6,764 research outputs found

    Application of fuzzy controllers in automatic ship motion control systems

    Get PDF
    Automatic ship heading control is a part of the automatic navigation system. It is charged with the task of maintaining the actual ship’s course angle or actual ship’s course without human intervention in accordance with the set course or setting parameter and maintaining this condition under the effect of disturbing influences. Thus, the corrective influence on deviations from a course can be rendered by the position of a rudder or controlling influence that leads to the rotary movement of a vessel around a vertical axis that represents a problem, which can be solved with the use of fuzzy logic. In this paper, we propose to consider the estimation of the efficiency of fuzzy controllers in systems of automatic control of ship movement, obtained by analysis of a method of the formalized record of a logic conclusion and structure of the fuzzy controller. The realization of this allows to carry out effective stabilization of a course angle of a vessel taking into account existing restrictions

    Desenvolvimento de testes genéticos por PCR em tempo-real para diagnóstico rápido de LHON e surdez

    Get PDF
    Mitochondrial cytopathies are a set of diseases caused by a disturbance in the cell energy production. Mitochondrial dysfunction impairs efficiency of the mitochondrial respiratory chain (MRC) and ATP production, affecting the organism’s energetic equilibrium. Pathogenic sequence variants in mitochondrial DNA (mtDNA) that lead to these pathologies are more frequent in tissues that need higher energy levels to function. The presented work looks into two such diseases: Leber’s Hereditary Optic Neuropathy and mitochondrial non-syndromic Hearing Loss (MNSHL). LHON is characterized by presence of genetic alterations in mtDNA, with three main primary pathogenic sequence variants existing, which represent 90-95% of LHON cases with an identified genetic cause: m.3460G>A, in ND1 subunit gene; m.11778G>A, in ND4 subunit gene; and m.14484T>C, in ND6 subunit gene. All of these are subunits of the MRC’s complex I. These mtDNA variations lead to mitochondrial dysfunction in complex I, creating ATP depletion, reactive oxygen species (ROS) increase and oxidative stress. LHON is commonly characterized by a sequential vision loss and, within 1 year of symptoms starting, 97% of patients with vision loss in one eye develop loss in the second. Therapy administration yields good outcomes, if done in a short-time span after first vision loss. It is essential to quickly and reliably scan for pathogenic sequence variants, in order to act timely and rescue function. Mitochondrial non-syndromic hearing loss and deafness (MNSHL) is characterized by sensorineural hearing loss (SNHL). This type of hearing loss, particularly when induced by aminoglycosides, has also three primary pathogenic sequence variants associated with ototoxicity: m.1494C>T and m.1555A>G, both in the MTRNR1 gene, and m.7445A>G, in the MTCO1 and MTTS1 genes. These are responsible for ATP depletion, an increase of ROS and oxidative stress, due to alterations in the mitochondrial ribosome or tRNA. In MNSHL, the cochlea is the affected tissue. With this disorder the principal modifier factor is the administration of aminoglycosides, a type of antibiotics, which trigger a cascade, that leads the individual permanently deaf. The best course of action is prevention, and to ensure clinical action is not dramatically slowed down, results that show whether administration is safe or not need to be quick. The aim of this work, for both diseases, is the development of a screening method characterized by fast and reliable approach for genetic assessment, to be used for clinical guidance, particularly in therapeutics. For LHON, the screening method is based on real-time PCR with High-Resolution Melting (HRM) analysis, for detection of the TOP-3 pathogenic sequence variants, by assessing the amplicon’s Tm. In this case, 94 samples were analyzed, including LHON suspected patients, relatives, other mitochondrial disease patients and healthy controls. All samples were previously classified by another method, having then been blinded before the performance of this work. For analysis, Real-Time PCR was run in triplicates, to allow for a more robust HRM analysis. The software had the ability to classify samples as different variants, wild-type or mutant; information which was then crossed with the previous classification of the sample to assess the success of the software classification. Samples were correctly assigned. This approach provides results in a quick fashion that guides clinical action in a timely fashion. The presence of other polymorphisms in the amplicons might be a hindrance to the robustness of the results provided by this technique and their effect on variant classification needs to be considered. For this, a predictive in-silico analysis was performed, regarding all described variants’ presence in the sequences in analysis. Accordingly, an additional complementary method may be necessary for assurance of result’s specificity. For MNSHL, the screening method was also real-time PCR based, but this one was performed with Amplification-Refractory Mutation System (ARMS) primers, designed for the pathogenic sequence variants previously associated in literature for the MNSHL. Discrimination of results was done based on amplification in positive cases and lack of it in negative cases. This approach analyzed 32 samples, including MNSHL suspected patients, their relatives, other mitochondrial disease patients and healthy controls, but only results concerning the m.1555A>G were obtained timely. All samples were previously classified by another method, having then been blinded before performance of this work. For optimization, Real-Time PCR was run in duplicates, to increase robustness of analysis. The Real-Time software showed if samples amplified as wild-type or mutant, with classification following. This data was crossed with previous known classification of the samples to assess the success of the approach. All analyzed samples were correctly identified with this approach. However, two of the three pathogenic sequence variants did not achieve implementation within the timeframe necessary for their inclusion, namely m.1494C>T and m.7445A>G. The optimization of their screening was not possible and further work is necessary to optimize and implement the approach concerning the analysis for these variants. In conclusion, it was possible to implement an analysis method for LHON’s TOP-3 pathogenic sequence variants within 24h, which represents a big step in precision medicine for diagnosis of this disease. On the other hand, although the implementation was not concluded, a similar approach was started for MNSHL – that, when concluded, will have an enormous impact in preventing aminoglycoside induced HL. This work represents a high impact scientific contribution in reverse translational research.As citopatias mitocondriais são um conjunto de doenças causadas por um distúrbio na produção de energia celular. A disfunção mitocondrial prejudica a eficiência da cadeia respiratória mitocondrial (CRM) e a produção de ATP, afetando o equilíbrio energético do organismo. As variações de sequência patogénicas no DNA mitocondrial (mtDNA) que levam a estas patologias são mais frequentes em tecidos que necessitam de maiores níveis de energia para funcionar. O presente trabalho explora duas dessas doenças: Neuropatia ótica hereditária de Leber (LHON) e Surdez mitocondrial induzida por aminoglicosídeos. A LHON é caracterizada pela presença de alterações genéticas do mtDNA, existindo três variações de sequência patogénicas primárias principais, que representam 90-95% de casos de LHON com identificação da causa genética: m.3460G>A, no gene que codifica a subunidade ND1; m.11778G>A, no gene que codifica a subunidade ND4; e m.14484T>C, no gene que codifica a subunidade ND6. Todas estas subunidades pertencem ao complexo I da CRM. Estas alterações no mtDNA levam a disfunção mitocondrial no complexo I, criando depleção de ATP, aumento de espécies reativas de oxigénio (ROS) e stresse oxidativo. A LHON é comummente caracterizada pela perda sequencial de visão e, 1 ano após o início dos sintomas, 97% dos casos com perda de visão num olho desenvolvem perda de visão no segundo. A administração de terapia produz bons resultados, quando realizada num curto período de tempo após a primeira perda de visão. Assim, é essencial pesquisar variações de sequência patogénicas genéticas de forma rápida e fiável, para atuar rapidamente e recuperar a função visual. A Surdez mitocondrial não-sindrómica (MNSHL), em particular a induzida por aminoglicosídeos, tem também três mutações principais associadas à perda de audição: m.1494C>T e m.1555A>G, ambas no gene MTRNR1, e m.7445A>G, nos genes MTCO1 e MTTS1. Estas são responsáveis pela depleção de ATP, aumento de ROS e stresse oxidativo, devido a alterações no ribossoma ou no tRNA mitocondrial. Aqui, o tecido afetado é a cóclea. Nesta doença, o fator modificador em destaque é a administração de antibióticos de tipo aminoglicosídeos, que despoletam uma cascata de acontecimentos, levando à surdez permanente. A melhor estratégia passa pela prevenção, enquanto ao mesmo tempo se garante que a ação clínica não sofre atrasos. Desta forma, são necessários resultados rápidos, que demonstrem se a administração será segura ou não. O objetivo deste trabalho, para ambas as doenças, é o desenvolvimento de um método de screening, caracterizado por uma abordagem rápida e fiável, usado para guiar a decisão clínica, particularmente na terapêutica. Para a LHON, o método de screening é baseado em PCR em tempo-real com análise de High-Resolution Melting (HRM), para deteção das variantes patogénicas TOP-3, avaliando as Tm dos amplicons. Neste caso, foram analisadas 94 amostras, incluindo doentes com suspeita de LHON, familiares, outros doentes com suspeita de outra doença mitocondrial e controlos saudáveis. Todas as amostras foram previamente classificadas por outro método, tendo sido sujeitas a anonimização antes da realização do trabalho. Para a análise, a PCR em tempo-real foi realizada em triplicados, para permitir uma análise de HRM mais robusta. O software teve a capacidade de classificar amostras como diferentes variantes, ou seja, normal ou mutante. Esta informação foi cruzada com as classificações previamente existentes para avaliar o sucesso da classificação pelo software. As amostras foram corretamente classificadas. Esta abordagem fornece resultados de forma rápida, podendo guiar a ação clínica em tempo útil. A presença de outros polimorfismos nos amplicons poderão obstruir a robustez dos resultados fornecidos por esta técnica e o seu efeito na classificação de variantes precisa de ser considerado. Por esta razão, foi realizada uma análise de previsão in-silico, considerando a presença de todas as variantes descritas. Nesse sentido, pode ser necessário um método complementar de análise para assegurar a especificidade dos resultados. Para a Surdez mitocondrial não-sindrómica, o método de screening baseou-se também na PCR em tempo-real, mas foi realizada com primers de Amplification-Refractory mutation system (ARMS), desenhados para as variantes de sequência patogénicas associadas à MNSHL induzida por aminoglicosídeos, previamente descritas na literatura para esta doença. A discriminação de resultados foi feita com base na presença/ausência de amplificação para cada variante. Foram analisadas 32 amostras com esta abordagem, incluindo doentes com suspeita de MNSHL, seus familiares, doentes com suspeita de outra doença mitocondrial e controlos saudáveis, mas apenas foram obtidos resultados em tempo útil para a m.1555A>G. Todas as amostras tinham sido previamente classificadas por outro método, tendo sido anonimizadas antes da realização do trabalho. Para a otimização, a PCR em tempo-real foi realizada em duplicados, aumentando a robustez da análise. O software de tempo-real mostrou quais as amostras que amplificaram como normais ou mutantes, permitindo a classificação das mesmas. Os dados foram comparados com as classificações previamente conhecidas, para avaliar o sucesso da abordagem em estudo. Todas as amostras em análise foram corretamente identificadas. No entanto, duas das três variantes patogénicas não foram implementadas em tempo útil para inclusão neste trabalho. Para a m.1494C>T e a m.7445A>G, a otimização não foi possível, e será necessário trabalho adicional no futuro, para a implementação da análise destas variantes. Em conclusão, foi possível implementar um método da análise das variantes genéticas TOP-3 da LHON em 24h, o que representa um grande passo na medicina de precisão para diagnóstico desta doença. Por outro lado, apesar de não ter sido concluída a implementação, iniciou-se uma abordagem semelhante para a MNSHL – que, quando for concluída, terá um enorme impacto para evitar a perda auditiva por exposição a aminoglicosídeos. Este trabalho representa uma contribuição científica de alto impacto na investigação translacional reversa.O Laboratório de Biomedicina Mitocondrial e Teranóstica recebeu apoio financeiro da Santhera Pharmaceuticals que permitiu implementação do projeto nacional “Investigação Translacional Epidemiológica, Bigenómica e Funcional nas Atrofias Ópticas” (IP Professora Doutora Manuela Grazina). Apoio financeiro do CNC.IBILI no âmbito do Plano Estratégico UID/NEU/04539/2019.Mestrado em Biologia Aplicad

    Addressing infrastructure challenges posed by the Harwich Formation through understanding its geological origins

    Get PDF
    Variable deposits known to make up the sequence of the Harwich Formation in London have been the subject of ongoing uncertainty within the engineering industry. Current stratigraphical subdivisions do not account for the systematic recognition of individual members in unexposed ground where recovered material is usually disturbed - fines are flushed out during the drilling process and loose materials are often lost or mixed with the surrounding layers. Most engineering problems associated with the Harwich Formation deposits are down to their unconsolidated nature and irregular cementation within layers. The consequent engineering hazards are commonly reflected in high permeability, raised groundwater pressures, ground settlements - when found near the surface and poor stability - when exposed during excavations or tunnelling operations. This frequently leads to sudden design changes or requires contingency measures during construction. All of these can result in damaged equipment, slow progress, and unforeseen costs. This research proposes a facies-based approach where the lithological facies assigned were identified based on reinterpretation of available borehole data from various ground investigations in London, supported by visual inspection of deposits in-situ and a selection of laboratory testing including Particle Size Distribution, Optical and Scanning Electron Microscopy and X-ray Diffraction analyses. Two ground models were developed as a result: 1st a 3D geological model (MOVE model) of the stratigraphy found within the study area that explores the influence of local structural processes controlling/affecting these sediments pre-, syn- and post- deposition and 2nd a sequence stratigraphic model (Dionisos Flow model) unveiling stratal geometries of facies at various stages of accretion. The models present a series of sediment distribution maps, localised 3D views and cross-sections that aim to provide a novel approach to assist the geotechnical industry in predicting the likely distribution of the Harwich Formation deposits, decreasing the engineering risks associated with this stratum.Open Acces

    Synthesis and Characterisation of Low-cost Biopolymeric/mineral Composite Systems and Evaluation of their Potential Application for Heavy Metal Removal

    Get PDF
    Heavy metal pollution and waste management are two major environmental problems faced in the world today. Anthropogenic sources of heavy metals, especially effluent from industries, are serious environmental and health concerns by polluting surface and ground waters. Similarly, on a global scale, thousands of tonnes of industrial and agricultural waste are discarded into the environment annually. There are several conventional methods to treat industrial effluents, including reverse osmosis, oxidation, filtration, flotation, chemical precipitation, ion exchange resins and adsorption. Among them, adsorption and ion exchange are known to be effective mechanisms for removing heavy metal pollution, especially if low-cost materials can be used. This thesis was a study into materials that can be used to remove heavy metals from water using low-cost feedstock materials. The synthesis of low-cost composite matrices from agricultural and industrial by-products and low-cost organic and mineral sources was carried out. The feedstock materials being considered include chitosan (generated from industrial seafood waste), coir fibre (an agricultural by-product), spent coffee grounds (a by-product from coffee machines), hydroxyapatite (from bovine bone), and naturally sourced aluminosilicate minerals such as zeolite. The novel composite adsorbents were prepared using commercially sourced HAp and bovine sourced HAp, with two types of adsorbents being synthesized, including two- and three-component composites. Standard synthetic methods such as precipitation were developed to synthesize these materials, followed by characterization of their structural, physical, and chemical properties (by using FTIR, TGA, SEM, EDX and XRD). The synthesized materials were then evaluated for their ability to remove metal ions from solutions of heavy metals using single-metal ion type and two-metal ion type solution systems, using the model ion solutions, with quantification of their removal efficiency. It was followed by experimentation using the synthesized adsorbents for metal ion removal in complex systems such as an industrial input stream solution system obtained from a local timber treatment company. Two-component composites were considered as control composites to compare the removal efficiency of the three-component composites against. The heavy metal removal experiments were conducted under a range of experimental conditions (e.g., pH, sorbent dose, initial metal ion concentration, time of contact). Of the four metal ion systems considered in this study (Cd2+, Pb2+, Cu2+ and Cr as chromate ions), Pb2+ ion removal by the composites was found to be the highest in single-metal and two-metal ion type solution systems, while chromate ion removal was found to be the lowest. The bovine bone-based hydroxyapatite (bHAp) composites were more efficient at removing the metal cations than composites formed from a commercially sourced hydroxyapatite (cHAp). In industrial input stream solution systems (containing Cu, Cr and As), the Cu2+ ion removal was the highest, which aligned with the observations recorded in the single and two-metal ion type solution systems. Arsenate ion was removed to a higher extent than chromate ion using the three-component composites, while the removal of chromate ion was found to be higher than arsenate ion when using the two-component composites (i.e., the control system). The project also aimed to elucidate the removal mechanisms of these synthesized composite materials by using appropriate adsorption and kinetic models. The adsorption of metal ions exhibited a range of adsorption behaviours as both the models (Langmuir and Freundlich) were found to fit most of the data recorded in different adsorption systems studied. The pseudo-second-order model was found to be the best fitted to describe the kinetics of heavy metal ion adsorption in all the composite adsorbent systems studied, in single-metal ion type and two-metal ion type solution systems. The ion-exchange mechanism was considered as one of the dominant mechanisms for the removal of cations (in single-metal and two-metal ion type solution systems) and arsenate ions (in industrial input stream solution systems) along with other adsorption mechanisms. In contrast, electrostatic attractions were considered to be the dominant mechanism of removal for chromate ions

    Investigating PAX6 and SOX2 dynamic interactions at the single molecule level in live cells

    Get PDF
    The abundance of transcription factor (TF) molecules in the nuclei of eukaryotic cells are in the range of thousands. However, the functional binding sites of most TFs lie in the range of hundreds. This suggests that there is a surplus of the number of molecules for many TFs, relative to their binding sites at any given time. Nevertheless, precise TF levels are instrumental for normal development and maintenance, with haploinsufficiency (namely lowering the dosage of a TF by half) being a hallmark of many TF-related human developmental disorders. Qualitative methods assessing TF binding such as chromatin immunoprecipitation, provide static information, from fixed cell populations and so fail to provide insight into TF dynamic behaviour. Live-cell imaging methodologies such as Fluorescence Correlation Spectroscopy (FCS) offer the ability to measure kinetics of binding to chromatin, protein-protein interactions, absolute concentrations of molecules and the underlying cell-to-cell variability. SOX2 and PAX6 TFs exhibit haploinsufficiency in humans. Heterozygous point mutations, deletions or insertions in these genes can lead to a plethora of abnormal ocular developmental disorders (e.g. coloboma, aniridia, microphthalmia, anopthalmia). SOX2 encodes a high-mobility group (HMG) domain-containing TF, essential for maintaining self-renewal of embryonic stem cells and is expressed in proliferating central nervous system (CNS) progenitors. PAX6 contains two DNA binding domains; a PAIRED domain (PD) and a homeodomain (HD). Both DNA binding domains present in PAX6 (PD and HD) can function either jointly, or separately, to regulate a plethora of genes implicated in the development and maintenance of the CNS, the eye and the pancreas. Despite existing genetic and phenotypic evidence, it remains unclear how PAX6 and SOX2 influence each other at the molecular level and how sensitive their stoichiometry is during ocular development. In this thesis I investigated the dynamic interplay between PAX6/SOX2 and chromatin in live cells, at the molecular level. I compared wild-type protein function with pathogenic missense variants using advanced fluorescence microscopy techniques and assessed how these mutations quantitatively and qualitatively affected molecular behaviour. My results showed that both SOX2 and PAX6 pathogenic missense mutants display differential subnuclear localisation, as well as altered protein-protein and protein-chromatin interactions, linking molecular diffusion to pathogenic phenotype in humans. More importantly, I identified a novel role of SOX2 in stabilising PAX6- chromatin complexes in live cells, providing further insight into the complex and dynamic relation of PAX6 and SOX2 in ocular tissue specification, maintenance and development

    Elasto-plastic deformations within a material point framework on modern GPU architectures

    Get PDF
    Plastic strain localization is an important process on Earth. It strongly influ- ences the mechanical behaviour of natural processes, such as fault mechanics, earthquakes or orogeny. At a smaller scale, a landslide is a fantastic example of elasto-plastic deformations. Such behaviour spans from pre-failure mech- anisms to post-failure propagation of the unstable material. To fully resolve the landslide mechanics, the selected numerical methods should be able to efficiently address a wide range of deformation magnitudes. Accurate and performant numerical modelling requires important compu- tational resources. Mesh-free numerical methods such as the material point method (MPM) or the smoothed-particle hydrodynamics (SPH) are particu- larly computationally expensive, when compared with mesh-based methods, such as the finite element method (FEM) or the finite difference method (FDM). Still, mesh-free methods are particularly well-suited to numerical problems involving large elasto-plastic deformations. But, the computational efficiency of these methods should be first improved in order to tackle complex three-dimensional problems, i.e., landslides. As such, this research work attempts to alleviate the computational cost of the material point method by using the most recent graphics processing unit (GPU) architectures available. GPUs are many-core processors originally designed to refresh screen pixels (e.g., for computer games) independently. This allows GPUs to delivers a massive parallelism when compared to central processing units (CPUs). To do so, this research work first investigates code prototyping in a high- level language, e.g., MATLAB. This allows to implement vectorized algorithms and benchmark numerical results of two-dimensional analysis with analytical solutions and/or experimental results in an affordable amount of time. After- wards, low-level language such as CUDA C is used to efficiently implement a GPU-based solver, i.e., ep2-3De v1.0, can resolve three-dimensional prob- lems in a decent amount of time. This part takes advantages of the massive parallelism of modern GPU architectures. In addition, a first attempt of GPU parallel computing, i.e., multi-GPU codes, is performed to increase even more the performance and to address the on-chip memory limitation. Finally, this GPU-based solver is used to investigate three-dimensional granular collapses and is compared with experimental evidences obtained in the laboratory. This research work demonstrates that the material point method is well suited to resolve small to large elasto-plastic deformations. Moreover, the computational efficiency of the method can be dramatically increased using modern GPU architectures. These allow fast, performant and accurate three- dimensional modelling of landslides, provided that the on-chip memory limi- tation is alleviated with an appropriate parallel strategy

    Antimicrobial Resistance at the Human-Animal Interface

    Get PDF
    Livestock-associated Methicillin-resistant Staphylococcus aureus (MRSA) are an emerging public-health issue in Australia, particularly amongst livestock and animal workers. We examined MRSA, isolated from humans and animals in Australia whole-genome sequencing and identified zoonotic and anthropozoonotic MRSA transmission, and antimicrobial-resistance gene transfer between MRSA of different host origin. This work highlights the need for expanded monitoring of microbial livestock pathogens and indicates the importance of prudent antimicrobial use in animal health

    Safe Water for All: A Multi-Modal Approach to North Alabama\u27s Water Resources

    Get PDF
    Environmental degradation is a destructive force produced by the human disturbance of pollution. It is a phenomenon that gradually evolves landscapes over time resulting in irreversible outcomes. Environmental degradation physically affects spaces’ resources, objects, and inhabiting humans. This study observes the impacts of pollution beyond physical boundaries and how it affects human identity/sense of place through the utilization of geographic information systems. Specifically, it examines cultural identity developed through human experiences and connections to landscapes containing water resources. Following, pollution contaminates water resources disrupting experiences and connections thus causing the cultural identity to disappear. The case study applied to this research is the Alabama cultural identity connected to the Tennessee River that flows through the northern portion of North Alabama. Alabama citizens formulate deep connections to landscapes through farming, attaching religious symbolism to the environment through biblical references, and perform Christian practices with objects found in spaces (Tuan, 1974). Due to the contamination in the Tennessee River, this affects utilization of water for farming and Christian practices performed in the river because of the threat pollution poses. As a result, Alabama cultural identity disappears halt of experiences against an unfamiliar landscape degraded by pollution. Testing this hypothesis, this research utilizes a mixed methods approach applying multiple analyses and models. Participatory observations, surveys, and interviews accomplished the qualitative analysis of Alabama culture. Then, the collection of multiple amounts hydrological data, survey statistics, interviews, poverty data and land use data were inputted into the geographically weighted regression model completing the quantitative analysis of water pollution. The model that was implemented was the Arc Story Map. Then, Arc Story Map presented the data visually for the public

    Machine learning and large scale cancer omic data: decoding the biological mechanisms underpinning cancer

    Get PDF
    Many of the mechanisms underpinning cancer risk and tumorigenesis are still not fully understood. However, the next-generation sequencing revolution and the rapid advances in big data analytics allow us to study cells and complex phenotypes at unprecedented depth and breadth. While experimental and clinical data are still fundamental to validate findings and confirm hypotheses, computational biology is key for the analysis of system- and population-level data for detection of hidden patterns and the generation of testable hypotheses. In this work, I tackle two main questions regarding cancer risk and tumorigenesis that require novel computational methods for the analysis of system-level omic data. First, I focused on how frequent, low-penetrance inherited variants modulate cancer risk in the broader population. Genome-Wide Association Studies (GWAS) have shown that Single Nucleotide Polymorphisms (SNP) contribute to cancer risk with multiple subtle effects, but they are still failing to give further insight into their synergistic effects. I developed a novel hierarchical Bayesian regression model, BAGHERA, to estimate heritability at the gene-level from GWAS summary statistics. I then used BAGHERA to analyse data from 38 malignancies in the UK Biobank. I showed that genes with high heritable risk are involved in key processes associated with cancer and are often localised in genes that are somatically mutated drivers. Heritability, like many other omics analysis methods, study the effects of DNA variants on single genes in isolation. However, we know that most biological processes require the interplay of multiple genes and we often lack a broad perspective on them. For the second part of this thesis, I then worked on the integration of Protein-Protein Interaction (PPI) graphs and omics data, which bridges this gap and recapitulates these interactions at a system level. First, I developed a modular and scalable Python package, PyGNA, that enables robust statistical testing of genesets' topological properties. PyGNA complements the literature with a tool that can be routinely introduced in bioinformatics automated pipelines. With PyGNA I processed multiple genesets obtained from genomics and transcriptomics data. However, topological properties alone have proven to be insufficient to fully characterise complex phenotypes. Therefore, I focused on a model that allows to combine topological and functional data to detect multiple communities associated with a phenotype. Detecting cancer-specific submodules is still an open problem, but it has the potential to elucidate mechanisms detectable only by integrating multi-omics data. Building on the recent advances in Graph Neural Networks (GNN), I present a supervised geometric deep learning model that combines GNNs and Stochastic Block Models (SBM). The model is able to learn multiple graph-aware representations, as multiple joint SBMs, of the attributed network, accounting for nodes participating in multiple processes. The simultaneous estimation of structure and function provides an interpretable picture of how genes interact in specific conditions and it allows to detect novel putative pathways associated with cancer
    corecore