Multilayer network methodologies for brain data analysis and modelling

The term neuroscience includes in itself a plethora of research areas devoted to undercover the most fascinating complex organ of our body: the brain. A common denominator of neuroscience areas, is the need for the application of methodologies to integrate different features. In this thesis, we focused on the analysis of two types of brain data: brain data coming from Traumatic Brain Injury (TBI) patients and data collected for the study of neurocognitive healthy ageing. In both cases there was the need of applying computational techniques able to integrate different features. To do so we used multilayer networks. For two groups of TBI patients (adults and paediatrics), time series data were collected from the observations of IntraCranial Pressure (ICP) and Heart Rate (HR). We first detected events of simultaneous increase of HR and ICP, which we called brain-heart crosstalks. Subsequently time series were translated into graphs, and network measures, during brain-heart crosstalks, were obtained. These were then included as predictors in a mortality outcome model, with crosstalks. Causality measures were also investigated, using a Granger causality approach, to understand the dynamics of signals during these events. We further applied multilayer networks to study neurocognitive ageing. To do so, we implemented a pipeline for community detection, which we called NetRank, applying it to the Cam-CAN, a large cross-sectional cohort for the study of healthy neurocognitive ageing. Using multilayer networks modelling, we identified subgroups of individuals, with similar lifestyles, and we related them to structural and functional brain features. We believe that multilayer networks and their extensions represent a powerful tool to be used in integrative and cross modal neuroscience datasets. New insights on cognitive neuroscience and time series analysis, can in fact be gained trough multilayer network, possibly improving patients managements and allowing to develop new predictive tools.EPSR

Challenges in biomedical data science: data-driven solutions to clinical questions

Data are influencing every aspect of our lives, from our work activities, to our spare time and even to our health. In this regard, medical diagnosis and treatments are often supported by quantitative measures and observations, such as laboratory tests, medical imaging or genetic analysis. In medicine, as well as in several other scientific domains, the amount of data involved in each decision-making process has become overwhelming. The complexity of the phenomena under investigation and the scale of modern data collections has long superseded human analysis and insights potential

XXI SPB CONGRESS BOOK

The University of Évora welcomes YOU at the XXI SPB National Congress of Biochemistry 2020 in 14-16 October 2021 either in person or online! Under challenging conditions, due to the COVID-19 pandemic, we have managed to organize the National Congress of Biochemistry in a hybrid format, where at least 2/3 of the participants will come to Évora in person. With the pandemic under control and we hope to carry out the Congress both successfully as well as safely. This is the main meeting point for Portuguese Biochemistry Academy, fostering the discussion and dissemination of high-quality research in Biochemistry, both fundamental and applied, taking place in Portugal. The Scientific Program covers a wide range of issues, from Health and Disease to Environment and Drugs development, where Biochemistry is either fundamental or instrumental in the study of complex and transdisciplinary problems in the society. The Congress is a moment of Science and Innovation in several Biochemistry domains, sharing experiences and fostering healthy confraternization. Despite the difficult context, over 160 confirmed registrations and >120 abstracts were submitted, involving the whole Portuguese Biochemical community. Moreover, this year for the first time the Congress has gone eco-friendly, with ePosters only where short poster presentations are encouraged. We hope the congress meets your expectations! The Organizing Committee, on behalf of the Portuguese Biochemical Society, looks forward meeting you, at Colégio do Espírito Santo, University of Évora!Sociedade Portuguesa de Bioquímica - SPB; Biochem; Instituto de Ciências da Terra - ICT; Fundação Eugénio de Almeida; Câmara Municipal de Évora; Universidade de Évora; Labor Spirit; Terrius; Nitrifresco; Evora Hotel

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Prevention and Reversal of Peripheral Neuropathy/Peripheral Arterial Disease

This monograph presents a five-step treatment protocol to prevent and reverse Peripheral Neuropathy (PN)/Peripheral Arterial Disease (PAD), based on the following systemic medical principle: at the present time, removal of cause is a necessary, but not necessarily sufficient, condition for restorative treatment to be effective. Implementation of the five-step PN/PAD treatment protocol is as follows: Step 1: Obtain a detailed medical and habit/exposure history from the patient. Step 2: Administer written and clinical performance and behavioral tests to assess the severity of the higher-level symptoms and degradation of executive functions Step 3: Administer laboratory tests (blood, urine, imaging, etc) Step 4: Eliminate ongoing PN/PAD contributing factors Step 5: Implement PN/PAD treatments This individually-tailored PN/PAD treatment protocol can be implemented with the data currently available in the biomedical literature. Additionally, while the methodology developed for this study was applied to comprehensive identification of diagnostics, contributing factors, and treatments for PN/PAD, it is general and applicable to any chronic disease/condition that, like PN/PAD, has an associated substantial research literature. Thus, the protocol and methodology developed to prevent or reverse PN/PAD can be used to prevent or reverse any chronic disease (with the possible exceptions of individuals with strong genetic predispositions to the disease in question or who have suffered irreversible damage from the disease)