Claudia Angelini List of Talks

Talks in Meetings or Conferences

  1. 1. C. Angelini, D. De Canditiis, I. De Feis, A. Iuliano AFTNet: a novel network-penalized Weibull AFT regression algorithm and its applications to cancer survival, SIS meeting 2024, Bari, 20/06/2024.
  2. 2. C. Angelini High dimensional data integration using graphical models”, Calcolo Scientifico e Modelli Matematici: Roma 8/04/2022
  3. 3. C. Angelini, On penalized network regression approaches with applications to omics data analysis in cancer studies. . NETWORKING INTERNATIONAL BIOMETRIC SOCIETY REGIONS, SIB 2019, Napoli, 08/07/2019
  4. 4. C. Angelini, An overview on penalized network regression approaches (and applications to genomics). . Workshop Woman in Networks (COST Action CA15109 -COSTNET ), Leeds UK, 28/02/2019
  5. 5. C. Angelini, The importance of being reproducible:.Challenges and Solutions for the analysis of NGS data. Workshop “The importance of being reproducible: a statistical prospective, CUSSB, Università Salute-Vita San Raffaele, Milano, 27/01/2017
  6. 6. C. Angelini, Algorithms, Methods and Computational Tools in Bioinformatics with applications, Conferenza DIITET-CNR, Roma, 23/11/2016.
  7. 7. C. Angelini, An introduction to next generation sequencing for studying omic-environment interactions, SIS meeting 2016, Salerno, 6/06/2016.
  8. 8. C. Angelini, Statistical Issues in the Analysis of ChIP-Seq and RNA-Seq Data and their integration, Annual Epigen Project meeting 2016, Rome, 26/05/2016.
  9. 9. F. Russo, D. Righelli, C. Angelini, The importance of being reproducible: tools and examples using R,XXII Congresso da Sociedade Portuguesa de Estatístic, Ria Formosa.October  7 – 10, 2015.
  10. 10. C. Angelini, Statistical Issues in the Analysis of ChIP-Seq and RNA-Seq Data: novel advancement, Annual Epigen Project meeting 2015, Rome, 23/04/2015.
  11. 11. C. Angelini, D. Righelli, F. Russo Reproducible Research in the era of Next Generation Sequencing: current approaches, examples and future perspectives, Next Generation Sequencing: a look into the future, 16-17 March 2015, Bratislava, Slovakia.
  12. 12. C. Angelini, Models, algorithms and tools for Bioinformatics, Synthetic and System Biology, “Nanotechnologies, Biotechnologies and ICT for Health-care and well-being”, Pisa, 5 Marzo 2015
  13. 13. C Angelini, Developing Computational tools for NGS data analysis in the spirit of Reproducible Research, Translating emerging seq-based technologies into integrated biomedical approaches, Naples, 24/06/2014.
  14. 14. C. Angelini, F. Russo Analyzing RNA-seq data with RNAseqGUI, NGS Data after the Gold Rush, Norwich, UK, 7/05/2014.
  15. 15. C. Angelini, Statistical Issues in the Analysis of ChIP-Seq and RNA-Seq Data,, Annual Epigen Project meeting 2014, Rome, 20/02/2014.
  16. 16. C. Angelini, Data integration and advanced data analysis: the example of ALE-HSA21, Annual InterOmics meeting 2013, Rome, 3/06/2013.
  17. 17. C. Angelini, Computational approaches for Isoforms' detection and estimation: Good and Bad news, Annual Epigen Project meeting 2013, Rome, 15/04/2013.
  18. 18. C. Angelini, Statistical challenges in NGS data analysis, German-Italian Dialogue 2012, Ercolano (NA), 17/07/2012.
  19. 19. C. Angelini, D. De Canditiis, M. Pensky, N. Brownstein, Bayesian models for the analysis of multi-sample time-course microarray experiments, Eight International meeting on Computational Intelligence methods for Bioinformatics and Biostatistics—CIBB 2011, Gargnano – Lago di Garda, 30/06/2011.
  20. 20. C. Angelini, Computational methods for RNA-Seq data analysis, Workshop on NGS (Solid) Data Analysis, organized by IGB-CNR, CNR Area di Ricerca di Napoli, 27/10/2010.
  21. 21. C. Angelini, An overview on time course microarray analysis: from genes detection to clustering, Second Workshop on Bioinformatica, Biostatistica e Machine Learning, Dipartimento di Matematica ed Informatica, Università degli Studi di Salerno, 6/10/2009.
  22. 22. C. Angelini, D. De Canditiis, M. Pensky, Bayesian methods for time course microarray analysis: from genes' detection to clustering, Invited Talk at the Special Session Statistical analysis of high-dimensional gene expression time series, organized by the Royal Statistical Society, within the European Conference on Statistical Methods for Large Data Sets, Pescara (Italy), 23- 25/09/2009.
  23. 23. C. Angelini, Statistical challenges in the analysis of gene-expression profiles, Invited Talk at the Workshop Approcci computazionali alla comprensione dei fenomeni biologici, organized by IGB-CNR and Tigem, CNR, Area di Ricerca di Napoli,11/09/2009.
  24. 24. C. Angelini, L. Cutillo, D. De Canditiis, M. Mutarelli, M. Pensky. BATS: A Bayesian user-friendly Software for analyzing time series microarray experiments. BioInfoGRID Symposium 2007, Milan 10-13/12/2007.
  25. 25. C. Angelini, L. Cutillo, D. De Canditiis, M. Mutarelli, M. Pensky. BATS: A user-friendly Software for analyzing time series microarray experiments. BITS 2007, Naples, 26-28/04/2007.
  26. 26. C. Angelini, Un approccio Bayesiano per l'analisi di esperimenti di time-course con microarrays, Bioinformatica e Biologia computazionale in Campania, 18/12/2006, ISA-CNR, Avellino.
  27. 27. C. Angelini, Bayesian Wavelet Estimators: what about Global and Pointwise Minimax Convergence? In Estimations Are Approximations: Multiresolution Modeling and Statistical Inference, The Radcliffe Institute for Advanced Study at Harvard University, USA, 27-29/10/2005.
  28. 28. C. Angelini, On Bayesian wavelet estimators: Global and Pointwise Convergence. Mini-Workshop on (Bayesian) Statistical Modeling in Wavelet Domain, Milan 17/12/2004.
  29. 29. F. Abramovich, C. Angelini, Bayesian MAP multiple thresholding procedures. The 3rd winter workshop on Statistics & Computer Science -Scientific Application of Bayesian Analysis. 5-8/12/2004, Ein Gedi (Israel).
  30. 30. F. Abramovich, U. Amato, C. Angelini. On optimality of Bayesian wavelet estimators. Wavelet and Statistics 4-7/09/2003, Villard de Lans, Grenoble France.
  31. 31. C. Angelini, T. Sapatinas. Empirical Bayes Approach to wavelet Regression using ε-contaminated priors. NPCONF2002, 15-19/07/2002 - Crete, Greece.
  32. 32. C. Angelini, D. De Canditiis, F. Leblanc. Wavelet regression estimation in nonparametric mixed effect models. ICCAM 2000, Leuven (Belgio), 17-21/07/2000.
  33. 33. C. Angelini, D. De Canditiis, F. Leblanc. Wavelet approximation of functions from samples affected by noise. Minisymposium on Approximation of Curves and Surfaces, Florence 8-9/06/2000.
  34. 34. C. Angelini, Tre approcci basati sulle wavelets per il problema dello smoothing di dati. XVI congresso UMI, Napoli 13-18/09/1999.
  35. 35. U. Amato, C. Angelini, D. De Canditiis, I. De Feis. Fourier frequency adaptive regularization for smoothing data. ICCAM 1998, Leuven, Belgio.

Seminars

  1. 1. C. Angelini Modelli predittivi attuali e futuri applicati alla genomica, LazioInnova networking per le imprese, Roma 19 Aprile 2024.
  2. 2. C. Angelini, On some statistical methods for omics data analysis. Seminari generali IAC, 13/04/2022
  3. 3. C. Angelini, “Analysis and Integration of Omics Data with Applications to Biomedical Research”, online meeting CNR Immunology Network, 16/11/2020
  4. 4. C. Angelini La matematica del genoma. Seminario Webinar Mathematical Methods in Data Science, 13/07/2020
  5. 5. C. Angelini, A walking tour on penalized network regression approaches with applications to omics data analysis. Masaryk University, Brno, Czech Republic, 14/03/2019
  6. 6. C. Angelini High dimensional statistical data analysis an overview from general concepts to an application to breast cancer survival prediction Gran Sasso Science Institute, 20/06/2018.
  7. 7. C. Angelini. Analyzing the Whole Transcriptome by RNA-Seq data: Statistical and Computational Challenges. Centre for Systems Engineering and Applied Mechanics (CESAME) Louvain-la-Neuve, 1/03/2011.
  8. 8. C. Angelini. Computational methods for the analysis of RNA-Seq experiments, nell' ambito de I Martedì della Bioinformatica, Università degli Studi di Salerno, 07/12/2010.
  9. 9. C. Angelini, On the Analysis of Time Course Microarray Experiments, in Tutorial di Metodi e Strumenti per l'Analisi dei Dati di Espressione Genica, Area della Ricerca CNR Napoli, 18/12/2007.
  10. 10. C. Angelini, BATS: modelli Bayesiani e software per l'analisi statistica di esperimenti di time-course con microarray, nell'ambito de I Martedì della Bioinformatica, Università degli Studi di Salerno, 06/11/2007.
  11. 11. C. Angelini, Bayesian approach to estimation and testing in time course microarray experiments, Department of Mathematics University of Central Florida, Orlando, 17/11/2006.
  12. 12. C. Angelini, Bayesian Maximum A Posteriori multiple testing procedures with applications to microarray data analysis Department of Mathematics University of Central Florida, Orlando 11/2005.
  13. 13. C. Angelini Wavelets: Cosa, Come e Perche'?, Università della Calabria-Arcavacata di Rende- il 22/09/2003.
  14. 14. C. Angelini, Fourier frequency adaptive regularization for smoothing data, LMC - University J. Fourier, Grenoble, France, 22/10/1998.

Special Lessons

  1. 1. C. Angelini, Introduzione al clustering Lezione per la Summer School in Mathematical Methods in Data Science, MMDS2021.
  2. 2. C. Angelini, Approfondimenti sulla Regressione Lineare. Lezione per la Summer School in Mathematical Methods in Data Science, MMDS2019. Bari, 18 Luglio 2019.
  3. 3. C. Angelini, Regressione Lineare ed Applicazioni mediante R. Lezione per la Summer School in Mathematical Methods in Data Science, MMDS2019. Bari, 18 Luglio 2019.
  4. 4. C. Angelini, Clustering per Applicazioni Biomediche. Lezione per la Summer School in Mathematical Methods in Data Science, MMDS2019. Bari, 17 Luglio 2019.
  5. 5. C. Angelini, Analisi Bayesiana per Applicazioni Biomediche. Lezione per la Summer School in Mathematical Methods in Data Science, MMDS2018. Bari, 18 Luglio 2018.
  6. 6. C. Angelini, Clustering per Applicazioni Biomediche. Lezione per la Summer School in Mathematical Methods in Data Science, MMDS2018. Bari, 17 Luglio 2018.
  7. 7. C. Angelini, Metodi statistici per la classificazione di campioni. Lezione al corso di aggiornamento Bioinformatica di base per la Proteomica. Genova, IST 24-27 Novembre 2015.
  8. 8. C.Angelini, Chip-seq: methods and applications in epigenomic studies (review + practical). EMBO course in Bioinformatics and Comparative Genome Analysis. Napoli, Stazione Zoologica, 15/5/2012.
  9. 9. C. Angelini, Metodi statistici per analisi di dati NGS. Corso di Gestione e Analisi di Dati di Next Generation Sequencing nell'Ambito della Ricerca Clinica. Pavia, Collegio Ghislieri, 9/5/2012.
  10. 10. C. Angelini, Metodi di analisi statistica di dati di Next Generation Sequencing. 11 Corso di formazione avanzata in Medicina genomica e terapia personalizzata in ematologia/oncologia. Pavia, Collegio Ghislieri, 17/4/2012.
  11. 11. C. Angelini, Metodi basati sulle wavelets per l'analisi di dati di spettrometria di massa. Lezione al corso di aggiornamento Bioinformatica per la Proteomica: basi teoriche ed applicazioni. Genova, IST 18-20 Ottobre 2010.
  12. 12. C. Angelini, Metodi basati sulle wavelets per il pre-processing di dati di spettrometria di massa. Lezione al corso di aggiornamento Bioinformatica per la Proteomica: basi teoriche ed applicazioni. Avellino, ISA-CNR, 10-13 November 2009.