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  • 1
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    Drug–target interaction prediction through domain-tuned network-based inference
    Oxford University Press (OUP) ; 2013
    In:  Bioinformatics Vol. 29, No. 16 ( 2013-08-15), p. 2004-2008
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 29, No. 16 ( 2013-08-15), p. 2004-2008
    Abstract: Motivation: The identification of drug–target interaction (DTI) represents a costly and time-consuming step in drug discovery and design. Computational methods capable of predicting reliable DTI play an important role in the field. Recently, recommendation methods relying on network-based inference (NBI) have been proposed. However, such approaches implement naive topology-based inference and do not take into account important features within the drug–target domain. Results: In this article, we present a new NBI method, called domain tuned-hybrid (DT-Hybrid), which extends a well-established recommendation technique by domain-based knowledge including drug and target similarity. DT-Hybrid has been extensively tested using the last version of an experimentally validated DTI database obtained from DrugBank. Comparison with other recently proposed NBI methods clearly shows that DT-Hybrid is capable of predicting more reliable DTIs. Availability: DT-Hybrid has been developed in R and it is available, along with all the results on the predictions, through an R package at the following URL: http://sites.google.com/site/ehybridalgo/. Contact:  apulvirenti@dmi.unict.it Supplementary information:  Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/btt307
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2013
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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  • 2
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    PANPROVA: pangenomic prokaryotic evolution of full assemblies
    Oxford University Press (OUP) ; 2022
    In:  Bioinformatics Vol. 38, No. 9 ( 2022-04-28), p. 2631-2632
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 38, No. 9 ( 2022-04-28), p. 2631-2632
    Abstract: Computational tools for pangenomic analysis have gained increasing interest over the past two decades in various applications such as evolutionary studies and vaccine development. Synthetic benchmarks are essential for the systematic evaluation of their performance. Currently, benchmarking tools represent a genome as a set of genetic sequences and fail to simulate the complete information of the genomes, which is essential for evaluating pangenomic detection between fragmented genomes. Results We present PANPROVA, a benchmark tool to simulate prokaryotic pangenomic evolution by evolving the complete genomic sequence of an ancestral isolate. In this way, the possibility of operating in the preassembly phase is enabled. Gene set variations, sequence variation and horizontal acquisition from a pool of external genomes are the evolutionary features of the tool. Availability and implementation PANPROVA is publicly available at https://github.com/InfOmics/PANPROVA. The manuscript explicitelly refers to the github repository. Supplementary information Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4803 , 1367-4811
    URL: Article
    DOI: 10.1093/bioinformatics/btac158
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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  • 3
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    On the Variable Ordering in Subgraph Isomorphism Algorithms
    Institute of Electrical and Electronics Engineers (IEEE) ; 2017
    In:  IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 14, No. 1 ( 2017-1-1), p. 193-203
    Details
    In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Institute of Electrical and Electronics Engineers (IEEE), Vol. 14, No. 1 ( 2017-1-1), p. 193-203
    Type of Medium: Online Resource
    ISSN: 1545-5963 , 1557-9964 , 2374-0043
    URL: Article
    DOI: 10.1109/TCBB.2016.2515595
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2017
    detail.hit.zdb_id: 2158957-4
    SSG: 12
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  • 4
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    Intracerebral overexpression of miR-669c is protective in mouse ischemic stroke model by targeting MyD88 and inducing alternative microglial/macrophage activation
    Springer Science and Business Media LLC ; 2020
    In:  Journal of Neuroinflammation Vol. 17, No. 1 ( 2020-12)
    Details
    In: Journal of Neuroinflammation, Springer Science and Business Media LLC, Vol. 17, No. 1 ( 2020-12)
    Abstract: Ischemic stroke is a devastating disease without a cure. The available treatments for ischemic stroke, thrombolysis by tissue plasminogen activator, and thrombectomy are suitable only to a fraction of patients and thus novel therapeutic approaches are urgently needed. The neuroinflammatory responses elicited secondary to the ischemic attack further aggravate the stroke-induced neuronal damage. It has been demonstrated that these responses are regulated at the level of non-coding RNAs, especially miRNAs. Methods We utilized lentiviral vectors to overexpress miR-669c in BV2 microglial cells in order to modulate their polarization. To detect whether the modulation of microglial activation by miR-669c provides protection in a mouse model of transient focal ischemic stroke, miR-669c overexpression was driven by a lentiviral vector injected into the striatum prior to induction of ischemic stroke. Results Here, we demonstrate that miR-669c-3p, a member of chromosome 2 miRNA cluster (C2MC), is induced upon hypoxic and excitotoxic conditions in vitro and in two different in vivo models of stroke. Rather than directly regulating the neuronal survival in vitro, miR-669c is capable of attenuating the microglial proinflammatory activation in vitro and inducing the expression of microglial alternative activation markers arginase 1 (Arg1), chitinase-like 3 (Ym1), and peroxisome proliferator-activated receptor gamma (PPAR-γ). Intracerebral overexpression of miR-669c significantly decreased the ischemia-induced cell death and ameliorated the stroke-induced neurological deficits both at 1 and 3 days post injury (dpi). Albeit miR-669c overexpression failed to alter the overall Iba1 protein immunoreactivity, it significantly elevated Arg1 levels in the ischemic brain and increased colocalization of Arg1 and Iba1. Moreover, miR-669c overexpression under cerebral ischemia influenced several morphological characteristics of Iba1 positive cells. We further demonstrate the myeloid differentiation primary response gene 88 (MyD88) transcript as a direct target for miR-669c-3p in vitro and show reduced levels of MyD88 in miR-669c overexpressing ischemic brains in vivo. Conclusions Collectively, our data provide the evidence that miR-669c-3p is protective in a mouse model of ischemic stroke through enhancement of the alternative microglial/macrophage activation and inhibition of MyD88 signaling. Our results accentuate the importance of controlling miRNA-regulated responses for the therapeutic benefit in conditions of stroke and neuroinflammation.
    Type of Medium: Online Resource
    ISSN: 1742-2094
    URL: Article
    DOI: 10.1186/s12974-020-01870-w
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2156455-3
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  • 5
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    Online Resource
    Bioinformatics in Italy: BITS2012, the ninth annual meeting of the Italian Society of Bioinformatics
    Springer Science and Business Media LLC ; 2013
    In:  BMC Bioinformatics Vol. 14, No. S7 ( 2013-04)
    Details
    In: BMC Bioinformatics, Springer Science and Business Media LLC, Vol. 14, No. S7 ( 2013-04)
    Abstract: The BITS2012 meeting, held in Catania on May 2-4, 2012, brought together almost 100 Italian researchers working in the field of Bioinformatics, as well as students in the same or related disciplines. About 90 original research works were presented either as oral communication or as posters, representing a landscape of Italian current research in bioinformatics. This preface provides a brief overview of the meeting and introduces the manuscripts that were accepted for publication in this supplement, after a strict and careful peer-review by an International board of referees.
    Type of Medium: Online Resource
    ISSN: 1471-2105
    URL: Article
    DOI: 10.1186/1471-2105-14-S7-S1
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2013
    detail.hit.zdb_id: 2041484-5
    SSG: 12
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  • 6
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    Involvement of GTA protein NC2β in Neuroblastoma pathogenesis suggests that it physiologically participates in the regulation of cell proliferation
    Springer Science and Business Media LLC ; 2008
    In:  Molecular Cancer Vol. 7, No. 1 ( 2008-12)
    Details
    In: Molecular Cancer, Springer Science and Business Media LLC, Vol. 7, No. 1 ( 2008-12)
    Abstract: The General Transcription Apparatus (GTA) comprises more than one hundred proteins, including RNA Polymerases, GTFs, TAFs, Mediator, and cofactors such as heterodimeric NC2. This complexity contrasts with the simple mechanical role that these proteins are believed to perform and suggests a still uncharacterized participation to important biological functions, such as the control of cell proliferation. Results To verify our hypothesis, we analyzed the involvement in Neuroblastoma (NB) pathogenesis of GTA genes localized at 1p, one of NB critical regions: through RT-PCR of fifty eight NB biopsies, we demonstrated the statistically significant reduction of the mRNA for NC2β (localized at 1p22.1) in 74% of samples (p = 0.0039). Transcripts from TAF13 and TAF12 (mapping at 1p13.3 and 1p35.3, respectively) were also reduced, whereas we didn't detect any quantitative alteration of the mRNAs from GTF2B and NC2α (localized at 1p22-p21 and 11q13.3, respectively). We confirmed these data by comparing tumour and constitutional DNA: most NB samples with diminished levels of NC2β mRNA had also genomic deletions at the corresponding locus. Conclusion Our data show that NC2β is specifically involved in NB pathogenesis and may be considered a new NB biomarker: accordingly, we suggest that NC2β, and possibly other GTA members, are physiologically involved in the control of cell proliferation. Finally, our studies unearth complex selective mechanisms within NB cells.
    Type of Medium: Online Resource
    ISSN: 1476-4598
    URL: Article
    DOI: 10.1186/1476-4598-7-52
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2008
    detail.hit.zdb_id: 2091373-4
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  • 7
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    18F‐Florbetaben PET/CT to Assess Alzheimer's Disease: A new Analysis Method for Regional Amyloid Quantification
    Wiley ; 2019
    In:  Journal of Neuroimaging Vol. 29, No. 3 ( 2019-05), p. 383-393
    Details
    In: Journal of Neuroimaging, Wiley, Vol. 29, No. 3 ( 2019-05), p. 383-393
    Abstract: While AD can be definitively confirmed by postmortem histopathologic examination, in vivo imaging may improve the clinician's ability to identify AD at the earliest stage. The aim of the study was to test the performance of amyloid PET using new processing imaging algorithm for more precise diagnosis of AD. METHODS Amyloid PET results using a new processing imaging algorithm (MRI‐Less and AAL Atlas) were correlated with clinical, cognitive status, CSF analysis, and other imaging. The regional SUVR using the white matter of cerebellum as reference region and scores from clinical and cognitive tests were used to create ROC curves. Leave‐one‐out cross‐validation was carried out to validate the results. RESULTS Forty‐four consecutive patients with clinical evidence of dementia, were retrospectively evaluated. Amyloid PET scan was positive in 26/44 patients with dementia. After integration with 18F‐FDG PET, clinical data and CSF protein levels, 22 of them were classified as AD, the remaining 4 as vascular or frontotemporal dementia. Amyloid and FDG PET, CDR 1, CSF Tau, and p‐tau levels showed the best true positive and true negative rates (amyloid PET: AUC = .85, sensitivity .91, specificity .79). A SUVR value of 1.006 in the inferior frontal cortex and of 1.03 in the precuneus region was the best cutoff SUVR value and showed a good correlation with the diagnosis of AD. Thirteen of 44 amyloid PET positive patients have been enrolled in clinical trials using antiamyloid approaches. CONCLUSIONS Amyloid PET using SPM‐normalized SUVR analysis showed high predictive power for the differential diagnosis of AD.
    Type of Medium: Online Resource
    ISSN: 1051-2284 , 1552-6569
    URL: Issue
    URL: Article
    DOI: 10.1111/jon.2019.29.issue-3
    DOI: 10.1111/jon.12601
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2035400-9
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  • 8
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    Combined Large Cell Neuroendocrine Carcinomas of the Lung: Integrative Molecular Analysis Identifies Subtypes with Potential Therapeutic Implications
    MDPI AG ; 2022
    In:  Cancers Vol. 14, No. 19 ( 2022-09-24), p. 4653-
    Details
    In: Cancers, MDPI AG, Vol. 14, No. 19 ( 2022-09-24), p. 4653-
    Abstract: Background: Combined large cell neuroendocrine carcinoma (CoLCNEC) is given by the association of LCNEC with adeno or squamous or any non-neuroendocrine carcinoma. Molecular bases of CoLCNEC pathogenesis are scant and no standardized therapies are defined. Methods: 44 CoLCNECs: 26 with adenocarcinoma (CoADC), 7 with squamous cell carcinoma (CoSQC), 3 with small cell carcinoma (CoSCLC), 4 with atypical carcinoid (CoAC) and 4 napsin-A positive LCNEC (NapA+), were assessed for alterations in 409 genes and transcriptomic profiling of 20,815 genes. Results: Genes altered included TP53 (n = 30), RB1 (n = 14) and KRAS (n = 13). Targetable alterations included six KRAS G12C mutations and ALK-EML4 fusion gene. Comparison of CoLCNEC transcriptomes with 86 lung cancers of pure histology (8 AC, 19 ADC, 19 LCNEC, 11 SCLC and 29 SQC) identified CoLCNEC as a separate entity of neuroendocrine tumours with three different molecular profiles, two of which showed a non-neuroendocrine lineage. Hypomethylation, activation of MAPK signalling and association to immunotherapy signature specifically characterized each of three CoLCNEC molecular clusters. Prognostic stratification was also provided. Conclusions: CoLCNECs are an independent histologic category. Our findings support the extension of routine evaluation of KRAS mutations, fusion genes and immune-related markers to offer new perspectives in the therapeutic management of CoLCNEC.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers14194653
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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  • 9
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    Long Non-Coding RNAs as Molecular Signatures for Canine B-Cell Lymphoma Characterization
    MDPI AG ; 2019
    In:  Non-Coding RNA Vol. 5, No. 3 ( 2019-09-19), p. 47-
    Details
    In: Non-Coding RNA, MDPI AG, Vol. 5, No. 3 ( 2019-09-19), p. 47-
    Abstract: Background: Diffuse large B-cell lymphoma (DLBCL), marginal zone lymphoma (MZL) and follicular lymphoma (FL) are the most common B-cell lymphomas (BCL) in dogs. Recent investigations have demonstrated overlaps of these histotypes with the human counterparts, including clinical presentation, biologic behavior, tumor genetics, and treatment response. The molecular mechanisms that underlie canine BCL are still unknown and new studies to improve diagnosis, therapy, and the utilization of canine species as spontaneous animal tumor models are undeniably needed. Recent work using human DLBCL transcriptomes has suggested that long non-coding RNAs (lncRNAs) play a key role in lymphoma pathogenesis and pinpointed a restricted number of lncRNAs as potential targets for further studies. Results: To expand the knowledge of non-coding molecules involved in canine BCL, we used transcriptomes obtained from a cohort of 62 dogs with newly-diagnosed multicentric DLBCL, MZL and FL that had undergone complete staging work-up and were treated with chemotherapy or chemo-immunotherapy. We developed a customized R pipeline performing a transcriptome assembly by multiple algorithms to uncover novel lncRNAs, and delineate genome-wide expression of unannotated and annotated lncRNAs. Our pipeline also included a new package for high performance system biology analysis, which detects high-scoring network biological neighborhoods to identify functional modules. Moreover, our customized pipeline quantified the expression of novel and annotated lncRNAs, allowing us to subtype DLBCLs into two main groups. The DLBCL subtypes showed statistically different survivals, indicating the potential use of lncRNAs as prognostic biomarkers in future studies. Conclusions: In this manuscript, we describe the methodology used to identify lncRNAs that differentiate B-cell lymphoma subtypes and we interpreted the biological and clinical values of the results. We inferred the potential functions of lncRNAs to obtain a comprehensive and integrative insight that highlights their impact in this neoplasm.
    Type of Medium: Online Resource
    ISSN: 2311-553X
    URL: Article
    DOI: 10.3390/ncrna5030047
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2813993-8
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  • 10
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    Fast methods for finding significant motifs on labelled multi-relational networks
    Oxford University Press (OUP) ; 2019
    In:  Journal of Complex Networks Vol. 7, No. 6 ( 2019-12-01), p. 817-837
    Details
    In: Journal of Complex Networks, Oxford University Press (OUP), Vol. 7, No. 6 ( 2019-12-01), p. 817-837
    Abstract: A labelled multi-relational network (or labelled multigraph, for short) is one in which nodes have labels and a pair of nodes may be connected by an edge with one or more labels. For example, in an airline route database, ‘large European city’ may be the label on the Paris node and ‘large Asian city’ may be the label on the New Delhi node and the edge between the two cities may be labelled by several carriers. This article presents an analytical method to compute the p-values of labelled subgraph (sub-network) motifs in such labelled multi-relational networks (multigraphs). The method (and a fast approximation to the method) works for both directed and undirected graphs and extends to large subgraphs. We have validated these methods on a dataset of medium size real networks (up to tens of thousands of nodes and hundreds of thousands of edges) of different types (biological, infrastructural and collaboration networks). The pure analytical model is faster than a randomized simulation model by a factor of approximately 1000 in most of our experiments. This improvement in performance is greater for larger graphs. The approximate analytical model avoids the calculations of statistical variance and achieves nearly the same precision and recall as the pure analytical model while being several times faster. To test the scalability of our methods, we run our algorithms on synthetic and real datasets from protein–protein interaction networks, airline flight paths, the internet infrastructural network and the IMDB movie network. We also illustrate a use case of this form of analysis on a large relationship network of people involved in the Panama papers scandal, retrieving frequently used money laundering patterns. labelled multigraphs motif enumeration; motif statistical significance; random network models; multi-relational networks; multigraphs.
    Type of Medium: Online Resource
    ISSN: 2051-1329
    URL: Article
    DOI: 10.1093/comnet/cnz008
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
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