GLORIA

GEOMAR Library Ocean Research Information Access

feed icon rss

Ihre E-Mail wurde erfolgreich gesendet. Bitte prüfen Sie Ihren Maileingang.

Leider ist ein Fehler beim E-Mail-Versand aufgetreten. Bitte versuchen Sie es erneut.

Vorgang fortführen?

Exportieren
  • 1
    Schlagwort(e): Bioinformatics--Congresses. ; Biometry--Congresses. ; Computational intelligence--Congresses. ; Computational Biology--Congresses. ; Artificial Intelligence--Congresses. ; Gene Expression--Congresses. ; Electronic books.
    Materialart: Online-Ressource
    Seiten: 1 online resource (280 pages)
    Ausgabe: 1st ed.
    ISBN: 9783642356865
    Serie: Lecture Notes in Computer Science Series ; v.7548
    DDC: 570.285
    Sprache: Englisch
    Anmerkung: Title -- Preface -- Special Guest Message for the 150th Anniversary of Italian Unification -- Organization -- Table of Contents -- Invited Lectures -- Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling -- Introduction -- Probabilistic Neural Models -- Modelling the Effect of Gene Dynamics on the Spiking Dynamics of a pSNN for a pCNGM -- Conclusion and Further Research -- References -- Biostatistics Meets Bioinformatics in Integrating Information from Highdimensional Heterogeneous Genomic Data: Two Examples from Rare Genetic Diseases and Infectious Diseases -- Introduction -- Statistics and Bioinformatics in Gene Therapy Frameworks -- Statistics and Bioinformatics in High Incidence Infectious Diseases: An Application to Mycobacterium Tubercolosis -- Methods -- sRNA Candidates Definition -- Candidates sRNA Encoding Region -- Final Comments -- References -- Statistical Learning -- Bayesian Models for the Multi-sample Time-Course Microarray Experiments -- Introduction -- Statistical Modeling, Estimation and Classification of Gene Expression Profiles -- The Data Structure -- Modeling the Gene Expression Profiles -- Modeling the Errors -- Estimation of Gene-Dependent Parameters -- Identification and Classification of Genes -- Evaluation of Class Probabilities -- Identification and Classification of Differentially Expressed Genes -- Estimation of Gene Expression Profiles -- Estimation of Global Parameters and Prior Hyperparameters -- Algorithm -- Simulations Results and Discussion -- References -- A Machine Learning Pipeline for Discriminant Pathways Identification -- Introduction -- Methods -- The Pipeline -- Experimental Setup for the Examples -- Data Description -- Results -- Air Pollution Experiment -- Parkinson Disease Experiment -- Conclusions -- References. , Discovering Hidden Pathways in Bioinformatics -- Introduction -- Materials and Methods -- Data -- Existing Methods -- Proposed Method -- Experimental Results -- Discussion and Conclusions -- References -- Genomics -- Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models -- Introduction -- Materials and Methods -- Results -- Experimental Data Description -- Model Estimation -- Validation -- Discussion -- Conclusions -- References -- A Bioinformatics Procedure to Identify and Annotate Somatic Mutations in Whole-Exome Sequencing Data -- Introduction -- Materials and Methods -- Results -- Discussion and Conclusion -- References -- Computational Intelligence for Health at the Edge -- Feature Selection for the Prediction and Visualization of Brain Tumor Types Using Proton Magnetic Resonance Spectroscopy Data -- Introduction -- Literature Review -- Class-Separability Feature Selection -- A Criterion for Class-Separability -- Experimental Work -- Datasets -- Experimental Settings -- Discussion of the Results -- Data Visualization -- Metabolic Interpretation -- The Effect of Redundancy in Class Separability -- Conclusions -- References -- On the Use of Graphical Models to Study ICU Outcome Prediction in Septic Patients Treated with Statins -- Introduction -- Materials -- Methods -- Statistic Algebraic Models -- Models of Conditional Independence -- Bayesian Networks -- Results -- Marginal Dependence between the Pre-admission Use of Statins and the ICU Outcome -- Study of the Protective Effect of Pre-admission Use of Statins with Bayesian Networks -- Conclusions -- References -- Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Biomedical Knowledge Discovery -- Introduction -- Related Work -- Genomic and Proteomic Data Warehouse (GPDW) -- Data Import Procedures of GPDW. , Data Integration Procedures of GPDW -- Generalization of Metadata -- GPDW Data Schema and Queries -- Quality Controls of Integrated Data -- Integrated Biomolecular Interaction Data -- Conceptual and Logical Analysis -- XML Design of Molecular Interaction Data -- Integration Results and Analysis -- Conclusions -- References -- Proteomics -- Machine-Learning Methods to Predict Protein Interaction Sites in Folded Proteins -- Introduction -- Dataset -- Definition of Protein Surface, Interaction Contacts and Patches -- ISPRED2 Implementation -- Measures of Accuracy -- ISPRED2 at Work -- The Effect of the Definition of Interaction Patches -- Comparison with Other Method -- Conclusions -- References -- Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree -- Introduction -- Proteins and Pharmacology -- Materials and Methods -- Kernel Generative Topographic Mapping -- The GPCR Data -- Phylogenetic Trees -- Results and Discussion -- Conclusions -- References -- DEEN: A Simple and Fast Algorithm for Network Community Detection -- Introduction -- The Algorithm -- DEEN: Delete Edges and Expand Nodes -- Delete Edges. -- Expand Nodes. -- Time Complexity. -- Related Work -- Experimental Evaluation -- Benchmark Networks -- The Karate Club Network. -- The US College Football Network. -- Protein Complex Detection in the Budding Yeast PPI Network -- Assignment of Annotation and p-values to Clusters. -- Results. -- Comparison with MCL. -- Conclusion -- References -- Intelligent Clinical Decision Support Systems(i-CDSS) -- Self-similarity in Physiological Time Series:New Perspectives from the Temporal Spectrum of Scale Exponents -- Introduction -- DFA and the Temporal Spectrum of Scale Exponents -- DFA Temporal Spectrum of Physiological Time Series -- Temporal Spectrum of EEG -- Temporal Spectrum of Cardiovascular Signals. , Discussion and Conclusions -- References -- Support Vector Machines for Survival Regression -- Introduction -- Survival Analysis as Quantile Regression -- Loss Function -- Censored Loss Function -- Theoretical Analysis -- Bounds on the Quantile Risk -- Bounds on the Quantile Property -- Optimisation of the Risk Functional -- Dual Optimisation -- Monotonicity Constraints -- Experiments -- Simulated Data -- German Breast Cancer Study Group 2 -- Conclusions -- References -- Boosted C5 Trees i-Biomarkers Panel for Invasive Bladder Cancer Progression Prediction -- Introduction -- Methods -- Data Preprocessing -- i-Biomarker Development Using C5 Decision Trees -- Results and Discussions -- Samples Data -- i-Biomarkers Development -- Panel of i-Biomarkers Using the KDD Set: -- Single i-Biomarker Using the KM Set: -- Conclusion -- References -- Bioinformatics -- A Faster Algorithm for Motif Finding in Sequences from ChIP-Seq Data -- Introduction -- The Problem -- The Algorithm -- Experimental Evaluation -- Conclusions -- References -- Case/Control Prediction from Illumina Methylation Microarray's β and Two-Color Channels in the Presence of Batch Effects -- Introduction -- Methods -- Results -- Discussion -- Conclusion -- References -- Supporting the Design, Communication and Management of Bioinformatic Protocols through the Leaf Tool -- Introduction -- Formalizing Bioinformatic Protocols -- Resources and Processors -- Protocols as Annnotated Directed Graphs -- The ``Leaf'' System -- The Leaf Graph Language -- The Leaf Protocol Engine -- A Real Application Example -- Conclusions -- References -- Data Clustering -- Genomic Annotation Prediction Based on Integrated Information -- Introduction. -- Data Warehousing and Information Integration -- Genomic and Proteomic Data Warehouse -- Information and Data Integration Approach -- Computational Methods. , Prediction of Biomolecular Annotations -- SVD - Singular Value Decomposition -- SIM - Semantic IMprovement -- Results -- Software Infrastructure and Performances -- ACML and SVDLIBC -- Performances -- Conclusions -- References -- Solving Biclustering with a GRASP-Like Metaheuristic: Two Case-Studies on Gene Expression Analysis -- Introduction -- Problem Formulation -- GRASP -- A Reactive GRASP-Like Algorithm for Biclustering -- Experimental Results and Biological Significance -- References -- Author Index.
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    ISSN: 1573-7276
    Schlagwort(e): adjuvant therapy ; angiogenesis ; metastasis ; tamoxifen
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Medizin
    Notizen: Abstract Some experimental studies suggested that one possible oestrogen-receptor-unrelated mechanism of action of tamoxifen involves inhibition of angiogenesis. We evaluated the correlation of the degree of vascularisation of the primary tumour and we assessed it by using the panendothelial marker anti- CD31 and immunohistochemistry with microvessels count, performed at the vascular ‘hot spot’ of each single cancer, with the risk of recurrence in time. A cohort of 176 consecutive patients with node-positive invasive breast cancer treated with adjuvant tamoxifen (30 mg/daily for 3 years) and a median follow-up of 72 months was studied. Sixty-two patients developed metastasis (30 visceral, 18 skeletal and 14 in soft tissues) during the time of observation. The study of the hazard function for metastasis was performed by a generalized linear modelling approach with a binomial error according to Efron. The risk of first recurrence was strictly associated with vascular index, having the patients with the highest microvessel counts the highest risk of metastasis during all the period of observation. We did not find an interaction of vascularity with oestrogen receptor (ER) status. However, in the subgroup of patients with ER-positive tumours the hazard of metastasis was almost constant in time, while in that with ER-negative tumours it increased rapidly up to 20 months and, thereafter, decreased sharply. The results of our study are an indirect evidence that the patients with highly vascularized breast cancers may gain poor benefit of adjuvant tamoxifen and, therefore, that this antioestrogen is unlikely to retain a clinically relevant antiangiogenic activity in human breast cancer. Our data need confirmation by a prospective randomized clinical trial.
    Materialart: Digitale Medien
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 3
    ISSN: 1573-7217
    Schlagwort(e): apoptosis ; breast cancer ; continuous variables statistical analysis ; cytokeratins ; multiple correspondence analysis ; prognosis ; tissue cytosol ; tissue polypeptide antigen (TPA)
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Medizin
    Notizen: Abstract Apoptosis is associated with caspase-mediated proteolysis of Type I (K18 and K19) cytokeratins. We previously showed a positive association between the levels of tissue polypeptide antigen (TPA), that recognizes cytokeratins K8, K18, and K19 fragments, and induced apoptosis in breast cancer cell lines. The aim of the present study was to evaluate the interrelationships between TPA, steroid receptors, and p53, and their joint prognostic role in node-negative breast cancer patients not treated with adjuvant therapies. Age and pT were also considered since they are known prognostic factors. Five hundred and ninety-nine cases with N- breast cancer were evaluated (median follow-up: 60 months). TPA was measured by an immunoradiometric assay and p53 by an immuno-chemiluminescent assay in tumor cytosol. Multiple correspondence analysis was used to study the associations among variables. Their prognostic role (univariate analysis) and their joint effect (multivariate analysis) on RFS were investigated with Cox regression models. TPA showed a direct association with ER and PgR. Higher p53 values were weakly associated to low values of ER, PgR, and TPA. Younger age was related to low and intermediate values of ER and PgR and to low p53 values, while older age was related to high values of ER. Multivariate analysis showed a significant prognostic impact for pT, age, ER, and TPA. Among the interactions considered clinically relevant, only that between ER and age was found. RFS estimated values were poorer in cases with lower than in those with higher TPA values, both in patients expected to have a poor (pT2, young age, low ER) and a better prognosis (pT1, older age, high ER). From the findings of the present study we can draw the following conclusions: The relationship of TPA with prognosis gives an additional contribution to pT, age, and steroid receptors in N- breast cancer; TPA may be considered the first marker of apoptosis measured with a fully standardized quantitative method in tumor cytosol and could be evaluated in prognostic indexes including markers related to different biological mechanisms.
    Materialart: Digitale Medien
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 4
    ISSN: 1573-7209
    Schlagwort(e): Angiogenesis ; breast cancer ; prognosis
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Medizin
    Notizen: Abstract Experimental and clinical studies have shown that human breast cancer is an angiogenesis-dependent neoplasm. In fact, several authors have demonstrated that the determination in primary tumors of the degree of vascularization (microvessel counts) as well as of some angiogenic peptides is of prognostic value. However, which are the most important mediators of angiogenesis and their relationship with other relevant biological markers needs further investigation. In the series of 260 women with node-negative breast cancer (NNBC) on which we previously assessed vascular endothelial growth factor (VEGF), we have now also determined thymidine phosphorylase (TP) protein as well as p53 protein and Cathepsin-D cytosolic levels using immunometric methods. The median concentrations of TP, p53 and Cathepsin-D were 105.4U/mg (range 1.2–843.1), 0.22 ng/mg (range 0.0–41.65) and 33.80nmol/mg (range 4.20–216.0), respectively. We found that TP concentrations were associated with Cathepsin-D and p53, but not with VEGF. VEGF (p〈0.0001) and p53 (p = 0.03 and p = 0.012, respectively) were found to be statistically significant prognostic variables for both relapse-free survival (RFS) and overall survival in univariate analysis. Conversely, TP and Cathepsin-D levels did not correlate with prognosis. In multivariate analysis for RFS, VEGF levels (p〈0.0001), TP levels (p = 0.050) and their first-order interaction terms (p = 0.027) were statistically significant prognostic indicators. Cathepsin-D and p53 protein levels did not retain significance in the model inclusive of all the above variables. The predictive capability of the complete model was satisfactory (Harrell c statistic = 0.72). Moreover, these results suggest a possible potentiation of the capability of predicting the likelihood of recurrence by the co-determination of TP and VEGF. The probability of recurrence was particularly high in the patients with primary tumors characterized by elevated levels of both angiogenic factors. This is the first study showing in vivo that two different angiogenic peptides concur in the progression of human breast cancer. The biology and possible therapeutic implications of this observation are discussed.
    Materialart: Digitale Medien
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
Schließen ⊗
Diese Webseite nutzt Cookies und das Analyse-Tool Matomo. Weitere Informationen finden Sie hier...