the heart. New magnetic resonance imaging (MRI) methods for metabolic characterization of the heart using hyperpolarized carbon-13 MRI are presented. Spatially resolved images of hyperpolarized 13C substrates and their downstream products can provide insight into real-time metabolic processes occurring in vivo, within minutes of injection of a pre-polarized 13C-labeled substrate. Conventional 3D spectroscopic acquisitions require in excess of 100 excitations, making it challenging to acquire full cardiac and respiratory-gated, whole-heart metabolic volumes. Each of the developments described in this thesis is intended to advance cardiac hyperpolarized 13C metabolic imaging towards a routine, clinical exam which can be used for prognosis and treatment optimization in patients with cardiovascular disease. The major technical development is a new interleaved-frequency, time-resolved MRI pulse sequence that can provide robust and reliable measurements of cardiac metabolic signals. The technique was applied to several realistic pre-clinical models of cardiac disease and the work presented will hopefully lead towards significant improvement in the management of patients with heart failure.

The in situ proximity ligation assay (in situ PLA) is an immunoassay that enables directvisualisation of single protein targets or protein interactions in cell or tissue samples. This project revolves around designing and introducing several novel multiplexable components tobe used in conjunction with Olink Bioscience's Duolink product line. In this report, a novel in silico approach to DNA oligomer interaction design is presented. Using this in silico method, a multiplexed system of DNA oligomers has been designed andevaluated using in situ PLA and fluorescence microscopy.

No description available.

Spread spectrum techniques have a number of different applications, including range finding, synchronisation, anti-jamming systems and multiple access communication systems. In each of these applications the properties of the resulting systems depend heavily on the family of spreading sequences employed. As such, the design of spreading sequences is an important area of research. Two areas of spreading sequence design are of particular interest in this work, combination techniques and Interference Free Window (IFW) sequences. Combination techniques allow a new sequence family to be constructed by combining two or more existing families. Such an approach allows some of the desirable properties of the components to be maintained, whilst mitigating the components' disadvantages. In addition, it can facilitate the construction of large families at a greatly reduced computational cost. Combination families are considered through the construction of two new classes of sequences, modified Unified Complex Hadamard Transform (UCHT) sequences, and combination Oppermann sequences, respectively based on UCHT sequences and periodic Oppermann sequences. Numerical optimisation techniques are employed to demonstrate the favourable performance of sequences from these classes compared to conventional families. Second, IFW sequences are considered. In systems where approximate, but not perfect, synchronisation between different users can be maintained, IFW sequences can be employed to greatly reduce both interference between users and interference resulting from multipath spread of each user's signal. Large Area Synchronous (LAS) sequences are a class of sequences which both result from combination techniques and exhibit an IFW. LAS sequences are produced by combining Large Area (LA) sequences and LS sequences. They have been demonstrated to be applicable to multiple access communication systems, particularly through their use in LAS2000, which was proposed for third generation mobile telephony. Work to date has been restricted to only a very small range of examples of these families. In order to examine a wider range of LAS sequences, the construction and resulting properties of LA and LS families are considered. The conditions an LA family must satisfy are codified here, and algorithms which can be used to construct LA families with given parameters are presented. The construction of LS sequences is considered, and relationship between each of the parameters used in this construction and the properties of the final family is examined. Using this expanded understanding of both these sequence families, a far wider range of LAS families, potentially applicable to a wider range of applications, can be considered. Initially, the merits of proposed sequences are considered primarily through their correlation properties. Both maximum and mean squared correlation values are considered, depending on the context. In order to demonstrate their practical applicability, combination Oppermann, modified UCHT and LAS sequences are employed in a simulated communications system, and the resulting bit error rates are examined.

Aufgrund ihrer Selbstorganisationseigenschaften besitzt DNA ein großes Potential für den Einsatz in Bottom-up-Techniken der Nanotechnologie. So erlaubt DNA eine genau definierte Anordnung von Bauelementen im Abstand von nur wenigen Nanometern. Zum Beispiel kann ein regelmäßig mit Metallclustern oder Proteinen bestücktes DNA-Netz als Katalysator oder in Sensoren eingesetzt werden. DNA wird außerdem als Templat für Nanodrähte benutzt und kann deshalb eine wichtige Rolle in einer zukünftigen Nanoelektronik spielen. DNA-Strukturen entstehen meist durch Selbsassemblierung von Einzelstrangmolekülen während einer Hybridisierung. Die Assemblierung wird dabei durch die Basensequenzen der beteiligten Einzelstränge gesteuert. Das bedeutet: Die Basensequenzen der Einzelstränge definieren die Gestalt der entstehenden Struktur. Diese Dissertation stellt Regeln für Sequenzkonfigurationen vor, welche DNA-Einzelstränge erfüllen müssen, damit die erfolgreiche Selbstassemblierung einer gewünschten Zielstruktur erfolgreich sein kann. Das Grundprinzip dieser Regeln ist eine Minimierung der Länge von Basenfehlpaarungen. Es wird ein Algorithmus entwickelt, welcher diese Regeln umsetzt und für beliebige Zielstrukturen passende Sequenzkonfigurationen erzeugt. Der Algorithmus arbeitet vollautomatisch und ist für die meisten Strukturgrößen sehr schnell. Eine Java-Implementierung des Algorithmus mit Namen Seed ist unter http://nano.tu-dresden.de/~jseiffert/Seed/ frei erhältlich. Abschließend präsentiert diese Arbeit ein Experiment, in welchem eine Reihe von Double-Crossover-(DX)-Molekülen zu einer langen Kette verbunden werden. Die Sequenzkonfiguration für dieses Experiment wurde mit Seed erstellt und zeigt die Anwendungsfähigkeit des vorgestellten Algorithmus. / Due to its self-recognition abilities, DNA has a great potential to disclose new bottom-up routes towards nanofabrication. DNA allows well-defined arrangements of building blocks with only a few nanometer distance. For example, a DNA network with regulary attached metal beeds or proteins can be placed on a surface to act as a catalyst or a sensor. DNA can also be used as template for nanowires and, therefore, might play a major role in future nanoelectronics. DNA structures mostly assemble themselves by hybridization of single stranded DNA molecules. The self-assemby process is controlled by the base sequences of the single strands: The sequence configuration defines the shape of the resulting structure. This thesis introduces rules for sequence configuration that DNA strands must fullfill to produce a desired target structure in a hybridazation process. The basic principle of these rules is a mismatch minimization. An algorithm is presented, which generates suitable sequence configurations according to the introduced rules. The algorithm can handle any DNA structures, works full-automatically, and for most structure dimensions, is very fast. A Java-implementation of the algorithm called Seed is freely available at http://nano.tu-dresden.de/~jseiffert/Seed/. Finally, this work describes a structure building experiment, where a number of double crossover (DX) molecules were concatenated into a long chain. The sequence configuration for this experiment was generated by the developed program Seed showing the use of the presented algorithm.

Structural and functional annotation of sequences of putative proteins encoded in the newly sequenced genomes pose an important challenge. While much progress has been made towards high throughput experimental techniques for structure determination and functional assignment to proteins, most of the current genome-wide annotation systems rely on computational methods to derive cues on structure and function based on relationship with related proteins of known structure and/or function. Evolutionary pressure on proteins, forces the retention of sequence features that are important for structure and function. Thus, if it can be established that two proteins have descended from a common ancestor, then it can be inferred that the structural fold and biological function of the two proteins would be similar. Homology based information transfer from one protein to another has played a central role in the understanding of evolution of protein structures, functions and interactions. Many algorithmic improvements have been developed over the past two decades to recognize homologues of a protein from sequence-based searches alone, but there are still a large number of proteins without any functional annotation. The sensitivity of the available methods can be further enhanced by indirect comparisons with the help of intermediately-related sequences which link related families. However, sequence-based homology searches in the current protein sequence space are often restricted to the family members, due to the paucity of natural intermediate sequences that can act as linkers in detecting remote homologues. Thus a major goal of this thesis is to develop computational methods to fill up the sparse regions in the protein sequence space with computationally designed protein-like sequences and thereby create a continuum of protein sequences, which could aid in detecting remote homologues. Such designed sequences are further assessed for their effectiveness in detection of distant evolutionary relationships and functional annotation of proteins with unknown structure and function. Another important aspect in structural bioinformatics is to gain a good understanding of protein sequence - structure - function paradigm. Functional annotations by comparisons of protein sequences can be further strengthened with the addition of structural information; however, instances of functional divergence and convergence may lead to functional mis-annotations. Therefore, a systematic analysis is performed on the fold–function associations using binding site information and their inter-relationships using binding site similarity networks. Chapter 1 provides a background on proteins, their evolution, classification and structural and functional features. This chapter also describes various methods for detection of remote similarities and the role of protein sequence design methods in detection of distant relatives for protein annotation. Pitfalls in prediction of protein function from sequence and structure are also discussed followed by an outline of the thesis. Chapter 2 addresses the problem of paucity of available protein sequences that can act as linkers between distantly related proteins/families and help in detection of distant evolutionary relationships. Previous efforts in protein sequence design for remote homology detection and design of sequences corresponding to specific protein families are discussed. This chapter describes a novel methodology to computationally design intermediately-related protein sequences between two related families and thus fill-in the gaps in the sequence space between the related families. Protein families as defined in SCOP database are represented as position specific scoring matrices (PSSMs) and these profiles of related protein families within a fold are aligned using AlignHUSH -a profile-profile alignment method. Guided by this alignment, the frequency distribution of the amino acids in the two families are combined and for each aligned position a residue is selected based on the combined probability to occur in the alignment positions of two families. Each computationally designed sequence is then subjected to RPS-BLAST searches against an all profile pool representing all protein families. Artificial sequences that detect both the parent profiles with no hits corresponding to other folds qualify as ‘designed intermediate sequences’. Various scoring schemes and divergence levels for the design of protein-like sequences are investigated such that these designed sequences intersperse between two related families, thereby creating a continuum in sequence space. The method is then applied on a large scale for all folds with two or more families and resulted in the design of 3,611,010 intermediately-related sequences for 27,882 profile-profile alignments corresponding to 374 folds. Such designed sequences are generic in nature and can be augmented in any sequence database of natural protein sequences. Such enriched databases can then be queried using any sequence-based remote homology detection method to detect distant relatives. The next chapter (Chapter 3) explores the ability of these designed intermediate sequences to act as linkers of two related families and aid in detection of remote homologues. To assess the applicability of these designed sequences two types of databases have been generated, namely a CONTROL database containing protein sequences from natural sequence databases and an AUGMENTED database in which designed sequences are included in the database of natural sequences. Detailed assessments of the utility of such designed sequences using traditional sequence-based searches in the AUGMENTED database showed an enhanced detection of remote homologues for almost 74% of the folds. For over 3,000 queries, it is demonstrated that designed sequences are positioned as suitable linkers, which mediate connections between distantly related proteins. Using examples from known distant evolutionary relationships, we demonstrate that homology searches in augmented databases show an increase of up to 22% in the number of /correct evolutionary relationships "discovered". Such connections are reported with high sensitivities and very low false positive rates. Interestingly, they fill-in void and sparse regions in sequence space and relate distant proteins not only through multiple routes but also through SCOP-NrichD database, SUPFAM+ database, SUPERFAMILY database, protein domain library queried by pDomTHREADER and HHsearch against HMM library of SCOP families. This approach detected evolutionary relationships for almost 20% of all the families with no known structure or function. Detailed report of predictions for 614 DUFs, their fold and species distribution are provided in this chapter. These predictions are then enriched with GO terms and enzyme information wherever available. A detailed discussion is provided for few of the interesting assignments: DUF1636, DUF1572 and DUF2092 which are functionally annotated as thioredoxin-like 2Fe-2S ferredoxin, putative metalloenzyme and lipoprotein localization factors respectively. These 614 novel structure-function relationships of which 193 are supported by consensus between at least two of the five methods, can be accessed from http://proline.biochem.iisc.ernet.in/RHD_DUFS/. Protein functions can be appreciated better in the light of evolutionary information from their structures. Chapter 6 describes a database of evolutionary relationships identified between Pfam families. The grouping of Pfam families is important to obtain a better understanding on evolutionary relationships and in obtaining clues to functions of proteins in families of yet unknown function. Many structural genomics initiative projects have made considerable efforts in solving structures and bridging the growing gap between protein sequences and their structures. The results of such experiments suggest that often the newly solved structure using X-ray crystallography or NMR methods has structural similarity to a protein with already known structure. These relationships often remain undetected due to unavailability of structural information. Therefore, SUPFAM+ database aims to detect such distant relationships between Pfam families by mapping the Pfam families and SCOP domain families. The work presented in this chapter describes the generation of SUPFAM+ database using a sensitive AlignHUSH method to uncover hidden relationships. Firstly, Pfam families are queried against a profile database of SCOP families to derived Pfam-SCOP associations, and then Pfam families are queried against Pfam database to derive Pfam-Pfam relationships. Pfam families that remain without a mapping to a SCOP family are mapped indirectly to a SCOP family by identifying relationships between such Pfam families and other Pfam families that are already mapped to a SCOP family. The criteria are kept stringent for these mappings to minimize the rate of false positives. In case of a Pfam family mapping to two or more SCOP superfamilies, a decision tree is implemented to assign the Pfam family to a single SCOP superfamily. Using these direct and indirect evolutionary relationships present in the SCOP database, associations between Pfam families are derived. Therefore, relationship between two Pfam families that do not have significant sequence similarity can be identified if both are related to same SCOP superfamily. Almost 36% of the Pfam families could be mapped to SCOP families through direct or indirect association. These Pfam-SCOP associations are grouped into 1,646 different superfamilies and cataloguing changes that occur in the binding sites between two functions, which are analysed in this study to trace possible routes between different functions in evolutionarily related enzymes. The main conclusions of the entire thesis are summarized in Chapter 8, contributing in the area of remote homology detection from sequence information alone and understanding the ‘sequence-structure-function’ paradigm from a binding site perspective. The chapter illustrates the importance of the work presented here in the post-genomic era. The development of the algorithm for the design of ‘intermediately-related sequences’ that could serve as effective linkers in remote homology detection, its subsequent large scale assessment and amenability to be augmented into any protein sequence database and exploration by any sequence-based search method is highlighted. Databases in the NrichD resource are made available in the public domain along with a portal to design artificial sequence for or between protein families. This thesis also provides useful and meaningful predictions for protein families with yet unknown structure and function using NrichD database as well as four other state-of-the-art sequence-based remote homology detection methods. A different aspect addressed in this thesis provides a fundamental understanding of the relationships between protein structure and functions. Evolutionary relationships between functional families are identified using the inherent structural information for these families and fold-function relationships are studied from a perspective of similarities in their binding sites. Such studies help in the area of functional annotation, polypharmacology and protein engineering. Chapter 2 addresses the problem of paucity of available protein sequences that can act as linkers between distantly related proteins/families and help in detection of distant evolutionary relationships. Previous efforts in protein sequence design for remote homology detection and design of sequences corresponding to specific protein families are discussed. This chapter describes a novel methodology to computationally design intermediately-related protein sequences between two related families and thus fill-in the gaps in the sequence space between the related families. Protein families as defined in SCOP database are represented as position specific scoring matrices (PSSMs) and these profiles of related protein families within a fold are aligned using AlignHUSH -a profile-profile alignment method. Guided by this alignment, the frequency distribution of the amino acids in the two families are combined and for each aligned position a residue is selected based on the combined probability to occur in the alignment positions of two families. Each computationally designed sequence is then subjected to RPS-BLAST searches against an all profile pool representing all protein families. Artificial sequences that detect both the parent profiles with no hits corresponding to other folds qualify as ‘designed intermediate sequences’. Various scoring schemes and divergence levels for the design of protein-like sequences are investigated such that these designed sequences intersperse between two related families, thereby creating a continuum in sequence space. The method is then applied on a large scale for all folds with two or more families and resulted in the design of 3,611,010 intermediately-related sequences for 27,882 profile-profile alignments corresponding to 374 folds. Such designed sequences are generic in nature and can be augmented in any sequence database of natural protein sequences. Such enriched databases can then be queried using any sequence-based remote homology detection method to detect distant relatives. The next chapter (Chapter 3) explores the ability of these designed intermediate sequences to act as linkers of two related families and aid in detection of remote homologues. To assess the applicability of these designed sequences two types of databases have been generated, namely a CONTROL database containing protein sequences from natural sequence databases and an AUGMENTED database in which designed sequences are included in the database of natural sequences. Detailed assessments of the utility of such designed sequences using traditional sequence-based searches in the AUGMENTED database showed an enhanced detection of remote homologues for almost 74% of the folds. For over 3,000 queries, it is demonstrated that designed sequences are positioned as suitable linkers, which mediate connections between distantly related proteins. Using examples from known distant evolutionary relationships, we demonstrate that homology searches in augmented databases show an increase of up to 22% in the number of /correct evolutionary relationships "discovered". Such connections are reported with high sensitivities and very low false positive rates. Interestingly, they fill-in void and sparse regions in sequence space and relate distant proteins not only through multiple routes but also through SCOP-NrichD database, SUPFAM+ database, SUPERFAMILY database, protein domain library queried by pDomTHREADER and HHsearch against HMM library of SCOP families. This approach detected evolutionary relationships for almost 20% of all the families with no known structure or function. Detailed report of predictions for 614 DUFs, their fold and species distribution are provided in this chapter. These predictions are then enriched with GO terms and enzyme information wherever available. A detailed discussion is provided for few of the interesting assignments: DUF1636, DUF1572 and DUF2092 which are functionally annotated as thioredoxin-like 2Fe-2S ferredoxin, putative metalloenzyme and lipoprotein localization factors respectively. These 614 novel structure-function relationships of which 193 are supported by consensus between at least two of the five methods, can be accessed from http://proline.biochem.iisc.ernet.in/RHD_DUFS/. Protein functions can be appreciated better in the light of evolutionary information from their structures. Chapter 6 describes a database of evolutionary relationships identified between Pfam families. The grouping of Pfam families is important to obtain a better understanding on evolutionary relationships and in obtaining clues to functions of proteins in families of yet unknown function. Many structural genomics initiative projects have made considerable efforts in solving structures and bridging the growing gap between protein sequences and their structures. The results of such experiments suggest that often the newly solved structure using X-ray crystallography or NMR methods has structural similarity to a protein with already known structure. These relationships often remain undetected due to unavailability of structural information. Therefore, SUPFAM+ database aims to detect such distant relationships between Pfam families by mapping the Pfam families and SCOP domain families. The work presented in this chapter describes the generation of SUPFAM+ database using a sensitive AlignHUSH method to uncover hidden relationships. Firstly, Pfam families are queried against a profile database of SCOP families to derived Pfam-SCOP associations, and then Pfam families are queried against Pfam database to derive Pfam-Pfam relationships. Pfam families that remain without a mapping to a SCOP family are mapped indirectly to a SCOP family by identifying relationships between such Pfam families and other Pfam families that are already mapped to a SCOP family. The criteria are kept stringent for these mappings to minimize the rate of false positives. In case of a Pfam family mapping to two or more SCOP superfamilies, a decision tree is implemented to assign the Pfam family to a single SCOP superfamily. Using these direct and indirect evolutionary relationships present in the SCOP database, associations between Pfam families are derived. Therefore, relationship between two Pfam families that do not have significant sequence similarity can be identified if both are related to same SCOP superfamily. Almost 36% of the Pfam families could be mapped to SCOP families through direct or indirect association. These Pfam-SCOP associations are grouped into 1,646 different superfamilies and cataloguing changes that occur in the binding sites between two functions, which are analysed in this study to trace possible routes between different functions in evolutionarily related enzymes. The main conclusions of the entire thesis are summarized in Chapter 8, contributing in the area of remote homology detection from sequence information alone and understanding the ‘sequence-structure-function’ paradigm from a binding site perspective. The chapter illustrates the importance of the work presented here in the post-genomic era. The development of the algorithm for the design of ‘intermediately-related sequences’ that could serve as effective linkers in remote homology detection, its subsequent large scale assessment and amenability to be augmented into any protein sequence database and exploration by any sequence-based search method is highlighted. Databases in the NrichD resource are made available in the public domain along with a portal to design artificial sequence for or between protein families. This thesis also provides useful and meaningful predictions for protein families with yet unknown structure and function using NrichD database as well as four other state-of-the-art sequence-based remote homology detection methods. A different aspect addressed in this thesis provides a fundamental understanding of the relationships between protein structure and functions. Evolutionary relationships between functional families are identified using the inherent structural information for these families and fold-function relationships are studied from a perspective of similarities in their binding sites. Such studies help in the area of functional annotation, polypharmacology and protein engineering.

L’Imagerie par Résonance Magnétique (IRM) est une belle application de la physique et constitue sans aucun doute l’une des techniques les plus performantes d’imagerie médicale. Basée sur le phénomène de la Résonance Magnétique Nucléaire (RMN) du proton contenu dans les molécules d’eau, l’IRM permet d’investiguer en coupes les tissus mous du corps, sur base de contrastes différents. La méthode est non-invasive et n’utilise pas de radiations ionisantes. En plus des données morphologiques, l’IRM permet également d’obtenir des informations fonctionnelles et physiologiques.<p>De nos jours, plus de 10 000 unités IRM existent dans le monde et des millions d’examens sont réalisés chaque année. La technique est en constant développement et le domaine de recherches est multidisciplinaire. Il concerne aussi bien les développements méthodologiques (imagerie rapide, imagerie de diffusion, etc.) que technologiques (imagerie à haut champ, systèmes de gradients à commutation rapide, etc.), le point central des recherches étant l’amélioration de la qualité des images et la diminution du temps d’acquisition. Ceci implique l'optimisation des différentes séquences IRM (séries d'impulsions radiofréquence et de gradients de champ magnétique) tenant compte des contraintes imposées par le matériel, ainsi que le développement et l'optimisation du matériel lui-même. Cette thèse est consacrée au design avancé des séquences d’impulsions et contribue donc à l'optimisation des schémas d’acquisition en IRM.<p>En particulier, le présent travail est focalisé sur la compréhension et l’amélioration d’un certain type de séquences rapides, employant des échos de gradients :les séquences Steady-State Free Precession (SSFP) et plus précisément les séquences dites balanced-SSFP. Dans ce genre de schéma d’acquisition, le système est excité rapidement et périodiquement, conduisant à l’établissement d’un état stationnaire de l’aimantation. <p>La première partie de la thèse est consacrée à une analyse approfondie des propriétés du signal dans une séquence balanced-SSFP, à la fois à l’état stationnaire et à l’état transitoire. Ensuite, de nouveaux schémas d’acquisition sont développés sur base de calculs analytiques et de simulations numériques et sont ensuite testés expérimentalement. D’une part, une manipulation de l’état stationnaire est présentée en vue de supprimer le signal de la graisse sur les images (qui peut être gênant pour le diagnostic de certaines lésions ou maladies). D’autre part, l’application d’une phase de préparation en vue d’obtenir un contraste basé sur le degré de diffusion des molécules d’eau dans les tissus est analysée en détails, afin d’améliorer la qualité d’image produite par des séquences de diffusion existantes.<p>La présente thèse constitue donc un travail de recherches théoriques et expérimentales, allant de la conception de nouveaux schémas d’acquisition à leur expérimentation sur volontaires, en passant par leur implémentation sur un imageur IRM. Ce travail a été réalisé au sein de l’Unité d’IRM – Radiologie de l’Hôpital Erasme, sous la direction de Thierry Metens, Docteur en Sciences et Physicien IRM.<p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished