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  1. Article ; Online: Editorial

    Swarup Roy / Pietro Hiram Guzzi / Jugal Kalita

    Frontiers in Bioinformatics, Vol

    Graph representation learning in biological network

    2023  Volume 3

    Keywords graph ; representation learning ; embedding ; complex network ; regulatory network ; protein network ; Computer applications to medicine. Medical informatics ; R858-859.7
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Using dual-network-analyser for communities detecting in dual networks

    Pietro Hiram Guzzi / Giuseppe Tradigo / Pierangelo Veltri

    BMC Bioinformatics, Vol 22, Iss S15, Pp 1-

    2022  Volume 16

    Abstract: Abstract Background Representations of the relationships among data using networks are widely used in several research fields such as computational biology, medical informatics and social network mining. Recently, complex networks have been introduced to ...

    Abstract Abstract Background Representations of the relationships among data using networks are widely used in several research fields such as computational biology, medical informatics and social network mining. Recently, complex networks have been introduced to better capture the insights of the modelled scenarios. Among others, dual networks (DNs) consist of mapping information as pairs of networks containing the same set of nodes but with different edges: one, called physical network, has unweighted edges, while the other, called conceptual network, has weighted edges. Results We focus on DNs and we propose a tool to find common subgraphs (aka communities) in DNs with particular properties. The tool, called Dual-Network-Analyser, is based on the identification of communities that induce optimal modular subgraphs in the conceptual network and connected subgraphs in the physical one. It includes the Louvain algorithm applied to the considered case. The Dual-Network-Analyser can be used to study DNs, to find common modular communities. We report results on using the tool to identify communities on synthetic DNs as well as real cases in social networks and biological data. Conclusion The proposed method has been tested by using synthetic and biological networks. Results demonstrate that it is well able to detect meaningful information from DNs.
    Keywords Dual networks ; Graphs ; Densest subgraph ; Communities ; Social Networks ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
    Subject code 006 ; 000
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: A Novel Algorithm for Local Network Alignment Based on Network Embedding

    Pietro Hiram Guzzi / Giuseppe Tradigo / Pierangelo Veltri

    Applied Sciences, Vol 12, Iss 5403, p

    2022  Volume 5403

    Abstract: Networks are widely used in bioinformatics and biomedicine to represent associations across a large class of biological entities. Network alignment refers to the set of approaches that aim to reveal similarities among networks. Local Network Alignment ( ... ...

    Abstract Networks are widely used in bioinformatics and biomedicine to represent associations across a large class of biological entities. Network alignment refers to the set of approaches that aim to reveal similarities among networks. Local Network Alignment (LNA) algorithms find (relatively small) local regions of similarity between two or more networks. Such algorithms are in general based on a set of seed nodes that are used to build the alignment incrementally. A large fraction of LNA algorithms uses a set of vertices based on context information as seed nodes, even if this may cause a bias or a data-circularity problem. Moreover, using topology information to choose seed nodes improves overall alignment. Finally, similarities among nodes can be identified by network embedding methods (or representation learning). Given there are two networks, we propose to use network embedding to capture structural similarity among nodes, which can also be used to improve LNA effectiveness. We present an algorithm and experimental tests on real and syntactic graph data to find LNAs.
    Keywords LNA ; Local Network Alignment ; topology ; biological entities ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Language English
    Publishing date 2022-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Will Artificial Intelligence Provide Answers to Current Gaps and Needs in Chronic Heart Failure?

    Fabiola Boccuto / Salvatore De Rosa / Daniele Torella / Pierangelo Veltri / Pietro Hiram Guzzi

    Applied Sciences, Vol 13, Iss 7663, p

    2023  Volume 7663

    Abstract: Chronic heart failure (CHF) is a prevalent and multifactorial condition associated with a significant burden of morbidity and mortality. Despite progress in its clinical management, the projected increase in CHF prevalence due to population ageing, ... ...

    Abstract Chronic heart failure (CHF) is a prevalent and multifactorial condition associated with a significant burden of morbidity and mortality. Despite progress in its clinical management, the projected increase in CHF prevalence due to population ageing, increased cardiovascular risk burdens, and advancing diagnostic and therapeutic options have led to a growing burden on healthcare systems and public budgets worldwide. In this context, artificial intelligence (AI) holds promise in assisting clinical decision-making, especially in analysing raw image data and electrocardiogram recordings. This article provides an overview of the current gaps and needs in CHF research and clinical management and the current and under-development AI-powered tools that may address these gaps and needs.
    Keywords heart failure ; artificial intelligence ; cardiology ; machine learning ; neural networks ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Spatio-Temporal Resource Mapping for Intensive Care Units at Regional Level for COVID-19 Emergency in Italy

    Pietro Hiram Guzzi / Giuseppe Tradigo / Pierangelo Veltri

    International Journal of Environmental Research and Public Health, Vol 17, Iss 3344, p

    2020  Volume 3344

    Abstract: COVID-19 is a worldwide emergency since it has rapidly spread from China to almost all the countries worldwide. Italy has been one of the most affected countries after China. North Italian regions, such as Lombardia and Veneto, had an abnormally large ... ...

    Abstract COVID-19 is a worldwide emergency since it has rapidly spread from China to almost all the countries worldwide. Italy has been one of the most affected countries after China. North Italian regions, such as Lombardia and Veneto, had an abnormally large number of cases. COVID-19 patients management requires availability of sufficiently large number of Intensive Care Units (ICUs) beds. Resources shortening is a critical issue when the number of COVID-19 severe cases are higher than the available resources. This is also the case at a regional scale. We analysed Italian data at regional level with the aim to: (i) support health and government decision-makers in gathering rapid and efficient decisions on increasing health structures capacities (in terms of ICU slots) and (ii) define a geographic model to plan emergency and future COVID-19 patients management using reallocating them among health structures. Finally, we retain that the here proposed model can be also used in other countries.
    Keywords COVID-19 ; prediction of infected ; data analysis ; Medicine ; R ; covid19
    Subject code 027
    Language English
    Publishing date 2020-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Book ; Online: Spatio-Temporal Resource Mapping for Intensive Care Units at Regional Level for COVID-19 Emergency in Italy

    Pietro Hiram Guzzi / Giuseppe Tradigo / Pierangelo Veltri

    International Journal of Environmental Research and Public Health ; Volume 17 ; Issue 10

    2020  

    Abstract: COVID-19 is a worldwide emergency since it has rapidly spread from China to almost all the countries worldwide. Italy has been one of the most affected countries after China. North Italian regions, such as Lombardia and Veneto, had an abnormally large ... ...

    Abstract COVID-19 is a worldwide emergency since it has rapidly spread from China to almost all the countries worldwide. Italy has been one of the most affected countries after China. North Italian regions, such as Lombardia and Veneto, had an abnormally large number of cases. COVID-19 patients management requires availability of sufficiently large number of Intensive Care Units (ICUs) beds. Resources shortening is a critical issue when the number of COVID-19 severe cases are higher than the available resources. This is also the case at a regional scale. We analysed Italian data at regional level with the aim to: (i) support health and government decision-makers in gathering rapid and efficient decisions on increasing health structures capacities (in terms of ICU slots) and (ii) define a geographic model to plan emergency and future COVID-19 patients management using reallocating them among health structures. Finally, we retain that the here proposed model can be also used in other countries.
    Keywords COVID-19 ; prediction of infected ; data analysis ; covid19
    Subject code 027
    Language English
    Publishing date 2020-05-12
    Publisher Multidisciplinary Digital Publishing Institute
    Publishing country ch
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Genome mining conformance to metabolite profile of Bacillus strains to control potato pathogens

    Arezoo Lagzian / Roohallah Saberi Riseh / Sajjad Sarikhan / Abozar Ghorbani / Pejman Khodaygan / Rainer Borriss / Pietro Hiram Guzzi / Pierangelo Veltri

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    2023  Volume 12

    Abstract: Abstract Biocontrol agents are safe and effective methods for controlling plant disease pathogens, such as Fusarium solani, which causes dry wilt, and Pectobacterium spp., responsible for potato soft rot disease. Discovering agents that can effectively ... ...

    Abstract Abstract Biocontrol agents are safe and effective methods for controlling plant disease pathogens, such as Fusarium solani, which causes dry wilt, and Pectobacterium spp., responsible for potato soft rot disease. Discovering agents that can effectively control both fungal and bacterial pathogens in potatoes has always presented a challenge. Biological controls were investigated using 500 bacterial strains isolated from rhizospheric microbial communities, along with two promising biocontrol strains: Pseudomonas (T17-4 and VUPf5). Bacillus velezensis (Q12 and US1) and Pseudomonas chlororaphis VUPf5 exhibited the highest inhibition of fungal growth and pathogenicity in both laboratory (48%, 48%, 38%) and greenhouse (100%, 85%, 90%) settings. Q12 demonstrated better control against bacterial pathogens in vivo (approximately 50%). Whole-genome sequencing of Q12 and US1 revealed a genome size of approximately 4.1 Mb. Q12 had 4413 gene IDs and 4300 coding sequences, while US1 had 4369 gene IDs and 4255 coding sequences. Q12 exhibited a higher number of genes classified under functional subcategories related to stress response, cell wall, capsule, levansucrase synthesis, and polysaccharide metabolism. Both Q12 and US1 contained eleven secondary metabolite gene clusters as identified by the antiSMASH and RAST servers. Notably, Q12 possessed the antibacterial locillomycin and iturin A gene clusters, which were absent in US1. This genetic information suggests that Q12 may have a more pronounced control over bacterial pathogens compared to US1. Metabolic profiling of the superior strains, as determined by LC/MS/MS, validated our genetic findings. The investigated strains produced compounds such as iturin A, bacillomycin D, surfactin, fengycin, phenazine derivatives, etc. These compounds reduced spore production and caused deformation of the hyphae in F. solani. In contrast, B. velezensis UR1, which lacked the production of surfactin, fengycin, and iturin, did not affect these structures and failed to inhibit the growth of ...
    Keywords Medicine ; R ; Science ; Q
    Subject code 572
    Language English
    Publishing date 2023-11-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Analysis of age-dependent gene-expression in human tissues for studying diabetes comorbidities

    Pietro Hiram Guzzi / Francesca Cortese / Gaia Chiara Mannino / Elisabetta Pedace / Elena Succurro / Francesco Andreozzi / Pierangelo Veltri

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    2023  Volume 20

    Abstract: Abstract The study of the relationship between type 2 diabetes mellitus (T2DM) disease and other pathologies (comorbidities), together with patient age variation, poses a challenge for medical research. There is evidence that patients affected by T2DM ... ...

    Abstract Abstract The study of the relationship between type 2 diabetes mellitus (T2DM) disease and other pathologies (comorbidities), together with patient age variation, poses a challenge for medical research. There is evidence that patients affected by T2DM are more likely to develop comorbidities as they grow older. Variation of gene expression can be correlated to changes in T2DM comorbidities insurgence and progression. Understanding gene expression changes requires the analysis of large heterogeneous data at different scales as well as the integration of different data sources into network medicine models. Hence, we designed a framework to shed light on uncertainties related to age effects and comorbidity by integrating existing data sources with novel algorithms. The framework is based on integrating and analysing existing data sources under the hypothesis that changes in the basal expression of genes may be responsible for the higher prevalence of comorbidities in older patients. Using the proposed framework, we selected genes related to comorbidities from existing databases, and then analysed their expression with age at the tissues level. We found a set of genes that changes significantly in certain specific tissues over time. We also reconstructed the associated protein interaction networks and the related pathways for each tissue. Using this mechanistic framework, we detected interesting pathways related to T2DM whose genes change their expression with age. We also found many pathways related to insulin regulation and brain activities, which can be used to develop specific therapies. To the best of our knowledge, this is the first study that analyses such genes at the tissue level together with age variations.
    Keywords Medicine ; R ; Science ; Q
    Subject code 616
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: L-HetNetAligner

    Marianna Milano / Tijana Milenković / Mario Cannataro / Pietro Hiram Guzzi

    Scientific Reports, Vol 10, Iss 1, Pp 1-

    A novel algorithm for Local Alignment of Heterogeneous Biological Networks

    2020  Volume 20

    Abstract: Abstract Networks are largely used for modelling and analysing a wide range of biological data. As a consequence, many different research efforts have resulted in the introduction of a large number of algorithms for analysis and comparison of networks. ... ...

    Abstract Abstract Networks are largely used for modelling and analysing a wide range of biological data. As a consequence, many different research efforts have resulted in the introduction of a large number of algorithms for analysis and comparison of networks. Many of these algorithms can deal with networks with a single class of nodes and edges, also referred to as homogeneous networks. Recently, many different approaches tried to integrate into a single model the interplay of different molecules. A possible formalism to model such a scenario comes from node/edge coloured networks (also known as heterogeneous networks) implemented as node/ edge-coloured graphs. Therefore, the need for the introduction of algorithms able to compare heterogeneous networks arises. We here focus on the local comparison of heterogeneous networks, and we formulate it as a network alignment problem. To the best of our knowledge, the local alignment of heterogeneous networks has not been explored in the past. We here propose L-HetNetAligner a novel algorithm that receives as input two heterogeneous networks (node-coloured graphs) and builds a local alignment of them. We also implemented and tested our algorithm. Our results confirm that our method builds high-quality alignments. The following website *contains Supplementary File 1 material and the code.
    Keywords Medicine ; R ; Science ; Q
    Subject code 004 ; 006
    Language English
    Publishing date 2020-03-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Exploiting the molecular basis of age and gender differences in outcomes of SARS-CoV-2 infections

    Daniele Mercatelli / Elisabetta Pedace / Pierangelo Veltri / Federico M. Giorgi / Pietro Hiram Guzzi

    Computational and Structural Biotechnology Journal, Vol 19, Iss , Pp 4092-

    2021  Volume 4100

    Abstract: Motivation: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease, 2019; COVID-19) is associated with adverse outcomes in patients. It has been observed that lethality seems to be related to the age of patients. ... ...

    Abstract Motivation: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease, 2019; COVID-19) is associated with adverse outcomes in patients. It has been observed that lethality seems to be related to the age of patients. While ageing has been extensively demonstrated to be accompanied by some modifications at the gene expression level, a possible link with COVID-19 manifestation still need to be investigated at the molecular level.Objectives: This study aims to shed out light on a possible link between the increased COVID-19 lethality and the molecular changes that occur in elderly people.Methods: We considered public datasets of ageing-related genes and their expression at the tissue level. We selected human proteins interacting with viral ones that are known to be related to the ageing process. Finally, we investigated changes in the expression level of coding genes at the tissue, gender and age level.Results: We observed a significant intersection between some SARS-CoV-2 interactors and ageing-related genes, suggesting that those genes are particularly affected by COVID-19 infection. Our analysis evidenced that virus infection particularly involves ageing molecular mechanisms centred around proteins EEF2, NPM1, HMGA1, HMGA2, APEX1, CHEK1, PRKDC, and GPX4. We found that HMGA1 and NPM1 have different expressions in the lung of males, while HMGA1, APEX1, CHEK1, EEF2, and NPM1 present changes in expression in males due to ageing effects.Conclusion: Our study generated a mechanistic framework to clarify the correlation between COVID-19 incidence in elderly patients and molecular mechanisms of ageing. We also provide testable hypotheses for future investigation and pharmacological solutions tailored to specific age ranges.
    Keywords Data science ; SARS-CoV-2 ; COVID-19 ; Ageing genes ; Interactomes ; Biotechnology ; TP248.13-248.65
    Subject code 616
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
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