Studying protein interaction networks using functional and topological information is important for understanding cellular organization and functionality. This study deals with identifying important proteins in protein interaction networks using SWEMODE (Lubovac, et al, 2006) and analyzing topological and functional properties of these proteins with the help of information derived from modular organization in protein interaction networks as well as information available in public resources, in this case, annotation sources describing the functionality of proteins. Multi-modular proteins are short-listed from the modules generated by SWEMODE. Properties of these short-listed proteins are then analyzed using functional information from SGD Gene Ontology(GO) (Dwight, et al., 2002) and MIPS functional categories (Ruepp, et al., 2004). Topological features such as lethality and centrality of these proteins are also investigated, using graph theoretic properties and information on lethal genes from Yeast Hub (Kei-Hoi, et al., 2005). The findings of the study based on GO terms reveal that these important proteins are mostly involved in the biological process of “organelle organization and biogenesis” and a majority of these proteins belong to MIPS “cellular organization” and “transcription” functional categories. A study of lethality reveals that multi-modular proteins are more likely to be lethal than proteins present only in a single module. An examination of centrality (degree of connectivity of proteins) in the network reveals that the ratio of number of important proteins to number of hubs at different hub sizes increases with the hub size (degree).

<p>Studying protein interaction networks using functional and topological information is important for understanding cellular organization and functionality. This study deals with identifying important proteins in protein interaction networks using SWEMODE (Lubovac, et al, 2006) and analyzing topological and functional properties of these proteins with the help of information derived from modular organization in protein interaction networks as well as information available in public resources, in this case, annotation sources describing the functionality of proteins. Multi-modular proteins are short-listed from the modules generated by SWEMODE. Properties of these short-listed proteins are then analyzed using functional information from SGD Gene Ontology(GO) (Dwight, et al., 2002) and MIPS functional categories (Ruepp, et al., 2004). Topological features such as lethality and centrality of these proteins are also investigated, using graph theoretic properties and information on lethal genes from Yeast Hub (Kei-Hoi, et al., 2005). The findings of the study based on GO terms reveal that these important proteins are mostly involved in the biological process of “organelle organization and biogenesis” and a majority of these proteins belong to MIPS “cellular organization” and “transcription” functional categories. A study of lethality reveals that multi-modular proteins are more likely to be lethal than proteins present only in a single module. An examination of centrality (degree of connectivity of proteins) in the network reveals that the ratio of number of important proteins to number of hubs at different hub sizes increases with the hub size (degree).</p>

To understand how diversity varies through time and/or space we need to understand speciation and extinction dynamics, and ultimately which factors (biotic or abiotic) affect such dynamics. It has been argued that biological interactions play an important role on the diversification of organisms, but macroevolutionary studies have usually adopted a simple characterization of species interactions. On the other hand ecological studies usually focus on well-characterized interactions of very few species. A network approach can augment our understanding of the ecological roles played by different species but it still lacks an evolutionary perspective preventing us to fully understand how ecological interactions are assembled. Using the available phylogeny, dietary data for virtually all bird species (approximately 9965 species) and a large collection of frugivory net- works, we tested the effect of diet on the diversification of birds, and the relationship between ecological roles within interaction networks and diversification dynamics of frugivorous species. Lastly, using computational simulations, we assessed the per- formance of two state-of-the-art methods to estimate diversification rates using molecular phylogenies. We suggest that omnivory acts as macroevolutionary sink where its ephemeral nature is retrieved through transitions from other guilds rather than from omnivore speciation. We propose that these dynamics result from competition within and among dietary guilds, influenced by the deep-time availability and predictability of food resources. We also observed that in the temperate zone, lineages with high-paced evolutionary dynamics (e.g. higher turn- over rates) typically do not occupy central roles in frugivory net- works, and that these restrictions are modulated by water avail- ability/predictability. Lastly, we found that the two state-of-the art phylogenetic methods perform equally well in diversity de- cline scenarios when estimating current rates, but both fail to detect the true diversification trajectory when extinction rates vary in time. This dissertation contributes to the understanding of biotic and abiotic mechanisms driving both the diversification and the assembly of interaction networks, and also provides important information on the reliability of diversification rate estimates by current, widely used methods / Para entendermos como a biodiversidade varia no tempo e/ou no espaço precisamos entender a dinâmcia de especiação e extinção, e quais fatores (bióticos ou abióticos) afetam essa dinâmica. Acredita-se que as interações biológicas desempen- ham um papel importante na diversificação de organismos, porém estudos macroevolutivos usualmente adotam caracter- izações simples de interações entre espécies. Por outro lado, estudos ecológicos comumente focam na descrição detalhada de interações entre poucas espécies. Uma abordagem de re- des pode aumentar a compreensão dos papéis ecológicos de- sempenhados por diferentes espécies, mas a pouca ênfase em abordagens evolutivas em estudos de redes biológicas nos im- pedem de compreender completamente como essas redes são montadas. Usando a filogenia e dados de dieta disponíveis para virtualmente todas as espécies de aves (aprox. 9965 espécies), e uma grande coleção de redes de frugivoria, investigamos o efeito da dieta na diversificação de aves, e testamos a relação en- tre papéis ecológicos em redes de interação e a dinâmica da di- versificação de espécies frugívoras. Ainda, usando simulações computacionais, avaliamos a performance de dois métodos am- plamente utilizados para estimar taxas de diversificação usando filogenias moleculares. Sugerimos que onivoria atua como um ralo macroevolutivo, onde sua natureza efêmera é recuperada através de transições de outras guildas de dieta ao invés de através da especiação de espécies onívoras. Nós sugerimos que essa dinâmica resulta da competição intra- e entre guildas, in- fluenciada pela disponibilidade e previsibilidade de recursos em ampla escalas de tempo. Nós também observamos que em regiões temperadas, linhagens com uma dinâmica evolutiova mais rápida (maiores taxas de substituição de espécies) em geral não ocupam papéis centrais em redes de frugivoria, e que es- sas restrições são principalmente modificadas por disponibili- dade/previsibilidade hídricas. Por fim, observamos que ambos os métodos filogenéticos testados tem desempenho igualmente bom para estimar taxas atuais, porém ambos falham em detectar a trajetória da diversificação quando as taxas de extinção variam no tempo. Essa tese contribui para o conhecimento de mecanis- mos bióticos e abióticos que afetam tanto a diversificação quanto a montagem de redes de interação, e também provê informações importantes acerca da confiabilidade das estimativas de taxas de diversificação advindas dos métodos atuais amplamente utilizados

The first aim of this thesis is to examine relationships between microRNAs targeting gene networks, combining knowledge from microRNA prediction databases into our microRNA Data Integration Portal (mirDIP). Modeling the microRNA:transcript interactome – referred to as the micronome – to build microRNA interaction networks of signalling pathways, we find genes within signalling pathways to be co-targeted by common microRNAs suggesting an unexpected level of transcriptional control. We identify two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets, to be more studied and more involved in cancer signalling than their intrapathway counterparts. The second aim was to undertake a more focused view, analyzing the characteristics of microRNAs within the micronome itself beginning with a focus on the under-examined microRNA terminal loop across the micronome to determine if this region of the microRNA structure might contribute to microRNA functioning. We have identified 2 main classes of microRNAs based on loop structure – perfect and occluded, which show biological relevance. We found regulatory motifs within microRNA terminal loops and found a large number of Frequently Occurring Words (FOWs) significantly overrepresented across the micronome. Set analysis of in vitro secreted microRNAs, microRNA expression across a panel of normal tissues, and microRNAs shown to be secreted in lung cancer shows that specific microRNA loop motifs within these groups are significantly overreperesented – suggesting that microRNA terminal loops harbour sequences bearing microRNA processing and localization signals.

The first aim of this thesis is to examine relationships between microRNAs targeting gene networks, combining knowledge from microRNA prediction databases into our microRNA Data Integration Portal (mirDIP). Modeling the microRNA:transcript interactome – referred to as the micronome – to build microRNA interaction networks of signalling pathways, we find genes within signalling pathways to be co-targeted by common microRNAs suggesting an unexpected level of transcriptional control. We identify two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets, to be more studied and more involved in cancer signalling than their intrapathway counterparts. The second aim was to undertake a more focused view, analyzing the characteristics of microRNAs within the micronome itself beginning with a focus on the under-examined microRNA terminal loop across the micronome to determine if this region of the microRNA structure might contribute to microRNA functioning. We have identified 2 main classes of microRNAs based on loop structure – perfect and occluded, which show biological relevance. We found regulatory motifs within microRNA terminal loops and found a large number of Frequently Occurring Words (FOWs) significantly overrepresented across the micronome. Set analysis of in vitro secreted microRNAs, microRNA expression across a panel of normal tissues, and microRNAs shown to be secreted in lung cancer shows that specific microRNA loop motifs within these groups are significantly overreperesented – suggesting that microRNA terminal loops harbour sequences bearing microRNA processing and localization signals.

Research into human disease has classically been 'bottom-up', focussing on individual genes. However, the emergence of Systems Biology has prompted a more holistic 'top-down' approach to decoding life. Less than a decade since the complete draft of the human genome was published, we are increasingly in a position to model the interacting constituents of a cell and thus understand molecular perturbations. Given biological systems are rarely attributable to individual molecules and linear pathways, we must understand the complex dynamic interplay as cellular components interact, combine, overlap and conflict. The integrative approach afforded by Network Biology provides us with a powerful toolset to understand the vast volumes of omics data. In this thesis, I investigate both infectious disease, specifically HIV infection and heritable disease. HIV, the causative agent of AIDS, represents an extensive perturbation of the host system and results in hijacking of cellular proteins to replicate. I first introduce the HIV-interaction data and then characterise HIV's hijack, revealing the ways Network Biology can greatly enhance our understanding of host-pathogen systems and ultimately the systems itself. I find a significantly greater propensity for HIV to interact with ''key'' host proteins that are highly connected and represent critical cellular functions. Unexpectedly, however, I find there are no associations between HIV interaction and inferred essentiality and genetic disease-association. I hypothesise that these observations could be the result of ancestral selection pressure on retroviruses to minimise interactions with phenotypically crucial proteins. Investigating inherited disease, I apply a similar integrative approach to determine the relationships between inherited disease, evolution and function. I find that 'disease' genes are not a homogenous group, and that their emergence has been ongoing throughout the evolution of life; contradicting previous studies. Finally, I consider the consequence of bias in literature-curated interaction datasets. I develop a novel method to identify and correct for ascertainment bias and demonstrate that failure to do this weakens conclusions. correct for ascertainment bias and demonstrate that failure to do this weakens conclusions. The aim of this thesis has been to explore the ways Network Biology can provide an integrative biological approach to studying infectious and inherited disease. Given billions of people around the world are susceptible to disease, it is ultimately hoped that a Systems Biology approach to understanding disease will herald new pharmaceutical interventions.

To understand how diversity varies through time and/or space we need to understand speciation and extinction dynamics, and ultimately which factors (biotic or abiotic) affect such dynamics. It has been argued that biological interactions play an important role on the diversification of organisms, but macroevolutionary studies have usually adopted a simple characterization of species interactions. On the other hand ecological studies usually focus on well-characterized interactions of very few species. A network approach can augment our understanding of the ecological roles played by different species but it still lacks an evolutionary perspective preventing us to fully understand how ecological interactions are assembled. Using the available phylogeny, dietary data for virtually all bird species (approximately 9965 species) and a large collection of frugivory net- works, we tested the effect of diet on the diversification of birds, and the relationship between ecological roles within interaction networks and diversification dynamics of frugivorous species. Lastly, using computational simulations, we assessed the per- formance of two state-of-the-art methods to estimate diversification rates using molecular phylogenies. We suggest that omnivory acts as macroevolutionary sink where its ephemeral nature is retrieved through transitions from other guilds rather than from omnivore speciation. We propose that these dynamics result from competition within and among dietary guilds, influenced by the deep-time availability and predictability of food resources. We also observed that in the temperate zone, lineages with high-paced evolutionary dynamics (e.g. higher turn- over rates) typically do not occupy central roles in frugivory net- works, and that these restrictions are modulated by water avail- ability/predictability. Lastly, we found that the two state-of-the art phylogenetic methods perform equally well in diversity de- cline scenarios when estimating current rates, but both fail to detect the true diversification trajectory when extinction rates vary in time. This dissertation contributes to the understanding of biotic and abiotic mechanisms driving both the diversification and the assembly of interaction networks, and also provides important information on the reliability of diversification rate estimates by current, widely used methods / Para entendermos como a biodiversidade varia no tempo e/ou no espaço precisamos entender a dinâmcia de especiação e extinção, e quais fatores (bióticos ou abióticos) afetam essa dinâmica. Acredita-se que as interações biológicas desempen- ham um papel importante na diversificação de organismos, porém estudos macroevolutivos usualmente adotam caracter- izações simples de interações entre espécies. Por outro lado, estudos ecológicos comumente focam na descrição detalhada de interações entre poucas espécies. Uma abordagem de re- des pode aumentar a compreensão dos papéis ecológicos de- sempenhados por diferentes espécies, mas a pouca ênfase em abordagens evolutivas em estudos de redes biológicas nos im- pedem de compreender completamente como essas redes são montadas. Usando a filogenia e dados de dieta disponíveis para virtualmente todas as espécies de aves (aprox. 9965 espécies), e uma grande coleção de redes de frugivoria, investigamos o efeito da dieta na diversificação de aves, e testamos a relação en- tre papéis ecológicos em redes de interação e a dinâmica da di- versificação de espécies frugívoras. Ainda, usando simulações computacionais, avaliamos a performance de dois métodos am- plamente utilizados para estimar taxas de diversificação usando filogenias moleculares. Sugerimos que onivoria atua como um ralo macroevolutivo, onde sua natureza efêmera é recuperada através de transições de outras guildas de dieta ao invés de através da especiação de espécies onívoras. Nós sugerimos que essa dinâmica resulta da competição intra- e entre guildas, in- fluenciada pela disponibilidade e previsibilidade de recursos em ampla escalas de tempo. Nós também observamos que em regiões temperadas, linhagens com uma dinâmica evolutiova mais rápida (maiores taxas de substituição de espécies) em geral não ocupam papéis centrais em redes de frugivoria, e que es- sas restrições são principalmente modificadas por disponibili- dade/previsibilidade hídricas. Por fim, observamos que ambos os métodos filogenéticos testados tem desempenho igualmente bom para estimar taxas atuais, porém ambos falham em detectar a trajetória da diversificação quando as taxas de extinção variam no tempo. Essa tese contribui para o conhecimento de mecanis- mos bióticos e abióticos que afetam tanto a diversificação quanto a montagem de redes de interação, e também provê informações importantes acerca da confiabilidade das estimativas de taxas de diversificação advindas dos métodos atuais amplamente utilizados

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An important aspect of systems biology is the elucidation of the protein-protein interactions (PPIs) that control important biological processes within a cell and between organisms. In particular, at the cellular and molecular level, interactions between a pathogen and its host play a vital role in initiating infection and a successful pathogenesis. Despite recent successes in the advancement of the systems biology of model organisms to understand complex diseases, the analysis of infectious diseases at the systems-level has not received as much attention. Since pathogen related disease is responsible for millions of deaths and billions of dollars in damage to crops and livestock, understanding the mechanisms employed by pathogens to infect their hosts is critical in the development of new and effective therapeutic strategies. The research presented here is one of the first computational approaches to studying host-pathogen PPI networks. This dissertation has two main aims. First, we discuss analytical tools for studying host-pathogen networks to identify common pathways perturbed and manipulated by pathogens. We present the first global comparison of the host-pathogen PPI networks of 190 different pathogens and their interactions with human proteins. We also present the construction and analysis of three highly infectious human-bacterial PPI networks: <i>Bacillus anthracis</i>, <i>Francislla tularensis</i>, and <i>Yersinia pestis</i>. The second aim of the research presented here is the development of predictive models for identifying PPIs between host and pathogen proteins. We present two methods: (i) a domain-based approach that uses frequency of domain-pairs in intra-species PPIs, and (ii) a supervised machine learning method that is trained on known inter-species PPIs. The techniques developed in this dissertation, along with the informative datasets presented, will serve as a foundation for the field of computational pathosystems biology. / Ph. D.