Paolo Tieri

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Verified

Paolo verified their affiliation via an institutional email.

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• PhD
• Senior Researcher at Italian National Research Council

The intrinsic complexity of human biology presents ongoing challenges to scientific understanding. Researchers collaborate across disciplines to expand our knowledge of the biological interactions that define human life. AI methodologies have emerged as powerful tools across scientific domains, particularly in computational biology, where graph dat...

Mechanotransduction is the process that enables the conversion of mechanical cues into biochemical signaling. While all our cells are well known to be sensitive to such stimuli, the details of the systemic interaction between mechanical input and inflammation are not well integrated. Often, indeed, they are considered and studied in relatively comp...

Leishmania spp. commonly infects phagocytic cells of the immune system, particularly macrophages, employing various immune evasion strategies that enable their survival by altering the intracellular environment. In mammals, these parasites establish persistent infections by modulating gene expression in macrophages, thus interfering with immune sig...

Mechanotransduction is the process that enables the conversion of mechanical cues into biochemical signaling. While all our cells are well known to be sensitive to such stimuli, the details of the systemic interaction between mechanical input and inflammation are not always well integrated. Often, they are considered and studied in relatively compa...

This chapter explores key aspects of the reconstruction and the use of networks in biology and medicine. The application of experimental, mathematical, and computational techniques and data integration allows for a systemic view and predictive models of biological systems. Networks have been a powerful tool in representing and analyzing complex sys...

Regular physical exercise and appropriate nutrition affect metabolic and hormonal responses and may reduce the risk of developing chronic non-communicable diseases such as high blood pressure, ischemic stroke, coronary heart disease, some types of cancer, and type 2 diabetes mellitus. Computational models describing the metabolic and hormonal chang...

Motivation Gene–disease associations are fundamental for understanding disease etiology and developing effective interventions and treatments. Identifying genes not yet associated with a disease due to a lack of studies is a challenging task in which prioritization based on prior knowledge is an important element. The computational search for new c...

Assessing the validity of a psychometric test is fundamental to ensure a reliable interpretation of its outcomes. Few attempts have been made recently to complement classical approaches (e.g., factor models) with a novel technique based on network analysis. The objective of the current study is to carry out a network-based validation of the Eating...

The possibility to computationally prioritize candidate disease genes capitalizing on existing information has led to a speedup in the discovery of new methods. Many gene discovery techniques exploit network data, like protein-protein interactions (PPIs), in order to extract knowledge from the network structure relying on several network metrics. W...

Background Network science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. One category of mental disorders, relevant for their severity, i...

Special Issue Proposal: Network Science and Artificial Intelligence for Biomedicine & Health Informatics @ BIBM 2022, Las Vegas

Drug repurposing is a highly active research area, aiming at finding novel uses for drugs that have been previously developed for other therapeutic purposes. Despite the flourishing of methodologies, success is still partial, and different approaches offer, each, peculiar advantages. In this composite landscape, we present a novel methodology focus...

Primary biliary cholangitis (PBC) is a chronic, cholestatic, immune-mediated, and progressive liver disorder. Treatment to preventing the disease from advancing into later and irreversible stages is still an unmet clinical need. Accordingly, we set up a drug repurposing framework to find potential therapeutic agents targeting relevant pathways deri...

The traditional approach in medicine starts with investigating patients' symptoms to make a diagnosis. While with the advent of precision medicine, a diagnosis results from several factors that interact and need to be analyzed together. This added complexity asks for increased support for medical personnel in analyzing these data altogether. Our ob...

Background and aim: The current unmet needs in understanding primary biliary cholangitis (PBC) pathogenesis, as well as the inefficacy of conventional therapies, have fueled the search for its etiological-pathogenetic determinants and novel approaches to developing unique immunomodulatory drugs. In this study, we aimed to investigate new potential...

Background and aim: The current unmet needs in understanding primary biliary cholangitis (PBC) pathogenesis, as well as the inefficacy of conventional therapies, have fueled the search for its etiological-pathogenetic determinants and novel approaches to developing unique immunomodulatory drugs. In this study, we aimed to investigate new potential...

Network science represents a powerful and increasingly promising method for studying complex real-world problems. In the last decade, it has been applied to psychometric data in the attempt to explain psychopathologies as complex systems of causally interconnected symptoms. With this work, we aimed to review a large sample of network-based studies...

Aggregating transcriptomics data across hospitals can increase sensitivity and robustness of differential expression analyses, yielding deeper clinical insights. As data exchange is often restricted by privacy legislation, meta-analyses are frequently employed to pool local results. However, the accuracy might drop if class labels are inhomogeneous...

Positive-Unlabelled (PU) learning is the machine learning setting in which only a set of positive instances are labelled, while the rest of the data set is unlabelled. The unlabelled instances may be either unspecified positive samples or true negative samples. Over the years, many solutions have been proposed to deal with PU learning. Some techniq...

Motivation Unsupervised learning approaches are frequently employed to stratify patients into clinically relevant subgroups and to identify biomarkers such as disease-associated genes. However, clustering and biclustering techniques are oblivious to the functional relationship of genes and are thus not ideally suited to pinpoint molecular mechanism...

Background The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology of the disease and simulates the immunological and metabolic alterations linked to type-2 diabetes s...

Despite the international guide-lines on the containment of the coronavirus disease 2019 (COVID-19) pandemic, the European scientific community was not sufficiently prepared to coordinate scientific efforts. To improve preparedness for future pandemics, we have initiated a network of nine European-funded Cooperation in Science and Technology (COST)...

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promi...

Coronavirus disease 2019 (COVID-19) death rate differs depending on sex: in Chinese confirmed cases, while the infection rate among men and women is similar, the death rate among men is 4.7% compared with 2.8% for women1. Italian data are similar as the reported death rate in men is significantly higher than that in women, 16.6% vs. 9.1%, respectiv...

Background: Systems Medicine is a novel approach to medicine, i.e. an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral...

The ongoing COVID-19 pandemic still requires fast and effective efforts from all fronts, including epidemiology, clinical practice, molecular medicine, and pharmacology. A comprehensive molecular framework of the disease is needed to better understand its pathological mechanisms, and to design successful treatments able to slow down and stop the im...

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In t...

Drug research, therapy development, and other areas of pharmacology and medicine can benefit from simulations and optimization of mathematical models that contain a mathematical description of interactions between systems elements at the cellular, tissue, organ, body, and population level. This approach is the foundation of systems medicine and pre...

The pandemic caused by SARS-CoV-2 represents an open and unresolved challenge for the global health system. The need to identify drugs that demonstrate efficacy in countering both the mechanisms of interaction of SARS-CoV-2 with host cells and to control the devastating inflammatory phenomena that characterize the late stages of viral infection, re...

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein–protein interaction networks, correlation‐based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approac...

Simulated data is crucial for evaluating epistasis detection tools in genome-wide association studies. Existing simulators are limited, as they do not account for linkage disequilibrium (LD), support limited interaction models of single nucleotide polymorphisms (SNPs) and only dichotomous phenotypes, or depend on proprietary software. In contrast,...

Motivation Unsupervised learning approaches are frequently employed to identify patient subgroups and biomarkers such as disease-associated genes. Thus, clustering and biclustering are powerful techniques often used with expression data, but are usually not suitable to unravel molecular mechanisms along with patient subgroups. To alleviate this, we...

Macrophages are key actors of the immune defense. They play a pivotal role in eliciting the primary immune response to frequently encountered antigens and to initiate and steer the adaptive immune reaction to less common pathogens. Computational modeling of the immune response cannot refrain from describing their role during the various phases of t...

Background: Systems Medicine is a novel approach to medicine, i.e. an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral...

Network-based ranking methods (e.g., centrality analysis) have found extensive use in systems biology and network medicine for the prediction of essential proteins, for the prioritization of drug targets candidates in the treatment of several pathologies and in biomarker discovery, and for human disease genes identification. We here studied the con...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Investigation about the mechanisms involved in the onset of type 2 diabetes in absence of familiarity is the focus of a research project which has led to the development of a computational model that recapitulates the aetiology of the disease. The model simulates the metabolic and immunological alterations related to type-2 diabetes associated to s...

Poster no. SNM-5, Presented at the Systems/Network Medicine in Clinical Practice session

Sex dimorphism in cell response to stress has previously been investigated by different research groups. This dimorphism could be at least in part accounted for by sex-biased expression of regulatory elements such as microRNAs (miRs). In order to spot previously unknown miR expression differences we took advantage of prior knowledge on specialized...

Background: Type 2 diabetes (T2D) is a chronic metabolic disease potentially leading to serious widespread tissue damage. Human organism develops T2D when the glucose-insulin control is broken for reasons that are not fully understood but have been demonstrated to be linked to the emergence of a chronic inflammation. Indeed such low-level chronic...

Macrophages derived from monocyte precursors undergo specific polarization processes which are influenced by the local tissue environment: classically activated (M1) macrophages, with a pro-inflammatory activity and a role of effector cells in Th1 cellular immune responses, and alternatively activated (M2) macrophages, with anti-inflammatory functi...

The beneficial effects of physical activity for the prevention and management of several chronic diseases are widely recognized. Mathematical modeling of the effects of physical exercise in body metabolism and in particular its influence on the control of glucose homeostasis is of primary importance in the development of eHealth monitoring devices...

Sensitivity analysis. Dynamics of insulin concentration for the sensitivity analysis in the first procedure. (TIF)

Sensitivity analysis. Dynamics of insulin for the sensitivity analysis after estimating the parameter k5. (TIF)

Metabolites and reactions. Metabolites and reactions in the computational model of fuel homeostasis by Kim et al. [13]. (TEX)

The Kim computational model. Brief description of the whole-body computational model by Kim et al. [13]. (TEX)

Sensitivity analysis. We have performed a sensitivity analysis to understand how the values of BW, Tv and k5 impact on the key variable plasma insulin concentration. (TEX)

Sensitivity analysis. Dynamics of insulin for the sensitivity analysis in the second procedure. (TIF)

Systems biology focuses on the integration of experimental, mathematical and computational techniques to develop systemic views and predictive models of biological systems. In this perspective, the concept of network has been a powerful tool for the representation and the analysis of complex systems: during the last two decades, the so-called netwo...

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 O...

Infection by Leishmania protozoan parasites can cause a variety of disease outcomes in humans and other mammals, from single self-healing cutaneous lesions to a visceral dissemination of the parasite. The correlation between chronic lesions and ecto-nucleotidase enzymes activity on the surface of the parasite is addressed here using damage caused i...

The change in interest from identifying individual molecules to several components in biological samples as well as how they interact is addressed by systems biology. Mathematical, statistical, and computational methods have emerged to deal with the biological complexity exposed in past years by the massive production of high-throughput data throug...

Background Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions. Methods Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory). Results To test the model, we simulated a large...

Full text: https://dx.doi.org/10.1016/j.arr.2016.11.005 Immunosenescence is thought to result from cellular aging and to reflect exposure to environmental stressors and antigens, including cytomegalovirus (CMV). However, not all of the features of immunosenescence are consistent with this view, and this has led to the emergence of the sister theor...

THIS IS A TRANSLATION OF THE ORIGINAL DOCUMENT "NETWORK LITERACY" AVAILABLE AT https://sites.google.com/a/binghamton.edu/netscied/teaching-learning/network-concepts Mentre il nostro mondo diventa sempre più connesso attraverso l'uso di reti, o network, che rendono le comunicazioni e la diffusione di informazioni pressoché istantanee, il livello di...

Recurrent focal neuropathy with liability to pressure palsies is a relatively frequent autosomal-dominant demyelinating neuropathy linked to peripheral myelin protein 22 (PMP22) gene deletions. The combination of PMP22 gene mutations with other genetic variants is known to cause a more severe phenotype than expected. We present the case of a patien...

One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasin...

Objective: To provide a frame to estimate the systemic impact (side/adverse events) of (novel) therapeutic targets by taking into consideration drugs potential on the numerous districts involved in rheumatoid arthritis (RA) from the inflammatory and immune response to the gut-intestinal (GI) microbiome. Methods: We curated the collection of molecul...

The complex differentiation process of the CD4+ T helper lymphocytes shapes the form and the range of the immune response to different antigenic challenges. Few mathematical and computational models have addressed this key phenomenon. We here present a multiscale approach in which two different levels of description, i.e. a gene regulatory network...

The conceptualization of immunological self is amongst the most important theories of modern biology, representing a sort of theoretical guideline for experimental immunologists, in order to understand how host constituents are ignored by the immune system (IS). A consistent advancement in this field has been represented by the danger/damage theory...

http://www.researchprotocols.org/2013/2/e44/ Type 2 diabetes mellitus (T2D) is a common age-related disease, and is a major health concern, particularly in developed countries where the population is aging, including Europe. The multi-scale immune system simulator for the onset of type 2 diabetes (MISSION-T2D) is a European Union-funded project th...

Background: issues and limitations related to accessibility, understandability and ease of use of signalling pathway databases may hamper or divert research workflow, leading, in the worst case, to the generation of confusing reference frameworks and misinterpretation of experimental results. In an attempt to retrieve signalling pathway data relat...

Genetic association studies of age-related, chronic human diseases often suffer from a lack of power to detect modest effects. Here we propose an alternative approach of including healthy centenarians as a more homogeneous and extreme control group. As a proof of principle we focused on type 2 diabetes (T2D) and assessed /genotypic associations of...

Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, r...

gene identifiers extracted from a manually curated list of NF-κB-downstream genes [13] and from the Transcriptional Regulatory Elements Database (TRED; [83], [84]), and related protein unique identifiers (Uniprot IDs) obtained using online ID converter tools [85] used to compile DG dataset. (XLS)

overrepresented KEGG pathways in DI, U, MC and DG datasets. (XLSX)

complete Cytoscape network session with full datasets and interactomes. (RAR)

Uniprot annotations retrieved and used to populate protein dataset U. (XLS)

Among the most important theories of modern biologica) thought, the concept of immune self appeared as a tacit assumption in the speculations of cellular pathologists and physiologists in the second half of the Nineteenth century. Thanks to its first conceptualization advanced by Burnet in the 1950's, immune self gained the central stage during the...

Omics data and computational approaches are today providing a key to disentangle the complex architecture of living systems. The integration and analysis of data of different nature allows to extract meaningful representations of signaling pathways and protein interactions networks, helpful in achieving an increased understanding of such intricate...

One of the phenomena observed in human aging is the progressive increase of a systemic inflammatory state, a condition referred to as “inflammaging”, negatively correlated with longevity. The five components of the Nuclear Factor kB (NF-kB) family are prominent mediators of inflammation. Several different signaling pathways activated by very divers...

In a systems biology perspective, protein-protein interactions (PPI) are encoded in machine-readable formats to avoid issues encountered in their retrieval for the reconstruction of comprehensive interaction maps and biological pathways. However, the information stored in electronic formats currently used doesn't allow a valid automatic reconstruct...