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  1. Book: Understanding drug release and absorption mechanisms

    Grassi, Mario

    a physical and mathematical approach

    2007  

    Author's details Mario Grassi
    Keywords Pharmacokinetics ; Pharmaceutical Preparations / metabolism ; Models, Theoretical ; Pharmacokinetics/Mathematical models ; Drugs/Solubility/Mathematical models ; Drugs/Absorption and adsorption/Mathematical models ; Drugs/Controlled release/Mathematical models
    Subject code 615.7
    Language English
    Size 627 S. : Ill., graph. Darst., 24cm
    Publisher CRC Press Taylor & Francis
    Publishing place Boca Raton, Fla
    Publishing country United States
    Document type Book
    Note Includes bibliographical references and index
    Accompanying material 1 CD-ROM (12 cm)
    HBZ-ID HT014975415
    ISBN 0-8493-3087-4 ; 978-0-8493-3087-2
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2007 A 1938 order for loan Magazin
    2007 MO 172 <<[Begleitmaterial]>> order for loan Magazin

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  2. Article ; Online: SEMtree: tree-based structure learning methods with structural equation models.

    Grassi, Mario / Tarantino, Barbara

    Bioinformatics (Oxford, England)

    2023  Volume 39, Issue 6

    Abstract: Motivation: With the exponential growth of expression and protein-protein interaction (PPI) data, the identification of functional modules in PPI networks that show striking changes in molecular activity or phenotypic signatures becomes of particular ... ...

    Abstract Motivation: With the exponential growth of expression and protein-protein interaction (PPI) data, the identification of functional modules in PPI networks that show striking changes in molecular activity or phenotypic signatures becomes of particular interest to reveal process-specific information that is correlated with cellular or disease states. This requires both the identification of network nodes with reliability scores and the availability of an efficient technique to locate the network regions with the highest scores. In the literature, a number of heuristic methods have been suggested. We propose SEMtree(), a set of tree-based structure discovery algorithms, combining graph and statistically interpretable parameters together with a user-friendly R package based on structural equation models framework.
    Results: Condition-specific changes from differential expression and gene-gene co-expression are recovered with statistical testing of node, directed edge, and directed path difference between groups. In the end, from a list of seed (i.e. disease) genes or gene P-values, the perturbed modules with undirected edges are generated with five state-of-the-art active subnetwork detection methods. The latter are supplied to causal additive trees based on Chu-Liu-Edmonds' algorithm (Chow and Liu, Approximating discrete probability distributions with dependence trees. IEEE Trans Inform Theory 1968;14:462-7) in SEMtree() to be converted in directed trees. This conversion allows to compare the methods in terms of directed active subnetworks. We applied SEMtree() to both Coronavirus disease (COVID-19) RNA-seq dataset (GEO accession: GSE172114) and simulated datasets with various differential expression patterns. Compared to existing methods, SEMtree() is able to capture biologically relevant subnetworks with simple visualization of directed paths, good perturbation extraction, and classifier performance.
    Availability and implementation: SEMtree() function is implemented in the R package SEMgraph, easily available at https://CRAN.R-project.org/package=SEMgraph.
    MeSH term(s) Humans ; Gene Regulatory Networks ; Reproducibility of Results ; COVID-19 ; Algorithms ; Protein Interaction Maps
    Language English
    Publishing date 2023-06-09
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btad377
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: SEMgsa: topology-based pathway enrichment analysis with structural equation models.

    Grassi, Mario / Tarantino, Barbara

    BMC bioinformatics

    2022  Volume 23, Issue 1, Page(s) 344

    Abstract: Background: Pathway enrichment analysis is extensively used in high-throughput experimental studies to gain insight into the functional roles of pre-defined subsets of genes, proteins and metabolites. Methods that leverages information on the topology ... ...

    Abstract Background: Pathway enrichment analysis is extensively used in high-throughput experimental studies to gain insight into the functional roles of pre-defined subsets of genes, proteins and metabolites. Methods that leverages information on the topology of the underlying pathways outperform simpler methods that only consider pathway membership, leading to improved performance. Among all the proposed software tools, there's the need to combine high statistical power together with a user-friendly framework, making it difficult to choose the best method for a particular experimental environment.
    Results: We propose SEMgsa, a topology-based algorithm developed into the framework of structural equation models. SEMgsa combine the SEM p values regarding node-specific group effect estimates in terms of activation or inhibition, after statistically controlling biological relations among genes within pathways. We used SEMgsa to identify biologically relevant results in a Coronavirus disease (COVID-19) RNA-seq dataset (GEO accession: GSE172114) together with a frontotemporal dementia (FTD) DNA methylation dataset (GEO accession: GSE53740) and compared its performance with some existing methods. SEMgsa is highly sensitive to the pathways designed for the specific disease, showing low p values ([Formula: see text]) and ranking in high positions, outperforming existing software tools. Three pathway dysregulation mechanisms were used to generate simulated expression data and evaluate the performance of methods in terms of type I error followed by their statistical power. Simulation results confirm best overall performance of SEMgsa.
    Conclusions: SEMgsa is a novel yet powerful method for identifying enrichment with regard to gene expression data. It takes into account topological information and exploits pathway perturbation statistics to reveal biological information. SEMgsa is implemented in the R package SEMgraph, easily available at https://CRAN.R-project.org/package=SEMgraph .
    MeSH term(s) Algorithms ; COVID-19 ; Computer Simulation ; DNA Methylation ; Humans ; Software
    Language English
    Publishing date 2022-08-17
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-022-04884-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Ionic Strength Impacts the Physical Properties of Agarose Hydrogels.

    Sacco, Pasquale / Piazza, Francesco / Marsich, Eleonora / Abrami, Michela / Grassi, Mario / Donati, Ivan

    Gels (Basel, Switzerland)

    2024  Volume 10, Issue 2

    Abstract: Agarose is a natural polysaccharide known for its ability to form thermoreversible hydrogels. While the effects of curing temperature and polysaccharide concentration on mechanical properties have been discussed in the literature, the role of ionic ... ...

    Abstract Agarose is a natural polysaccharide known for its ability to form thermoreversible hydrogels. While the effects of curing temperature and polysaccharide concentration on mechanical properties have been discussed in the literature, the role of ionic strength has been less studied. In the present manuscript, we investigate the effects of supporting salt concentration and the role of cation (i.e. Na
    Language English
    Publishing date 2024-01-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2813982-3
    ISSN 2310-2861 ; 2310-2861
    ISSN (online) 2310-2861
    ISSN 2310-2861
    DOI 10.3390/gels10020094
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: SEMgraph: an R package for causal network inference of high-throughput data with structural equation models.

    Grassi, Mario / Palluzzi, Fernando / Tarantino, Barbara

    Bioinformatics (Oxford, England)

    2022  Volume 38, Issue 20, Page(s) 4829–4830

    Abstract: Motivation: With the advent of high-throughput sequencing in molecular biology and medicine, the need for scalable statistical solutions for modeling complex biological systems has become of critical importance. The increasing number of platforms and ... ...

    Abstract Motivation: With the advent of high-throughput sequencing in molecular biology and medicine, the need for scalable statistical solutions for modeling complex biological systems has become of critical importance. The increasing number of platforms and possible experimental scenarios raised the problem of integrating large amounts of new heterogeneous data and current knowledge, to test novel hypotheses and improve our comprehension of physiological processes and diseases.
    Results: Combining network analysis and causal inference within the framework of structural equation modeling (SEM), we developed the R package SEMgraph. It provides a fully automated toolkit, managing complex biological systems as multivariate networks, ensuring robustness and reproducibility through data-driven evaluation of model architecture and perturbation, which is readily interpretable in terms of causal effects among system components.
    Availability and implementation: SEMgraph package is available at https://cran.r-project.org/web/packages/SEMgraph.
    Supplementary information: Supplementary data are available at Bioinformatics online.
    MeSH term(s) Causality ; High-Throughput Nucleotide Sequencing ; Models, Theoretical ; Reproducibility of Results ; Software
    Language English
    Publishing date 2022-09-20
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btac567
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2374: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: Drug Repurposing in Human Cancers.

    Grassi, Gabriele / Grassi, Mario

    Current medicinal chemistry

    2020  Volume 27, Issue 42, Page(s) 7213

    MeSH term(s) Drug Repositioning ; Humans ; Neoplasms/drug therapy
    Language English
    Publishing date 2020-12-17
    Publishing country United Arab Emirates
    Document type Editorial
    ZDB-ID 1319315-6
    ISSN 1875-533X ; 0929-8673
    ISSN (online) 1875-533X
    ISSN 0929-8673
    DOI 10.2174/092986732742201105104417
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4432: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article ; Online: Physical and chemical properties of carbon nanotubes in view of mechanistic neuroscience investigations. Some outlook from condensed matter, materials science and physical chemistry.

    Mezzasalma, Stefano A / Grassi, Lucia / Grassi, Mario

    Materials science & engineering. C, Materials for biological applications

    2021  Volume 131, Page(s) 112480

    Abstract: The open border between non-living and living matter, suggested by increasingly emerging fields of nanoscience interfaced to biological systems, requires a detailed knowledge of nanomaterials properties. An account of the wide spectrum of phenomena, ... ...

    Abstract The open border between non-living and living matter, suggested by increasingly emerging fields of nanoscience interfaced to biological systems, requires a detailed knowledge of nanomaterials properties. An account of the wide spectrum of phenomena, belonging to physical chemistry of interfaces, materials science, solid state physics at the nanoscale and bioelectrochemistry, thus is acquainted for a comprehensive application of carbon nanotubes interphased with neuron cells. This review points out a number of conceptual tools to further address the ongoing advances in coupling neuronal networks with (carbon) nanotube meshworks, and to deepen the basic issues that govern a biological cell or tissue interacting with a nanomaterial. Emphasis is given here to the properties and roles of carbon nanotube systems at relevant spatiotemporal scales of individual molecules, junctions and molecular layers, as well as to the point of view of a condensed matter or materials scientist. Carbon nanotube interactions with blood-brain barrier, drug delivery, biocompatibility and functionalization issues are also regarded.
    MeSH term(s) Chemistry, Physical ; Materials Science ; Nanostructures ; Nanotubes, Carbon ; Neurons
    Chemical Substances Nanotubes, Carbon
    Language English
    Publishing date 2021-10-14
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 2012160-X
    ISSN 1873-0191 ; 0928-4931
    ISSN (online) 1873-0191
    ISSN 0928-4931
    DOI 10.1016/j.msec.2021.112480
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Online: SEMgraph

    Palluzzi, Fernando / Grassi, Mario

    An R Package for Causal Network Analysis of High-Throughput Data with Structural Equation Models

    2021  

    Abstract: With the advent of high-throughput sequencing (HTS) in molecular biology and medicine, the need for scalable statistical solutions for modeling complex biological systems has become of critical importance. The increasing number of platforms and possible ... ...

    Abstract With the advent of high-throughput sequencing (HTS) in molecular biology and medicine, the need for scalable statistical solutions for modeling complex biological systems has become of critical importance. The increasing number of platforms and possible experimental scenarios raised the problem of integrating large amounts of new heterogeneous data and current knowledge, to test novel hypotheses and improve our comprehension of physiological processes and diseases. Although network theory provided a framework to represent biological systems and study their hidden properties, different algorithms still offer low reproducibility and robustness, dependence on user-defined setup, and poor interpretability. Here we discuss the R package SEMgraph, combining network analysis and causal inference within the framework of structural equation modeling (SEM). It provides a fully automated toolkit, managing complex biological systems as multivariate networks, ensuring robustness and reproducibility through data-driven evaluation of model architecture and perturbation, that is readily interpretable in terms of causal effects among system components. In addition, SEMgraph offers several functions for perturbed path finding, model reduction, and parallelization options for the analysis of large interaction networks.

    Comment: 29 pages; 5 figures; original article; R package; CRAN stable version at: https://CRAN.R-project.org/package=SEMgraph; Development version available at https://github.com/fernandoPalluzzi/SEMgraph
    Keywords Quantitative Biology - Molecular Networks ; Statistics - Applications
    Subject code 006
    Publishing date 2021-03-15
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  9. Article: Polysaccharide-based hydrogels crosslink density equation: A rheological and LF-NMR study of polymer-polymer interactions

    Kopač, Tilen / Abrami, Michela / Grassi, Mario / Ručigaj, Aleš / Krajnc, Matjaž

    Carbohydrate polymers. 2022 Feb. 01, v. 277

    2022  

    Abstract: A simple relation between pendant groups of polymers in hydrogels is introduced to determine the crosslink density of (complex) hydrogel systems (mixtures of 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) modified nanocellulose, alginate, scleroglucan and ... ...

    Abstract A simple relation between pendant groups of polymers in hydrogels is introduced to determine the crosslink density of (complex) hydrogel systems (mixtures of 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) modified nanocellulose, alginate, scleroglucan and Laponite in addition of crosslinking agents). Furthermore, the rheological properties and their great potential connection to design complex hydrogel systems with desired properties have been thoroughly investigated. Hydrogel structures governing internal friction and flow resistance were described by the predominant effect of ionic, hydrogen, and electrostatic interactions. The relationship between rheological properties and polymer-polymer interactions in the hydrogel network is explained and expressed in a new mathematical model for determining the crosslink density of (crosslinked) hydrogels based on single or mixture of polymer systems. In the end, the combined used of rheology and low field nuclear magnetic resonance spectroscopy (LF-NMR) for the characterization of hydrogel networks is developed.
    Keywords alginates ; cellulose ; crosslinking ; equations ; flow resistance ; friction ; hydrogels ; hydrogen ; laponite ; mathematical models ; nuclear magnetic resonance spectroscopy ; polymers ; rheology ; scleroglucan
    Language English
    Dates of publication 2022-0201
    Publishing place Elsevier Ltd
    Document type Article
    ZDB-ID 1501516-6
    ISSN 1879-1344 ; 0144-8617
    ISSN (online) 1879-1344
    ISSN 0144-8617
    DOI 10.1016/j.carbpol.2021.118895
    Database NAL-Catalogue (AGRICOLA)

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  10. Article ; Online: Hydrophobically-Modified PEG Hydrogels with Controllable Hydrophilic/Hydrophobic Balance.

    Bignotti, Fabio / Baldi, Francesco / Grassi, Mario / Abrami, Michela / Spagnoli, Gloria

    Polymers

    2021  Volume 13, Issue 9

    Abstract: This work reports on a novel method to synthesize hydrophobically-modified hydrogels by curing epoxy monomers with amines. The resulting networks contain hydrophilic poly(ethylene glycol) (PEG) segments, poly(propylene glycol) (PPG) segments, and ... ...

    Abstract This work reports on a novel method to synthesize hydrophobically-modified hydrogels by curing epoxy monomers with amines. The resulting networks contain hydrophilic poly(ethylene glycol) (PEG) segments, poly(propylene glycol) (PPG) segments, and C
    Language English
    Publishing date 2021-05-06
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527146-5
    ISSN 2073-4360 ; 2073-4360
    ISSN (online) 2073-4360
    ISSN 2073-4360
    DOI 10.3390/polym13091489
    Database MEDical Literature Analysis and Retrieval System OnLINE

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