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Michele Ceccarelli
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2020 – today
- 2024
- [c39]Stefano Bistarelli, Michele Ceccarelli, Chiara Luchini, Ivan Mercanti, Francesco Santini:
A Preliminary Study on the Creation of a Covert Channel with HTTP Headers. ITASEC 2024 - [i4]Lujia Wang, Hairong Wang, Fulvio D'Angelo, Lee Curtin, Christopher P. Sereduk, Gustavo De Leon, Kyle W. Singleton, Javier Urcuyo, Andrea Hawkins-Daarud, Pamela R. Jackson, Chandan Krishna, Richard S. Zimmerman, Devi P. Patra, Bernard R. Bendok, Kris A. Smith, Peter Nakaji, Kliment Donev, Leslie C. Baxter, Maciej M. Mrugala, Michele Ceccarelli, Antonio Iavarone, Kristin R. Swanson, Nhan L. Tran, Leland S. Hu, Jing Li:
Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. CoRR abs/2401.00128 (2024) - 2023
- [c38]Stefano Bistarelli
, Michele Ceccarelli
A Survey of Steganography Tools at Layers 2-4 and HTTP. ARES 2023: 81:1-81:9 - 2021
- [j35]Francesca P. Caruso
A review of COVID-19 biomarkers and drug targets: resources and tools. Briefings Bioinform. 22(2): 701-713 (2021) - [j34]Raghvendra Mall
Network-based identification of key master regulators associated with an immune-silent cancer phenotype. Briefings Bioinform. 22(6) (2021) - [j33]Antonio de Falco, Zoltán Dezsö, Francesco Ceccarelli
Adaptive one-class Gaussian processes allow accurate prioritization of oncology drug targets. Bioinform. 37(10): 1420-1427 (2021) - [j32]Antonella Paladino
Structural Model for Recruitment of RIT1 to the LZTR1 E3 Ligase: Evidences from an Integrated Computational Approach. J. Chem. Inf. Model. 61(4): 1875-1888 (2021) - 2020
- [j31]Zoltán Dezsö
Machine learning prediction of oncology drug targets based on protein and network properties. BMC Bioinform. 21(1): 104 (2020) - [j30]Teresa Maria Rosaria Noviello
Deep learning predicts short non-coding RNA functions from only raw sequence data. PLoS Comput. Biol. 16(11) (2020) - [j29]Michele Ceccarelli:
Preface: In memory of Alfredo Petrosino. Pattern Recognit. Lett. 138: 657-658 (2020)
2010 – 2019
- 2018
- [j28]Teresa Maria Rosaria Noviello
Detection of long non-coding RNA homology, a comparative study on alignment and alignment-free metrics. BMC Bioinform. 19(1): 407:1-407:12 (2018) - [i3]Raghvendra Mall
An unsupervised disease module identification technique in biological networks using novel quality metric based on connectivity, conductance and modularity. F1000Research 7: 378 (2018) - [i2]Tiago Chedraoui Silva, Antonio Colaprico
TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data. F1000Research 7: 439 (2018) - 2017
- [j27]Giovanna M. M. Ventola, Teresa Maria Rosaria Noviello
Identification of long non-coding transcripts with feature selection: a comparative study. BMC Bioinform. 18(1): 187:1-187:16 (2017) - [j26]Raghvendra Mall
Detection of statistically significant network changes in complex biological networks. BMC Syst. Biol. 11(1): 32:1-32:17 (2017) - [c37]Raghvendra Mall
Differential Community Detection in Paired Biological Networks. BCB 2017: 330-339 - [c36]Raghvendra Mall
An adaptive refinement for community detection methods for disease module identification in biological networks using novel metric based on connectivity, conductance & modularity. BIBM 2017: 2282-2284 - 2016
- [i1]Tiago Chedraoui Silva
TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages. F1000Research 5: 1542 (2016) - 2015
- [j25]Samreen Anjum, Sandro Morganella
VEGAWES: variational segmentation on whole exome sequencing for copy number detection. BMC Bioinform. 16: 315:1-315:10 (2015) - [j24]Luigi Cerulo, Massimiliano Di Penta
Irish: A Hidden Markov Model to detect coded information islands in free text. Sci. Comput. Program. 105: 26-43 (2015) - [c35]Michele Ceccarelli
Infer Gene Regulatory Networks from Time Series Data with Probabilistic Model Checking. FormaliSE@ICSE 2015: 26-32 - 2013
- [j23]Luigi Cerulo
A negative selection heuristic to predict new transcriptional targets. BMC Bioinform. 14(S-1): S3 (2013) - [c34]Michele Ceccarelli
Infer gene regulatory networks from time series data with formal methods. BIBM 2013: 115-120 - [c33]Giovanna Maria Ventola
An Approach to Identify miRNA Associated with Cancer Altered Pathways. ICIAP Workshops 2013: 399-408 - [c32]Luigi Cerulo, Michele Ceccarelli
A Hidden Markov Model to detect coded information islands in free text. SCAM 2013: 157-166 - 2012
- [j22]Sandro Morganella
VegaMC: a R/bioconductor package for fast downstream analysis of large array comparative genomic hybridization datasets. Bioinform. 28(19): 2512-2514 (2012) - 2011
- [j21]Sandro Morganella
Finding recurrent copy number alterations preserving within-sample homogeneity. Bioinform. 27(21): 2949-2956 (2011) - [c31]Stefano Maria Pagnotta
An Algorithm for Finding Gene Signatures Supervised by Survival Time Data. KES (1) 2011: 568-578 - [c30]Gerardo Canfora
How Long Does a Bug Survive? An Empirical Study. WCRE 2011: 191-200 - 2010
- [j20]Sandro Morganella, Luigi Cerulo
VEGA: variational segmentation for copy number detection. Bioinform. 26(24): 3020-3027 (2010) - [j19]Pietro Zoppoli
TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach. BMC Bioinform. 11: 154 (2010) - [j18]Luigi Cerulo
Learning gene regulatory networks from only positive and unlabeled data. BMC Bioinform. 11: 228 (2010) - [j17]Paulo J. G. Lisboa, Alfredo Vellido
Data Mining in Cancer Research [Application Notes]. IEEE Comput. Intell. Mag. 5(1): 14-18 (2010) - [j16]Michele Ceccarelli
Automatic Detection and Surface Measurements of Micronucleus by a Computer Vision Approach. IEEE Trans. Instrum. Meas. 59(9): 2383-2390 (2010) - [c29]Luigi Cerulo
Labeling Negative Examples in Supervised Learning of New Gene Regulatory Connections. CIBB 2010: 159-173 - [c28]Michele Ceccarelli
An eclectic approach for change impact analysis. ICSE (2) 2010: 163-166 - [c27]Gerardo Canfora
Using multivariate time series and association rules to detect logical change coupling: An empirical study. ICSM 2010: 1-10 - [c26]Carlo Sansone, Vincenzo Paduano, Michele Ceccarelli:
Combining 2D and 3D Features to Classify Protein Mutants in HeLa Cells. MCS 2010: 284-293
2000 – 2009
- 2009
- [j15]Michele Ceccarelli
Virtual genetic coding and time series analysis for alternative splicing prediction in C. elegans. Artif. Intell. Medicine 45(2-3): 109-115 (2009) - [j14]Michele Ceccarelli, Antonio d'Acierno
A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection. BMC Bioinform. 10(S-12): 9 (2009) - [j13]Sandro Morganella
IRIS: a method for reverse engineering of regulatory relations in gene networks. BMC Bioinform. 10: 444 (2009) - [j12]Michele Ceccarelli, Antonio Maratea:
Concordance indices for comparing fuzzy, possibilistic, rough and grey partitions. Int. J. Knowl. Eng. Soft Data Paradigms 1(4): 331-344 (2009) - [c25]Pietro Zoppoli
An Information Theoretic Approach to Reverse Engineering of Regulatory Gene Networks from Time-Course Data. CIBB 2009: 97-111 - [c24]Alessandro De Stasio, Marcus Ertelt, Wolfgang Kemmner, Ulf Leser, Michele Ceccarelli
Exploiting scientific workflows for large-scale gene expression data analysis. ISCIS 2009: 448-453 - [c23]Michele Ceccarelli, Alessandro De Stasio, Antonio Donatiello, Dante Vitale:
A Guideline Engine For Knowledge Management in Clinical Decision Support Systems (CDSSs). SEKE 2009: 252-257 - [c22]Michele Ceccarelli
Reverse Engineering of Regulatory Relations in Gene Networks by a Probabilistic Approach. WILF 2009: 360-367 - 2008
- [j11]Michele Ceccarelli
Improving fuzzy clustering of biological data by metric learning with side information. Int. J. Approx. Reason. 47(1): 45-57 (2008) - [c21]Michele Ceccarelli
A Machine Learning Approach to Mass Spectra Classification with Unsupervised Feature Selection. CIBB 2008: 242-252 - [c20]Michele Ceccarelli
KON^3: A Clinical Decision Support System, in Oncology Environment, Based on Knowledge Management. ICTAI (2) 2008: 206-210 - [c19]Michele Ceccarelli
Image Registration using Non-Linear Diffusion. IGARSS (5) 2008: 220-223 - [c18]Michele Ceccarelli, Antonio Maratea:
A Fuzzy Extension of Some Classical Concordance Measures and an Efficient Algorithm for Their Computation. KES (3) 2008: 755-763 - 2007
- [j10]Giuliano Antoniol, Michele Ceccarelli
Microarray image gridding with stochastic search based approaches. Image Vis. Comput. 25(2): 155-163 (2007) - [j9]Michele Ceccarelli
A Finite Markov Random Field approach to fast edge-preserving image recovery. Image Vis. Comput. 25(6): 792-804 (2007) - [c17]Michele Ceccarelli, Antonio Maratea:
Assessing Clustering Reliability and Features Informativeness by Random Permutations. KES (3) 2007: 878-885 - [c16]Michele Ceccarelli, Antonio Maratea:
An Alternative Splicing Predictor in C.Elegans Based on Time Series Analysis. WILF 2007: 588-595 - 2006
- [j8]Nazzareno Diodato
Computational uncertainty analysis of groundwater recharge in catchment. Ecol. Informatics 1(4): 377-389 (2006) - [j7]Michele Ceccarelli
Content-based Image Retrieval by a Fuzzy Scale-space Approach. Int. J. Pattern Recognit. Artif. Intell. 20(6): 849-868 (2006) - [j6]Michele Ceccarelli
A Deformable Grid-Matching Approach for Microarray Images. IEEE Trans. Image Process. 15(10): 3178-3188 (2006) - [c15]Michele Ceccarelli, Nicola De Luca, Sandro Morganella:
An Active Contour Approach To Automatic Detection Of The Intima-Media Thickness. ICASSP (2) 2006: 709-712 - 2005
- [c14]Michele Ceccarelli
A Fuzzy Scale-Space Approach to Feature-Based Image Representation and Retrieval. BVAI 2005: 377-385 - [c13]Michele Ceccarelli
Fast Edge Preserving Picture Recovery by Finite Markov Random Fields. ICIAP 2005: 277-286 - [c12]Giuliano Antoniol, Michele Ceccarelli
Microarray image addressing based on the Radon transform. ICIP (1) 2005: 13-16 - [c11]Michele Ceccarelli
Semi-supervised Fuzzy c-Means Clustering of Biological Data. WILF 2005: 259-266 - 2004
- [c10]Giuliano Antoniol, Michele Ceccarelli
A Markov Random Field Approach to Microarray Image Gridding. ICPR (3) 2004: 550-553 - [c9]Giuliano Antoniol, Michele Ceccarelli, P. Petrillo, Alfredo Petrosino:
An ICA Approach to Unsupervised Change Detection in Multispectral Images. WIRN 2004: 299-311 - 2003
- [c8]Michele Ceccarelli
High Performance Missing Data Detection and Interpolation for Video Compression and Restoration Applications. IPDPS 2003: 233 - [c7]Giuliano Antoniol, Michele Ceccarelli, Antonio Maratea, F. Russo:
Classification of Digital Terrain Models Through Fuzzy Clustering: An Application. WILF 2003: 174-182 - [c6]Giuliano Antoniol, Michele Ceccarelli, Vincenzo Fabio Rollo, Wanda Longo, Teresa Nutile, Marina Ciullo, Enza Colonna, Antonietta Calabria, Maria Astore, Anna Lembo, Paola Toriello, M. Grazia Persico:
Browsing Large Pedigrees to Study of the Isolated Populations in the "Parco Nazionale del Cilento e Vallo di Diano". WIRN 2003: 258-268 - 2002
- [j5]Michele Ceccarelli
A parallel fuzzy scale-space approach to the unsupervised texture separation. Pattern Recognit. Lett. 23(5): 557-567 (2002) - [c5]Michele Ceccarelli
High performance motion analysis for video restoration. DSP 2002: 689-692 - 2001
- [c4]Michele Ceccarelli
Circle Detection Based on Orientation Matching. ICIAP 2001: 119-124 - [c3]Michele Ceccarelli, Alfredo Petrosino:
The orientation matching approach to circular object detection. ICIP (3) 2001: 712-715 - 2000
- [c2]Alfredo Petrosino, Michele Ceccarelli:
Unsupervised Texture Discrimination Based on Rough Fuzzy Sets and Parallel Hierarchical Clustering. ICPR 2000: 7100-7103
1990 – 1999
- 1999
- [c1]Alfredo Petrosino, Michele Ceccarelli
A Scale-Space Approach to Pre-Attentive Texture Discrimination. ICIAP 1999: 162-167 - 1997
- [j4]Michele Ceccarelli
Multi-feature adaptive classifiers for SAR image segmentation. Neurocomputing 14(4): 345-363 (1997) - 1996
- [j3]Michele Ceccarelli
Sequence recognition with radial basis function networks: experiments with spoken digits. Neurocomputing 11(1): 75-88 (1996) - 1993
- [j2]Michele Ceccarelli, Alfredo Petrosino, Roberto Vaccaro:
Competitive neural networks on message-passing parallel computers. Concurr. Pract. Exp. 5(6): 449-470 (1993) - 1992
- [j1]Eduardo R. Caianiello, Michele Ceccarelli, Maria Marinaro:
Can Spurious States Be Useful? Complex Syst. 6(1) (1992)
Coauthor Index
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last updated on 2024-12-10 20:50 CET by the dblp team
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