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Marco J. Morelli
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2020 – today
- 2022
- [j8]Fabrizio Frasca, Matteo Matteucci, Michele Leone, Marco J. Morelli, Marco Masseroli:
Accurate and highly interpretable prediction of gene expression from histone modifications. BMC Bioinform. 23(1): 151 (2022)
2010 – 2019
- 2018
- [j7]Vahid Jalili, Matteo Matteucci, Marco Masseroli, Marco J. Morelli:
Using combined evidence from replicates to evaluate ChIP-seq peaks. Bioinform. 34(13): 2338 (2018) - [c2]Fabrizio Frasca, Matteo Matteucci, Marco J. Morelli, Marco Masseroli:
Exposing and Characterizing Subpopulations of Distinctly Regulated Genes by K-Plane Regression. CIBB 2018: 227-238 - [c1]Fabrizio Frasca, Matteo Matteucci, Marco Masseroli, Marco J. Morelli:
Modeling Gene Transcriptional Regulation by Means of Hyperplanes Genetic Clustering. IJCNN 2018: 1-8 - 2017
- [j6]Vahid Jalili, Matteo Matteucci, Marco J. Morelli, Marco Masseroli:
MuSERA: Multiple Sample Enriched Region Assessment. Briefings Bioinform. 18(3): 367-381 (2017) - [j5]Alice C. L. Parodi, Laura M. Sangalli, Simone Vantini, Bruno Amati, Piercesare Secchi, Marco J. Morelli:
FunChIP: an R/Bioconductor package for functional classification of ChIP-seq shapes. Bioinform. 33(16): 2570-2572 (2017) - 2015
- [j4]Vahid Jalili, Matteo Matteucci, Marco Masseroli, Marco J. Morelli:
Using combined evidence from replicates to evaluate ChIP-seq peaks. Bioinform. 31(17): 2761-2769 (2015) - [j3]Stefano de Pretis, Theresia Kress, Marco J. Morelli, Giorgio E. M. Melloni, Laura Riva, Bruno Amati, Mattia Pelizzola:
INSPEcT: a computational tool to infer mRNA synthesis, processing and degradation dynamics from RNA- and 4sU-seq time course experiments. Bioinform. 31(17): 2829-2835 (2015) - [j2]Kamal Kishore, Stefano de Pretis, Ryan Lister, Marco J. Morelli, Valerio Bianchi, Bruno Amati, Joseph R. Ecker, Mattia Pelizzola:
methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data. BMC Bioinform. 16: 313:1-313:11 (2015) - 2012
- [j1]Marco J. Morelli, Gaël Thébaud, Joël Chadoeuf, Donald P. King, Daniel T. Haydon, Samuel Soubeyrand:
A Bayesian Inference Framework to Reconstruct Transmission Trees Using Epidemiological and Genetic Data. PLoS Comput. Biol. 8(11) (2012)
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