55 research outputs found

    New Polynomial-Based Molecular Descriptors with Low Degeneracy

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    In this paper, we introduce a novel graph polynomial called the ‘information polynomial’ of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power

    Integrative Network Biology: Graph Prototyping for Co-Expression Cancer Networks

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    Network-based analysis has been proven useful in biologically-oriented areas, e.g., to explore the dynamics and complexity of biological networks. Investigating a set of networks allows deriving general knowledge about the underlying topological and functional properties. The integrative analysis of networks typically combines networks from different studies that investigate the same or similar research questions. In order to perform an integrative analysis it is often necessary to compare the properties of matching edges across the data set. This identification of common edges is often burdensome and computational intensive. Here, we present an approach that is different from inferring a new network based on common features. Instead, we select one network as a graph prototype, which then represents a set of comparable network objects, as it has the least average distance to all other networks in the same set. We demonstrate the usefulness of the graph prototyping approach on a set of prostate cancer networks and a set of corresponding benign networks. We further show that the distances within the cancer group and the benign group are statistically different depending on the utilized distance measure

    Reduced Plasmodium vivax Erythrocyte Infection in PNG Duffy-Negative Heterozygotes

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    BACKGROUND: Erythrocyte Duffy blood group negativity reaches fixation in African populations where Plasmodium vivax (Pv) is uncommon. While it is known that Duffy-negative individuals are highly resistant to Pv erythrocyte infection, little is known regarding Pv susceptibility among heterozygous carriers of a Duffy-negative allele (+/−). Our limited knowledge of the selective advantages or disadvantages associated with this genotype constrains our understanding of the effect that interventions against Pv may have on the health of people living in malaria-endemic regions. METHODS AND FINDINGS: We conducted cross-sectional malaria prevalence surveys in Papua New Guinea (PNG), where we have previously identified a new Duffy-negative allele among individuals living in a region endemic for all four human malaria parasite species. We evaluated infection status by conventional blood smear light microscopy and semi-quantitative PCR-based strategies. Analysis of a longitudinal cohort constructed from our surveys showed that Duffy heterozygous (+/−) individuals were protected from Pv erythrocyte infection compared to those homozygous for wild-type alleles (+/+) (log-rank tests: LM, p = 0.049; PCR, p = 0.065). Evaluation of Pv parasitemia, determined by semi-quantitative PCR-based methods, was significantly lower in Duffy +/− vs. +/+ individuals (Mann-Whitney U: p = 0.023). Overall, we observed no association between susceptibility to P. falciparum erythrocyte infection and Duffy genotype. CONCLUSIONS: Our findings provide the first evidence that Duffy-negative heterozygosity reduces erythrocyte susceptibility to Pv infection. As this reduction was not associated with greater susceptibility to Pf malaria, our in vivo observations provide evidence that Pv-targeted control measures can be developed safely

    Demographic, clinical and antibody characteristics of patients with digital ulcers in systemic sclerosis: data from the DUO Registry

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    OBJECTIVES: The Digital Ulcers Outcome (DUO) Registry was designed to describe the clinical and antibody characteristics, disease course and outcomes of patients with digital ulcers associated with systemic sclerosis (SSc). METHODS: The DUO Registry is a European, prospective, multicentre, observational, registry of SSc patients with ongoing digital ulcer disease, irrespective of treatment regimen. Data collected included demographics, SSc duration, SSc subset, internal organ manifestations, autoantibodies, previous and ongoing interventions and complications related to digital ulcers. RESULTS: Up to 19 November 2010 a total of 2439 patients had enrolled into the registry. Most were classified as either limited cutaneous SSc (lcSSc; 52.2%) or diffuse cutaneous SSc (dcSSc; 36.9%). Digital ulcers developed earlier in patients with dcSSc compared with lcSSc. Almost all patients (95.7%) tested positive for antinuclear antibodies, 45.2% for anti-scleroderma-70 and 43.6% for anticentromere antibodies (ACA). The first digital ulcer in the anti-scleroderma-70-positive patient cohort occurred approximately 5 years earlier than the ACA-positive patient group. CONCLUSIONS: This study provides data from a large cohort of SSc patients with a history of digital ulcers. The early occurrence and high frequency of digital ulcer complications are especially seen in patients with dcSSc and/or anti-scleroderma-70 antibodies

    Quantitative Network Measures as Biomarkers for Classifying Prostate Cancer Disease States: A Systems Approach to Diagnostic Biomarkers

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    <div><p>Identifying diagnostic biomarkers based on genomic features for an accurate disease classification is a problem of great importance for both, basic medical research and clinical practice. In this paper, we introduce quantitative network measures as <i>structural biomarkers</i> and investigate their ability for classifying disease states inferred from gene expression data from prostate cancer. We demonstrate the utility of our approach by using eigenvalue and entropy-based graph invariants and compare the results with a conventional biomarker analysis of the underlying gene expression data.</p></div

    Undirected example graphs .

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    <p>Undirected example graphs .</p

    Characteristics of the spectra concerning MS 2265 and AG 3982.

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    <p>Characteristics of the spectra concerning MS 2265 and AG 3982.</p

    Calculation of sensitivity index for two chemical databases.

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    <p>Calculation of sensitivity index for two chemical databases.</p
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