1. 1) A. Carissimo, L. Cutillo, I. De Feis. Validation of community robustness. Computational Statistics and Data Analysis, 120, 1-24, (2018)
  2. 2) S. Gatto, M. Gagliardi, M. Franzese, S. Leppert, M. Papa, M. Cammisa, G. Grillo, G. Velasco, C. Francastel, S. Toubiana, M. D'Esposito, C. Angelini, M. R Matarazzo. ICF-specific DNMT3B dysfunction interferes with intragenic regulation of mRNA transcription and alternative splicing . Nucleic Acid Research (2017)
  3. 3) V. Costa, D. Righelli, F. Russo, P. De Berardinis, C. Angelini, L. D'Apice. Distinct antigen delivery systems induce dendritic cells divergent transcriptional response: new insights from a comparative and reproducible computational analysis. International Journal of Molecular Sciences, 18 (3), E494, (2017)
  4. 4) C. D’Aniello, E. Habibi, F. Cermola,D. Paris, F. Russo, A. Fiorenzano, G. Di Napoli, D. J. Melck, G.Cobellis, C. Angelini, A. Fico, R. Blelloch, A. Motta, H. G. Stunnenberg, D. De Cesare, E.J. Patriarca, and G. Minchiotti, Vitamin C and L-Proline Antagonistic Effects Capture Alternative States in the Pluripotency Continuum Stem Cell Reports, 8(1), pp. 1-10, (2017)
  5. 5) E. Di Costanzo, V. Ingangi, C. Angelini, M.F. Carfora, M.V. Carriero, R .Natalini, A Macroscopic Mathematical Model For Cell Migration Assays Using A Real-Time Cell Analysis PLoS ONE 11(9): e0162553 (2016)
  6. 6) A. Fiorenzano, E. Pascale, C. D'Aniello, D. Acampora, C. Bassalert, F. Russo, G. Andolfi, M. Biffoni, F. Francescangeli, A. Zeuner, C Angelini, C. Chazaud, E. J. Patriarca, A. Fico, G.Minchiotti. Cripto is essential to capture mouse epiblast stem cell and human embryonic stem cell pluripotency, Nature Communications 7, Article number: 12589 (2016)
  7. 7) A. Iuliano, A. Occhipinti, I. De Feis, C. Angelini, P. Lio'. Cancer markers selection using network-based Cox Regression: a methodological and computational practice., Frontiers in Physiology (2016).
  8. 8) G.F. Fulcoli, M. Franzese, X. Liu, Z. Zhang, C. Angelini,A. Baldini. Rebalancing gene haploinsufficiency in a mouse model of DiGeorge syndrome by targeting chromatin., Nature Communications, 7, Article number: 11688, (2016).
  9. 9) V. Riso, M. Cammisa, H. Kukreja, Z. Anvar, G. Verde, A. Sparago, B. Acurzio, S. Lad, E. Lonardo, A. Sankar, K. Helin, R. Feil, A. Fico, C. Angelini, G. Grimaldi, A. Riccio . ZFP57 maintains the parent-of-origin-specific expression of the imprinted genes and differentially affects non-imprinted targets in mouse embryonic stem cells, Nucleic Acids Research (2016).
  10. 10) M. Pinelli, A. Carissimo, L. Cutillo, CH Lai, M. Mutarelli, MN Moretti, MV Singh, M Karali, D. Carrella, M. Pizzo, F. Russo, S. Ferrari, D. Ponzin, C. Angelini, S. Banfi, D. di Bernardo. An atlas of gene expression and gene co-regulation in the human retina. Nucleic Acids Res. 2016
  11. 11) R. De Fez, R. Esposito, C. Angelini,C. Bianco Overproduction of indole-3-acetic acid in free-living rhizobia induces transcriptional changes resembling those occurring in nodule bacteroids. Molecular Plant-Microbe Interactions (2016)
  12. 12) U. Amato, A. Antoniadis, I. De Feis. Additive model selection. Statistical Methods and Applications, (2016)
  13. 13) A. Tarallo, C. Angelini, R. Sanges, M. Yagi, C. Agnisola, G. D’ Onofrio. On the genome base composition of teleosts: the effect of environment and lifestyle. BMC Genomics (2016)
  14. 14) F. Russo, D. Righelli, C. Angelini. Advancements in RNASeqGUI towards a Reproducible Analysis of RNA-Seq Experiments. BioMed Research International (2016).
  15. 15) Z. Anvar, M. Cammisa, V. Riso, I. Baglivo, H. Kukreja, A. Sparago, M. Girardot, S. Lad, I. De Feis, F. Cerrato, C. Angelini, R. Feil, P.V. Pedone, G. Grimaldi and A. Riccio, ZFP57 recognizes multiple and closely spaced sequence motif variants to maintain repressive epigenetic marks in mouse embryonic stem cells, Nucleic Acid Research (2015)
  16. 16) M. Scarpato, C. Angelini, E. Cocca, Pallotta M, Morescalchi M.A., Capriglione, T., Short interspersed DNA elements and miRNAs: a novel hidden gene regulation layer in zebrafish , Chomosome Research, (2015)
  17. 17) C. Angelini, R. Heller, R. Volkinshtein and D. Yekutieli Is this the right normalization? A diagnostic tool for ChIP-seq normalization. BMC Bioinformatics (2015).
  18. 18) A. Cicatelli, D. Baldantoni, P. Iovieno, M. Carotenuto, A. Alfani, I. De Feis, S. Castiglione. Genetically biodiverse potato cultivars grown on a suitable agricultural soil under compost amendment or mineral fertilization: yield, quality, genetic and epigenetic variations, soil properties, Science of Total Environment, volume 493, Pages 1025–1035. (2014)
  19. 19) F. Russo and C. Angelini. RNASeqGUI: A GUI for analyzing RNA-seq data. Bioinformatics, 30 (17): 2514-2516, (2014)
  20. 20) Angelini, D. De Canditiis, I. De Feis. Computational approaches for Isoform detection and estimation: Good and bad news. BMC Bioinformatics, 15:135, (2014)
  21. 21) Scarpato M, Esposito R, Evangelista D, Aprile M, Ambrosio MR, Angelini C, Ciccodicola A, Costa V. AnaLysis of Expression on human chromosome 21, ALE-HSA21: a pilot integrated web resource. Database (Oxford). (2014)
  22. 22) Cutillo L., De Feis I, Nikolaidou C, Sapatinas T. Wavelet density estimation for weighted data. Journal of Statistical Planning and Inference, Volume 146, Pages 1-19, (2014).
  23. 23) Comes S, Gagliardi M, Laprano N, Fico A, Cimmino A, Palamidessi A, De Cesare D, De Falco S, Angelini C, Scita G, Patriarca EJ, Matarazzo MR, Minchiotti G. L-Proline Induces a Mesenchymal-like Invasive Program in Embryonic Stem Cells by Remodeling H3K9 and H3K36 Methylation. Stem Cell Reports, (2013).
  24. 24) Cicatelli A, Fortunati T, De Feis I, Castiglione S. Oil composition and genetic biodiversity of ancient and new olive (Olea europea L.) varieties and accessions of southern Italy. Plant Sci. (2013)
  25. 25) Liò P, Angelini C, De Feis I, Nguyen VA. Statistical approaches to use a model organism for regulatory sequences annotation of newly sequenced species. PLoS One. (2012)
  26. 26) Berná L, Chaurasia A, Angelini C, Federico C, Saccone S, D'Onofrio G. The footprint of metabolism in the organization of mammalian genomes. BMC Genomics. 2012).
  27. 27) Angelini C, De Canditiis D, Pensky M. Clustering Time-Course Microarray Data Using Functional Bayesian Infinite Mixture Model. Journal of Applied Statistics, 39, 129-149, (2012).
  28. 28) Murino L, Angelini C, De Feis I, Raiconi G, Tagliaferri R. Beyond classical consensus clustering: the Least Squares approach to multiple solutions.Pattern Recognition Letters 32,1604-1612, (2011).
  29. 29) Costa V, Angelini C, D'Apice L, Mutarelli M, Casamassimi A, Sommese L, Gallo MA, Aprile M, Esposito R, Leone L, Donizetti A, Crispi S, Rienzo M, Sarubbi B, Calabrò R, Picardi M, Salvatore P, Infante T, De Berardinis P, Napoli C, Ciccodicola A. Massive-scale RNA-Seq analysis of non ribosomal transcriptome in human trisomy 21. PLoS One. (2011)
  30. 30) Pava-Ripoll M, Angelini C,< Fang W, Wang S, Posada FJ, St Leger R. The rhizosphere-competent entomopathogen Metarhizium anisopliae expresses a specific subset of genes in plant root exudate. Microbiology, (2011).
  31. 31) Costa V, Sommese L, Casamassimi A, Colicchio R, Angelini C, Marchesano V, Milone L, Farzati B, Giovane A, Fiorito C, Rienzo M, Picardi M, Avallone B, Marco Corsi M, Sarubbi B, Calabrò R, Salvatore P, Ciccodicola A, Napoli C. Impairment of circulating endothelial progenitors in Down syndrome.BMC Med Genomics. (2010)
  32. 32) Costa V, Angelini C, De Feis I, Ciccodicola A. Uncovering the complexity of transcriptomes with RNA-Seq.J Biomed Biotechnol. (2010).
  33. 33) Angelini C, De Canditiis D, Pensky M.Bayesian models for the two-sample time-course microarray experiments. Computational Statistics & Data Analysis, 53, pp. 1547-1565, (2009).
  34. 4) Abramovich A., De Feis I., Sapatinas T. Optimal testing for additivity in multiple nonparametric regression. Annals of the Institute of Statistical Mathematics, vol. 61, no. 3, pp. 691-714.
  35. 35) Angelini C, Cutillo L, De Canditiis D, Mutarelli M, Pensky M. BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.BMC Bioinformatics, (2008)
  36. 36) Mutarelli M, Cicatiello L, Ferraro L, Grober OM, Ravo M, Facchiano AM, Angelini C, Weisz A. Time-course analysis of genome-wide gene expression data from hormone-responsive human breast cancer cells.BMC Bioinformatics, (2008).
  37. 37) C. Angelini, D. De Canditiis, M. Mutarelli, M. Pensky. A Bayesian Approach to Estimation and Testing in Time-course Microarray Experiments, Statistical Applications in Genetics and Molecular Biology: vol 6 : Iss. 1, Article 24, (2007).
  38. 38) I. Cascino, F. Paladini, F. Belfiore, A., Cauli, C. Angelini, M.T. Fiorillo, A. Matieu, R. Sorrentino. Identification of previously unrecognized predisposing factors for ankylosing spondylitis from analysis of HLA-B27 extended haplotypes in Sardinia. Arthritis & Rheumatism, 56, pp. 2640-2651, (2007).
  39. 39) F. Abramovich, C. Angelini, D. De Canditiis. Pointwise optimality of Bayesian wavelet estimators. Ann. Inst. Statist. Math, 59, pp. 425-434,(2007).

Other Publications

  1. 1) F. Russo, D. Righelli, C. Angelini, Advantages and Limits in the Adoption of Reproducible Research and R-Tools for the Analysis of Omic Data. Lecture notes in Bioinformatics, 9874, pp 245-258, (2016).
  2. 2) A. Iuliano, A. Occhipinti, C. Angelini, I. De Feis, P.Liò. Applications of network-based survival analysis methods for pathway detection in cancer. in Lecture Notes in Bioinformatics, 8623, 76-88, (2015)
  3. 3) C. Angelini and V. Costa. Understanding gene regulatory mechanisms by integrating ChIP-seq and RNA-seq data: statistical solutions to biological problems , Front. Cell Dev. Biol.,(2014)
  4. 4) Gagliardi F., Angelini C. Discovering Typical Transcription Factors Patterns in Gene Expression Levels of Mouse Embryonic Stem Cells by Instance-Based Classifiers, ICIAP 2013 Workshops. Lecture Notes in Computer Science 8158, pp. 381-388, (2013).
  5. 5) Angelini C., De Canditiis D., Pensky M., Brownstein N. Bayesian models for the analysis of multi sample time-course microarray experiments. Lecture Notes in Bioinformatics 7548, pp. 21-35, (2012).
  6. 6) Angelini C., De Canditiis D., Pensky M. Bayesian methods for Time-course microarray analysis: from genes detection to clustering. Studies in Theoretical and Applied Statistics, Springer, pp. 47-56, (2012).
  7. 7) Costa V, Angelini C, D'Apice L, Mutarelli M, Casamassimi A, Sommese L, Gallo MA, Aprile M, Esposito R, Leone L, Donizetti A, Crispi S, Rienzo M, Sarubbi B, Calabrò R, Picardi M, Salvatore P, Infante T, De Berardinis P, Napoli C, Ciccodicola A. RNA-seq: from computational challenges to biological insights, in Network tools and applications in Bioinformatics, Proceeding of Nettab 2010, ARACNE, Network tools and Applications in Biology, pp. 77-83, (2010).
  8. 8) Angelini C., De Feis I., van der Wath R., Nguyen V.-A., Liò P. Combining Replicates and Nearby Species Data: Methodologies, Examples and Results.Lecture Notes in Bioinformatics, 6160, pp. 191-205, (2010)
  9. 9) Murino L., Angelini C., Bifulco I., De Feis I., Raiconi G., Tagliaferri R. Multiple Clustering Solutions Analysis Through Lest-Square Consensus Algorithms. Lecture Notes in Bioinformatics, 6160, 215-227, (2010)
  10. 10) Angelini C., De Canditiis D., Pensky M. Estimation and Testing in Time-course Microarray Experiments. Bayesian Modeling in Bioinformatics, Chapman & Hall/CRC Biostatistics Series. (2010).
  11. 11) Angelini,C., De Canditiis, D., Pensky, M. Bayesian models for time-course microarray analysis: from genes' detection to clustering. In Statistical methods for the analysis of large data-sets. Book of short paper of the Italian Statistical Society, Invited paper by the Royal Statistical Society, pp. 19-23, (2009).
  12. 12) Angelini C., Cutillo L., De Feis I., van der Wath R., Liò P. Combining experimental evidences from replicates and nearby species data for annotating novel genomes. AIP Proceedings, Vol. 1028, (2008).
  13. 13) Angelini, C.,Cutillo, L., De Feis, I, van der Wath, R, Liò, P. Identify regulatory sites using neighborhood species. In Lecture Notes in Computer Science, 4447, pp 1-10. (2007).