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1.
Adv Protein Chem Struct Biol ; 127: 217-248, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34340768

RESUMO

Protein structure characterization is fundamental to understand protein properties, such as folding process and protein resistance to thermal stress, up to unveiling organism pathologies (e.g., prion disease). In this chapter, we provide an overview on how the spectral properties of the networks reconstructed from the Protein Contact Map (PCM) can be used to generate informative observables. As a specific case study, we apply two different network approaches to an example protein dataset, for the aim of discriminating protein folding state, and for the reconstruction of protein 3D structure.


Assuntos
Bases de Dados de Proteínas , Dobramento de Proteína , Mapas de Interação de Proteínas , Proteínas/química , Proteínas/metabolismo , Animais , Humanos , Domínios Proteicos , Estabilidade Proteica
2.
Nat Commun ; 11(1): 6074, 2020 11 27.
Artigo em Inglês | MEDLINE | ID: mdl-33247093

RESUMO

Environmental factors, and in particular diet, are known to play a key role in the development of Coronary Heart Disease. Many of these factors were unveiled by detailed nutritional epidemiology studies, focusing on the role of a single nutrient or food at a time. Here, we apply an Environment-Wide Association Study approach to Nurses' Health Study data to explore comprehensively and agnostically the association of 257 nutrients and 117 foods with coronary heart disease risk (acute myocardial infarction and fatal coronary heart disease). After accounting for multiple testing, we identify 16 food items and 37 nutrients that show statistically significant association - while adjusting for potential confounding and control variables such as physical activity, smoking, calorie intake, and medication use - among which 38 associations were validated in Nurses' Health Study II. Our implementation of Environment-Wide Association Study successfully reproduces prior knowledge of diet-coronary heart disease associations in the epidemiological literature, and helps us detect new associations that were only marginally studied, opening potential avenues for further extensive experimental validation. We also show that Environment-Wide Association Study allows us to identify a bipartite food-nutrient network, highlighting which foods drive the associations of specific nutrients with coronary heart disease risk.


Assuntos
Doença das Coronárias/complicações , Dieta , Infarto do Miocárdio/complicações , Meio Ambiente , Feminino , Humanos , Estudos Longitudinais , Reprodutibilidade dos Testes , Fatores de Risco , Inquéritos e Questionários
3.
Sci Rep ; 10(1): 16191, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-33004889

RESUMO

Thanks to the many chemical and nutritional components it carries, diet critically affects human health. However, the currently available comprehensive databases on food composition cover only a tiny fraction of the total number of chemicals present in our food, focusing on the nutritional components essential for our health. Indeed, thousands of other molecules, many of which have well documented health implications, remain untracked. To explore the body of knowledge available on food composition, we built FoodMine, an algorithm that uses natural language processing to identify papers from PubMed that potentially report on the chemical composition of garlic and cocoa. After extracting from each paper information on the reported quantities of chemicals, we find that the scientific literature carries extensive information on the detailed chemical components of food that is currently not integrated in databases. Finally, we use unsupervised machine learning to create chemical embeddings, finding that the chemicals identified by FoodMine tend to have direct health relevance, reflecting the scientific community's focus on health-related chemicals in our food.


Assuntos
Algoritmos , Bases de Dados Factuais , Análise de Alimentos/métodos , Alimentos/estatística & dados numéricos , PubMed/estatística & dados numéricos , Humanos , Processamento de Linguagem Natural
4.
Nat Commun ; 9(1): 4514, 2018 10 30.
Artigo em Inglês | MEDLINE | ID: mdl-30375513

RESUMO

We characterize different tumour types in search for multi-tumour drug targets, in particular aiming for drug repurposing and novel drug combinations. Starting from 11 tumour types from The Cancer Genome Atlas, we obtain three clusters based on transcriptomic correlation profiles. A network-based analysis, integrating gene expression profiles and protein interactions of cancer-related genes, allows us to define three cluster-specific signatures, with genes belonging to NF-κB signaling, chromosomal instability, ubiquitin-proteasome system, DNA metabolism, and apoptosis biological processes. These signatures have been characterized by different approaches based on mutational, pharmacological and clinical evidences, demonstrating the validity of our selection. Moreover, we define new pharmacological strategies validated by in vitro experiments that show inhibition of cell growth in two tumour cell lines, with significant synergistic effect. Our study thus provides a list of genes and pathways that could possibly be used, singularly or in combination, for the design of novel treatment strategies.


Assuntos
Redes Reguladoras de Genes , Genômica , Neoplasias/tratamento farmacológico , Mapas de Interação de Proteínas , Proteômica , Apoptose/genética , Instabilidade Cromossômica/genética , DNA/metabolismo , Reposicionamento de Medicamentos , Genes Neoplásicos , Ensaios de Triagem em Larga Escala , Humanos , Terapia de Alvo Molecular , NF-kappa B/genética , NF-kappa B/metabolismo , Neoplasias/genética , Neoplasias/metabolismo , Complexo de Endopeptidases do Proteassoma/genética , Complexo de Endopeptidases do Proteassoma/metabolismo , Transdução de Sinais , Transcriptoma , Ubiquitina/genética , Ubiquitina/metabolismo
5.
Sci Rep ; 6: 30367, 2016 07 28.
Artigo em Inglês | MEDLINE | ID: mdl-27464796

RESUMO

Proteins fold using a two-state or multi-state kinetic mechanisms, but up to now there is not a first-principle model to explain this different behavior. We exploit the network properties of protein structures by introducing novel observables to address the problem of classifying the different types of folding kinetics. These observables display a plain physical meaning, in terms of vibrational modes, possible configurations compatible with the native protein structure, and folding cooperativity. The relevance of these observables is supported by a classification performance up to 90%, even with simple classifiers such as discriminant analysis.


Assuntos
Dobramento de Proteína , Proteínas/química , Algoritmos , Cinética , Modelos Teóricos
6.
J Proteome Res ; 15(9): 3298-307, 2016 09 02.
Artigo em Inglês | MEDLINE | ID: mdl-27436276

RESUMO

We approach here the problem of defining and estimating the nature of the metabolite-metabolite association network underlying the human individual metabolic phenotype in healthy subjects. We retrieved significant associations using an entropy-based approach and a multiplex network formalism. We defined a significantly over-represented network formed by biologically interpretable metabolite modules. The entropy of the individual metabolic phenotype is also introduced and discussed.


Assuntos
Entropia , Redes e Vias Metabólicas , Metabolômica/métodos , Voluntários Saudáveis , Humanos , Metaboloma , Fenótipo
7.
Sci Rep ; 6: 20706, 2016 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-26869210

RESUMO

The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has been characterized only on isolated networks, while the vast majority of complex systems are formed by multilayer networks. Here we build a theoretical framework for the linear controllability of multilayer networks by mapping the problem into a combinatorial matching problem. We found that correlating the external signals in the different layers can significantly reduce the multiplex network robustness to node removal, as it can be seen in conjunction with a hybrid phase transition occurring in interacting Poisson networks. Moreover we observe that multilayer networks can stabilize the fully controllable multiplex network configuration that can be stable also when the full controllability of the single network is not stable.

8.
Brief Bioinform ; 17(3): 527-40, 2016 05.
Artigo em Inglês | MEDLINE | ID: mdl-26307062

RESUMO

Systems Medicine (SM) can be defined as an extension of Systems Biology (SB) to Clinical-Epidemiological disciplines through a shifting paradigm, starting from a cellular, toward a patient centered framework. According to this vision, the three pillars of SM are Biomedical hypotheses, experimental data, mainly achieved by Omics technologies and tailored computational, statistical and modeling tools. The three SM pillars are highly interconnected, and their balancing is crucial. Despite the great technological progresses producing huge amount of data (Big Data) and impressive computational facilities, the Bio-Medical hypotheses are still of primary importance. A paradigmatic example of unifying Bio-Medical theory is the concept of Inflammaging. This complex phenotype is involved in a large number of pathologies and patho-physiological processes such as aging, age-related diseases and cancer, all sharing a common inflammatory pathogenesis. This Biomedical hypothesis can be mapped into an ecological perspective capable to describe by quantitative and predictive models some experimentally observed features, such as microenvironment, niche partitioning and phenotype propagation. In this article we show how this idea can be supported by computational methods useful to successfully integrate, analyze and model large data sets, combining cross-sectional and longitudinal information on clinical, environmental and omics data of healthy subjects and patients to provide new multidimensional biomarkers capable of distinguishing between different pathological conditions, e.g. healthy versus unhealthy state, physiological versus pathological aging.


Assuntos
Inflamação , Análise de Sistemas , Biomarcadores , Estudos Transversais , Humanos , Neoplasias , Biologia de Sistemas
9.
Mech Ageing Dev ; 151: 45-53, 2015 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-26209580

RESUMO

MARK-AGE aims at the identification of biomarkers of human aging capable of discriminating between the chronological age and the effective functional status of the organism. To achieve this, given the structure of the collected data, a proper statistical analysis has to be performed, as the structure of the data are non trivial and the number of features under study is near to the number of subjects used, requiring special care to avoid overfitting. Here we described some of the possible strategies suitable for this analysis. We also include a description of the main techniques used, to explain and justify the selected strategies. Among other possibilities, we suggest to model and analyze the data with a three step strategy.


Assuntos
Envelhecimento , Bases de Dados Factuais , Processamento Eletrônico de Dados/métodos , Modelos Teóricos , Feminino , Humanos , Masculino , Processos Estocásticos
10.
Sci Rep ; 5: 10073, 2015 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-25985280

RESUMO

Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant for routing problems, inference and data mining. In real growing networks, topological, structural and geometrical properties emerge spontaneously from their dynamical rules. Nevertheless we still miss a model in which networks develop an emergent complex geometry. Here we show that a single two parameter network model, the growing geometrical network, can generate complex network geometries with non-trivial distribution of curvatures, combining exponential growth and small-world properties with finite spectral dimensionality. In one limit, the non-equilibrium dynamical rules of these networks can generate scale-free networks with clustering and communities, in another limit planar random geometries with non-trivial modularity. Finally we find that these properties of the geometrical growing networks are present in a large set of real networks describing biological, social and technological systems.


Assuntos
Modelos Teóricos , Algoritmos
11.
Mol Biosyst ; 11(7): 1824-31, 2015 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-25909281

RESUMO

We characterize different cell states, related to cancer and ageing phenotypes, by a measure of entropy of network ensembles, integrating gene expression profiling values and protein interaction network topology. In our case studies, network entropy, that by definition estimates the number of possible network instances satisfying the given constraints, can be interpreted as a measure of the "parameter space" available to the cell. Network entropy was able to characterize specific pathological conditions: normal versus cancer cells, primary tumours that developed metastasis or relapsed, and extreme longevity samples. Moreover, this approach has been applied at different scales, from whole network to specific subnetworks (biological pathways defined on a priori biological knowledge) and single nodes (genes), allowing a deeper understanding of the cell processes involved.


Assuntos
Neoplasias/metabolismo , Mapas de Interação de Proteínas , Envelhecimento , Algoritmos , Progressão da Doença , Entropia , Perfilação da Expressão Gênica , Humanos , Modelos Biológicos , Neoplasias/patologia
12.
Phys Rev Lett ; 113(7): 078701, 2014 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-25170736

RESUMO

The problem of controllability of the dynamical state of a network is central in network theory and has wide applications ranging from network medicine to financial markets. The driver nodes of the network are the nodes that can bring the network to the desired dynamical state if an external signal is applied to them. Using the framework of structural controllability, here, we show that the density of nodes with in degree and out degree equal to one and two determines the number of driver nodes in the network. Moreover, we show that random networks with minimum in degree and out degree greater than two, are always fully controllable by an infinitesimal fraction of driver nodes, regardless of the other properties of the degree distribution. Finally, based on these results, we propose an algorithm to improve the controllability of networks.


Assuntos
Algoritmos , Modelos Teóricos , Simulação por Computador
13.
PLoS One ; 9(6): e97857, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-24906003

RESUMO

One of the most important challenges in network science is to quantify the information encoded in complex network structures. Disentangling randomness from organizational principles is even more demanding when networks have a multiplex nature. Multiplex networks are multilayer systems of [Formula: see text] nodes that can be linked in multiple interacting and co-evolving layers. In these networks, relevant information might not be captured if the single layers were analyzed separately. Here we demonstrate that such partial analysis of layers fails to capture significant correlations between weights and topology of complex multiplex networks. To this end, we study two weighted multiplex co-authorship and citation networks involving the authors included in the American Physical Society. We show that in these networks weights are strongly correlated with multiplex structure, and provide empirical evidence in favor of the advantage of studying weighted measures of multiplex networks, such as multistrength and the inverse multiparticipation ratio. Finally, we introduce a theoretical framework based on the entropy of multiplex ensembles to quantify the information stored in multiplex networks that would remain undetected if the single layers were analyzed in isolation.


Assuntos
Redes Neurais de Computação
14.
Artigo em Inglês | MEDLINE | ID: mdl-25615157

RESUMO

Multiplex networks describe a large number of systems ranging from social networks to the brain. These multilayer structure encode information in their structure. This information can be extracted by measuring the correlations present in the multiplex networks structure, such as the overlap of the links in different layers. Many multiplex networks are also weighted, and the weights of the links can be strongly correlated with the structural properties of the multiplex network. For example, in multiplex network formed by the citation and collaboration networks between PRE scientists it was found that the statistical properties of citations to coauthors differ from the one of citations to noncoauthors, i.e., the weights depend on the overlap of the links. Here we present a theoretical framework for modeling multiplex weighted networks with different types of correlations between weights and overlap. To this end, we use the framework of canonical network ensembles, and the recently introduced concept of multilinks, showing that null models of a large variety of network structures can be constructed in this way. In order to provide a concrete example of how this framework apply to real data we consider a multiplex constructed from gene expression data of healthy and cancer tissues.

15.
Theor Biol Forum ; 107(1-2): 77-87, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25936214

RESUMO

In this paper we introduce the framework for the application of statistical mechanics to network theory, with a particular emphasis to the concept of entropy of network ensembles. This formalism provides novel observables and insights for the analysis of high-throughput transcriptomics data, integrated with apriori biological knowledge, embedded in-to available public databases of protein-protein interaction and cell signaling.


Assuntos
Bases de Dados Genéticas , Genômica/métodos , Modelos Estatísticos , Biologia de Sistemas , Animais , Entropia , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Análise de Sequência com Séries de Oligonucleotídeos , Mapeamento de Interação de Proteínas , Mapas de Interação de Proteínas , RNA Mensageiro/metabolismo
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