Pesquisa que analisa questões técnicas, éticas e jurídicas relacionadas com o uso informatizado de dados genéticos na persecução criminal que suscitam a elaboração de regulamentações técnicas legais para o desejável equilíbrio entre garantias e direitos individuais e os de interesse coletivo relacionados com segurança pública. A automatização de dados de caráter pessoal tem trazido preocupações aos governantes de diversos países, levando-os a adotar medidas legais sobre o tema. Os avanços da genética e da informática possibilitaram a criação de bancos de dados de DNA voltados à identificação criminal que, por serem eficazes no combate à criminalidade, tornaram-se aspiração para muitos Estados, como é o caso brasileiro. Sem que se olvidem ou que se exaltem as potenciais benesses sociais, na criação de bancos de dados de DNA devem ser valorados outros aspectos que também permeiam a questão e que podem ferir suscetibilidades, direitos e garantias individuais. Dentre estes se destacam os de vieses técnicos e éticos concernentes à possibilidade de uso indevido de informações genômicas contidas na molécula de DNA, além dos aspectos jurídicos relacionados com garantias e direitos individuais e coletivos. A presente investigação estuda elementos técnicos relacionados com a análise de polimorfismos do DNA que autorizam seu uso como método de identificação humana, amplamente empregado na atualidade pela Medicina Legal e pela Criminalística para determinação de parentesco biológico e elucidação de crimes. São analisadas características estruturais e funcionais de bancos de dados genéticos e as principais questões técnicas, éticas e legais relacionadas com a coleta de materiais biológicos, com os cuidados de preservação e garantia de autenticidade, com a qualidade dos serviços laboratoriais usados para obtenção de perfis genéticos e com o valor probante da prova pericial formada. É avaliada a importância dos bancos de dados criminais de DNA para a investigação policial e para a persecução judicial, sopesando-se os interesses da segurança pública e os de preservação da privacidade dos sujeitos afetados. São também comparativamente examinados os principais dos bancos de dados de identificação genética criminal já em funcionamento no mundo e suas características atinentes aos sujeitos e tipos de delitos que neles são incluídos; o tempo de permanência dos dados; seu gerenciamento e o armazenamento de vestígios e de amostras-referência. São ainda apontados os parâmetros técnicos e legais mínimos a serem considerados para a criação e o estabelecimento de um banco de dados desse gênero. É estudada pormenorizadamente a proposta feita pela SENASP/MJ para a implantação de um banco nacional de perfis de DNA criminal no Brasil, aos moldes do consagrado CODIS norte-americano. Os resultados desta pesquisa sugerem que, ao se considerar que os direitos e garantias individuais não têm caráter absoluto frente a interesses públicos legítimos, a criação de um banco de dados criminais de DNA no Brasil é viável através da edição de uma lei estabelecedora dos limites das medidas restritivas das prerrogativas individuais e que regule minuciosamente seu funcionamento. / Research that analyses juridical, ethical and technical questions related to the digital use of genetic data at criminal prosecutions that engender the elaboration of legal and technical regulation to the desirable balance among individual rights and guarantees and those of collective interests related to public security. Personal data automation has brought concerns to several countries governments, leading them to adopt legal measures about the theme. Enhancements at genetics and information technology areas had made possible the creation of DNA databases related to criminal identification that, due to their efficacy at criminal combat, have become an aspiration to many States, such as Brazil. Without neither forgetting nor magnifying its potential social benefits, at DNAs database creation other aspects, that are also involved and that could hurt individual susceptibilities, rights and guarantees, should be valued. Among these, it should be emphasized those of technical and ethical concerns related to the improper use of DNAs genomic information, besides juridical aspects related to individual and collective rights and guarantees. The present investigation studies technical elements related to DNA polymorphisms analysis that allow its use as an Human Identification Method, largely employed nowadays at Criminalistics and Forensic Medicine to determine biological kinships and crime scene elucidations. We analyze genetic databases functional and structural characteristics, and the main legal, ethical and technical questions related to biological samples collection, to their preservation and authenticity guarantee, to the involved laboratories quality, and to the probative value of the formed forensic proof. Its also evaluated DNA criminal databases importance to police investigation and judicial prosecution, considering both the public security interest and the privacy preservation of the affected individuals. The main genetic identification databases already working around the world are also comparatively analyzed, as well as their characteristics, such as: what kinds of individuals and faults are included at database; for how long this data stays at the bank; how it is managed and how the storage of evidences and reference samples is done. We also point the minimum legal and technical parameters that should be considered to the creation and establishment of such a database. Its studied in details the SENASP/MJ proposal to implement a national bank of criminal DNA profiles in Brazil, similar to the American CODIS. The results of our study suggest that, considering that individual rights and guarantees dont have absolute character front legitimate public interests, the creation of a criminal DNA database in Brazil is practicable through the edition of some law that would establish the limits to individual prerogatives and also minutely regulate its operation.

Of the many existing eukaryotic gene finding software programs, none are able to guarantee accurate identification of genomic protein coding regions and other biological signals central to pathway from DNA to the protein. Eukaryotic gene finding is difficult mainly due to noncontiguous and non-continuous nature of genes. Existing approaches are heavily dependent on the compositional statistics of the sequences they learn from and are not equally suitable for all types of sequences. This thesis firstly develops efficient digital signal processing-based methods for the identification of genomic protein coding regions, and then combines the optimum signal processing-based non-data-driven technique with an existing data-driven statistical method in a novel system demonstrating improved identification of acceptor splice sites. Most existing well-known DNA symbolic-to-numeric representations map the DNA information into three or four numerical sequences, potentially increasing the computational requirement of the sequence analyzer. Proposed mapping schemes, to be used for signal processing-based gene and exon prediction, incorporate DNA structural properties in the representation, in addition to reducing complexity in subsequent processing. A detailed comparison of all DNA representations, in terms of computational complexity and relative accuracy for the gene and exon prediction problem, reveals the newly proposed ?paired numeric? to be the best DNA representation. Existing signal processing-based techniques rely mostly on the period-3 behaviour of exons to obtain one dimensional gene and exon prediction features, and are not well equipped to capture the complementary properties of exonic / intronic regions and deal with the background noise in detection of exons at their nucleotide levels. These issues have been addressed in this thesis, by proposing six one-dimensional and three multi-dimensional signal processing-based gene and exon prediction features. All one-dimensional and multi-dimensional features have been evaluated using standard datasets such as Burset/Guigo1996, HMR195, and the GENSCAN test set. This is the first time that different gene and exon prediction features have been compared using substantial databases and using nucleotide-level metrics. Furthermore, the first investigation of the suitability of different window sizes for period-3 exon detection is performed. Finally, the optimum signal processing-based gene and exon prediction scheme from our evaluations is combined with a data-driven statistical technique for the recognition of acceptor splice sites. The proposed DSP-statistical hybrid is shown to achieve 43% reduction in false positives over WWAM, as used in GENSCAN.

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Research efforts to determine the causes, effects and locations of mutations within the human genome have been widely pursued due to their role in the development of various diseases. The main cause of mutations in vivo is oxidative damage to DNA via oxidants and free radical species. Numerous studies have been performed in vitro to determine how oxidative damage is induced in DNA. Most of these in vitro studies require photosensitizers to initiate the oxidative damage through various mechanisms. For the purposes of this research, all the photosensitizers that were used initiated oxidative damage in DNA through the electron transfer mechanism. In the charge transport studies, an anthraquinone photosensitizer was covalently linked to the 5 end of DNA by a short carbon tether in order to determine the pattern of damage induced along the length of the DNA. Anthraquinone preferentially damages guanine bases. Our first work sought to determine the effects of charge transport through guanine rich quadruplex DNA dimers. The dimers were formed by the combination of two hairpins with duplex overhangs extending beyond the quadruplex region. This enabled the optimal comparison of the effects of charge transport between duplex and quadruplex DNA structures. Another area of research we pursued in this area was to determine the effects of charge transport in M-DNA (a novel DNA conformation that was reported to form in the presence of zinc ions at a pH above 8). Earlier work on M-DNA suggested that it behaved like a molecular wire. Our research attempted to determine the effects of charge transport on this structure in order to show the behavior of a DNA molecular wire as compared to the standard studies performed in this area on normal B-DNA structures. Lastly, in collaboration with Dr. Ramaiah and colleagues we designed some viologen linked acridine photosensitizers which were tested for any ability to cleave GGG bulges. In preliminary studies, these viologen linked acridine derivatives showed preferential cleavage for guanine bases. They were not covalently bound to DNA, although they could potentially form non covalent interactions with DNA such as intercalation and/or groove binding. Our overall research goal was to determine the extent and overall effect of oxidative damage (using different photosensitizers) on the various DNA structures mentioned above.

Of the many existing eukaryotic gene finding software programs, none are able to guarantee accurate identification of genomic protein coding regions and other biological signals central to pathway from DNA to the protein. Eukaryotic gene finding is difficult mainly due to noncontiguous and non-continuous nature of genes. Existing approaches are heavily dependent on the compositional statistics of the sequences they learn from and are not equally suitable for all types of sequences. This thesis firstly develops efficient digital signal processing-based methods for the identification of genomic protein coding regions, and then combines the optimum signal processing-based non-data-driven technique with an existing data-driven statistical method in a novel system demonstrating improved identification of acceptor splice sites. Most existing well-known DNA symbolic-to-numeric representations map the DNA information into three or four numerical sequences, potentially increasing the computational requirement of the sequence analyzer. Proposed mapping schemes, to be used for signal processing-based gene and exon prediction, incorporate DNA structural properties in the representation, in addition to reducing complexity in subsequent processing. A detailed comparison of all DNA representations, in terms of computational complexity and relative accuracy for the gene and exon prediction problem, reveals the newly proposed ?paired numeric? to be the best DNA representation. Existing signal processing-based techniques rely mostly on the period-3 behaviour of exons to obtain one dimensional gene and exon prediction features, and are not well equipped to capture the complementary properties of exonic / intronic regions and deal with the background noise in detection of exons at their nucleotide levels. These issues have been addressed in this thesis, by proposing six one-dimensional and three multi-dimensional signal processing-based gene and exon prediction features. All one-dimensional and multi-dimensional features have been evaluated using standard datasets such as Burset/Guigo1996, HMR195, and the GENSCAN test set. This is the first time that different gene and exon prediction features have been compared using substantial databases and using nucleotide-level metrics. Furthermore, the first investigation of the suitability of different window sizes for period-3 exon detection is performed. Finally, the optimum signal processing-based gene and exon prediction scheme from our evaluations is combined with a data-driven statistical technique for the recognition of acceptor splice sites. The proposed DSP-statistical hybrid is shown to achieve 43% reduction in false positives over WWAM, as used in GENSCAN.

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007

Complex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain? / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290759 / Thesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007