Profile

Dr Fabrizio Costa

Publications

_{Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.}

_{Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.}

| 2023 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999 |

2023

• Thomas G, Stoner O, Costa F, Ames RM. (2023) Fungal Pathogen Gene Selection for Predicting the Onset of Infection Using a Multi-Stage Machine Learning Approach, DOI:10.1101/2023.09.26.559518. [PDF]

2020

• Tran VD, Sperduti A, Backofen R, Costa F. (2020) Heterogeneous networks integration for disease-gene prioritization with node kernels, Bioinformatics, volume 36, no. 9, pages 2649-2656, DOI:10.1093/bioinformatics/btaa008. [PDF]

2019

• Miladi M, Sokhoyan E, Houwaart T, Heyne S, Costa F, Grüning B, Backofen R. (2019) GraphClust2: annotation and discovery of structured RNAs with scalable and accessible integrative clustering, DOI:10.1101/550335.
• Milad M, Sokhoyan E, Houwaart T, Heyne S, Costa F, Grüning B, Backofen R. (2019) Empowering the annotation and discovery of structured RNAs with scalable and accessible integrative clustering.
• Miladi M, Sokhoyan E, Houwaart T, Heyne S, Costa F, Grüning B, Backofen R. (2019) GraphClust2: Annotation and discovery of structured RNAs with scalable and accessible integrative clustering, Gigascience, volume 8, no. 12, DOI:10.1093/gigascience/giz150. [PDF]
• Mautner S, Backofen R, Costa F. (2019) Progress towards graph optimization: Efficient learning of vector to graph space mappings, ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pages 287-292.
• Mautner S, Montaseri S, Miladi M, Raden M, Costa F, Backofen R. (2019) ShaKer: RNA SHAPE prediction using graph kernel, Bioinformatics, volume 35, no. 14, pages i354-i359, DOI:10.1093/bioinformatics/btz395.

2018

• Costa F, Grün D, Backofen R. (2018) GraphDDP: a graph-embedding approach to detect differentiation pathways in single-cell-data using prior class knowledge, Nat Commun, volume 9, no. 1, DOI:10.1038/s41467-018-05988-7. [PDF]
• Raden M, Ali SM, Alkhnbashi OS, Busch A, Costa F, Davis JA, Eggenhofer F, Gelhausen R, Georg J, Heyne S. (2018) Freiburg RNA tools: a central online resource for RNA-focused research and teaching, Nucleic Acids Res, volume 46, no. W1, pages W25-W29, DOI:10.1093/nar/gky329. [PDF]
• Costa F, Tran Van D, Sperduti A. (2018) The conjunctive disjunctive graph node kernel for disease gene prioritization, Neurocomputing, DOI:10.1016/j.neucom.2018.01.089.

2017

• Backofen R, Costa F, Theis F, Marr C, Preusse M, Becker C, Saunders S, Palme K, Dovzhenko O. (2017) MicroRNA as an Integral Part of Cell Communication: Regularized Target Prediction and Network Prediction, Information- and Communication Theory in Molecular Biology, Springer.
• Tran-Van D, Sperduti A, Costa F. (2017) Joint Neighborhood Subgraphs Link Prediction, International Conference On Neural Information Processing, Guangzhou, China, 14th - 17th Nov 2017, Springer.
• Tran-Van D, Sperduti A, Costa F. (2017) Link Enrichment for Diffusion-based Graph Node Kernels, International Conference on Artificial Neural Networks, Italy, 11th - 15th Sep 2017.
• Navarin N, Costa F. (2017) An efficient graph kernel method for non-coding RNA functional prediction, Bioinformatics, volume 33, no. 17, pages 2642-2650, DOI:10.1093/bioinformatics/btx295. [PDF]
• Miladi M, Junge A, Costa F, Seemann SE, Havgaard JH, Gorodkin J, Backofen R. (2017) RNAscClust: clustering RNA sequences using structure conservation and graph based motifs, Bioinformatics, volume 33, no. 14, pages 2089-2096, DOI:10.1093/bioinformatics/btx114. [PDF]
• Donini M, Navarin N, Lauriola I, Aiolli F, Costa F. (2017) Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges (belgium), 26th - 28th Apr 2017.
• Van Dinh T, Sperduti A, Costa F. (2017) The Conjunctive Disjunctive Node Kernel, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges (belgium), 26th - 28th Apr 2017.
• Costa F. (2017) Learning an efficient constructive sampler for graphs, Artificial Intelligence, volume 244, pages 217-238, DOI:10.1016/j.artint.2016.01.006.

2016

• Phuong D, Hoinka J, Wang Y, Takahashi M, Zhou J, Costa F, Rossi J, Burnett J, Backofen R, Przytycka TM. (2016) AptaTRACE: Elucidating Sequence-Structure Binding Motifs by Uncovering Selection Trends in HT-SELEX Experiments, DOI:10.1101/047357.
• Dao P, Hoinka J, Wang Y, Takahashi M, Zhou J, Costa F, Rossi J, Burnett J, Backofen R, Przytycka TM. (2016) AptaTRACE: Elucidating Sequence-Structure Binding Motifs by Uncovering Selection Trends in HT-SELEX Experiments, DOI:10.48550/arxiv.1604.03081.
• Costa F, Alkhnbashi O, Saunders S, Shah S, Garrett RA, Backofen R. (2016) CRISPR-cas locus and array leader sequence boundaries prediction: towards an automated annotation of CRISPR-cas systems, Annual international CRISPR meeting.
• Costa F, Backofen R, Przytycka T, Dao P, Hoinka J, Wang Y, Takahashi M, Zhou J, Rossi J, Burnett J. (2016) AptaTRACE: Elucidating Sequence-Structure Binding Motifs by Uncovering Selection Trends in HT-SELEX Experiments, RECOMB.
• Costa F, Kohvaei P, Kleinkauf R. (2016) RNAsynth: Constraints learning for RNA inverse folding, ESANN 2016 - 24th European Symposium on Artificial Neural Networks, pages 17-22.
• Dao P, Hoinka J, Takahashi M, Zhou J, Ho M, Wang Y, Costa F, Rossi JJ, Backofen R, Burnett J. (2016) AptaTRACE Elucidates RNA Sequence-Structure Motifs from Selection Trends in HT-SELEX Experiments, Cell Syst, volume 3, no. 1, pages 62-70, DOI:10.1016/j.cels.2016.07.003. [PDF]
• de Araujo Oliveira JV, Costa F, Backofen R, Stadler PF, Machado Telles Walter ME, Hertel J. (2016) SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification, BMC Bioinformatics, volume 17, no. Suppl 18, DOI:10.1186/s12859-016-1345-6. [PDF]
• Lai ZW, Weisser J, Nilse L, Costa F, Keller E, Tholen M, Kizhakkedathu JN, Biniossek M, Bronsert P, Schilling O. (2016) Formalin-Fixed, Paraffin-Embedded Tissues (FFPE) as a Robust Source for the Profiling of Native and Protease-Generated Protein Amino Termini, MOLECULAR & CELLULAR PROTEOMICS, volume 15, no. 6, pages 2203-2213, DOI:10.1074/mcp.O115.056515. [PDF]
• Alkhnbashi OS, Shah SA, Garrett RA, Saunders SJ, Costa F, Backofen R. (2016) Characterizing leader sequences of CRISPR loci, Bioinformatics, volume 32, no. 17, pages i576-i585, DOI:10.1093/bioinformatics/btw454. [PDF]
• Corrado G, Tebaldi T, Costa F, Frasconi P, Passerini A. (2016) RNAcommender: genome-wide recommendation of RNA-protein interactions, Bioinformatics, volume 32, no. 23, pages 3627-3634, DOI:10.1093/bioinformatics/btw517.

2015

• Alkhnbashi O, Shah S, Garrett R, Saunders S, Costa F, Backofen R. (2015) Towards an automatic annotation of CRISPR-cas subtypes, Annual international CRISPR meeting.
• Frasconi P, Costa F, De Raedt L, De Grave K. (2015) KLog: A language for logical and relational learning with kernels, IJCAI International Joint Conference on Artificial Intelligence, volume 2015-January, pages 4183-4187.
• Makarova KS, Wolf YI, Alkhnbashi OS, Costa F, Shah SA, Saunders SJ, Barrangou R, Brouns SJJ, Charpentier E, Haft DH. (2015) An updated evolutionary classification of CRISPR-Cas systems, NATURE REVIEWS MICROBIOLOGY, volume 13, no. 11, pages 722-736, DOI:10.1038/nrmicro3569. [PDF]

2014

• Verbeke M, Frasconi P, De Grave K, Costa F, De Raedt L. (2014) kLogNLP: Graph Kernel-based Relational Learning of Natural Language, PROCEEDINGS OF 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: SYSTEM DEMONSTRATIONS, pages 85-90. [PDF]
• Costa F, Verbeke M, De Raedt L. (2014) Relational Regularization and Feature Ranking, SIAM International Conference on Data Mining.
• Videm P, Rose D, Costa F, Backofen R. (2014) BlockClust: Efficient clustering and classification of non-coding RNAs from short read RNA-Seq profiles, Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), volume P-235, pages 12-22.
• Backofen R, Amman F, Costa F, Findeiss S, Richter AS, Stadler PF. (2014) Bioinformatics of prokaryotic RNAs, RNA BIOLOGY, volume 11, no. 5, pages 470-483, DOI:10.4161/rna.28647. [PDF]
• Kundu K, Mann M, Costa F, Backofen R. (2014) MoDPepInt: an interactive web server for prediction of modular domain-peptide interactions, BIOINFORMATICS, volume 30, no. 18, pages 2668-2669, DOI:10.1093/bioinformatics/btu350. [PDF]
• Maticzka D, Lange SJ, Costa F, Backofen R. (2014) GraphProt: modeling binding preferences of RNA-binding proteins, GENOME BIOLOGY, volume 15, no. 1, article no. ARTN R17, DOI:10.1186/gb-2014-15-1-r17. [PDF]
• Frasconi P, Costa F, De Raedt L, De Grave K. (2014) kLog: A language for logical and relational learning with kernels, ARTIFICIAL INTELLIGENCE, volume 217, pages 117-143, DOI:10.1016/j.artint.2014.08.003. [PDF]
• Ferrarese R, Harsh GR, Yadav AK, Bug E, Maticzka D, Reichardt W, Dombrowski SM, Miller TE, Masilamani AP, Dai F. (2014) Lineage-specific splicing of a brain-enriched alternative exon promotes glioblastoma progression, JOURNAL OF CLINICAL INVESTIGATION, volume 124, no. 7, pages 2861-2876, DOI:10.1172/JCI68836. [PDF]
• Videm P, Rose D, Costa F, Backofen R. (2014) BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles, BIOINFORMATICS, volume 30, no. 12, pages 274-282, DOI:10.1093/bioinformatics/btu270. [PDF]
• Alkhnbashi OS, Costa F, Shah SA, Garrett RA, Saunders SJ, Backofen R. (2014) CRISPRstrand: predicting repeat orientations to determine the crRNA-encoding strand at CRISPR loci, BIOINFORMATICS, volume 30, no. 17, pages I489-I496, DOI:10.1093/bioinformatics/btu459. [PDF]
• Corrado G, Tebaldi T, Bertamini G, Costa F, Quattrone A, Viero G, Passerini A. (2014) PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps, BMC Genomics, volume 15, DOI:10.1186/1471-2164-15-304. [PDF]

2013

• Costa F, Sorescu D. (2013) The Constructive Learning Problem: an efficient approach for hypergraphs, Workshop on Constructive Machine Learning at NIPS.
• Kundu K, Costa F, Backofen R. (2013) A graph kernel approach for alignment-free domain-peptide interaction prediction with an application to human SH3 domains, BIOINFORMATICS, volume 29, no. 13, pages 335-343, DOI:10.1093/bioinformatics/btt220. [PDF]
• Kundu K, Costa F, Huber M, Reth M, Backofen R. (2013) Semi-Supervised Prediction of SH2-Peptide Interactions from Imbalanced High-Throughput Data, PLOS ONE, volume 8, no. 5, article no. ARTN e62732, DOI:10.1371/journal.pone.0062732. [PDF]

2012

• Frasconi P, Costa F, De Raedt L, De Grave K. (2012) kLog: A Language for Logical and Relational Learning with Kernels, ArXiv.
• Antanas L, Frasconi P, Costa F, Tuytelaars T, De Raedt L. (2012) A Relational Kernel-based Framework for Hierarchical Image Understanding, Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012).
• Heyne S, Costa F, Rose D, Backofen R. (2012) GraphClust: alignment-free structural clustering of local RNA secondary structures, BIOINFORMATICS, volume 28, no. 12, pages I224-I232, DOI:10.1093/bioinformatics/bts224. [PDF]

2011

• Ramon J, Costa F, Florêncio CC, Kok J. (2011) Preface, Fundamenta Informaticae, volume 113, no. 2, DOI:10.3233/FI-2011-601.
• Maticzka D, Backofen R, Costa F. (2011) Prediction of binding preferences of RNA-binding proteins using a novel graph representation, 19th Annual International Conference on Intelligent Systems for Molecular Biology and 10th European Conference on Computational Biology (ISMB-ECCB)(poster).
• Kundu K, Costa F, Sinha R, Reth M, Huber M, Backofen R. (2011) Identification of SH2-peptide interactions using support vector machine, 19th Annual International Conference on Intelligent Systems for Molecular Biology and 10th European Conference on Computational Biology (ISMB-ECCB) (poster).
• Vens C, Costa F. (2011) Random forest based feature induction, Proceedings - IEEE International Conference on Data Mining, ICDM, pages 744-753, DOI:10.1109/ICDM.2011.121.

2010

• Ramon J, Costa F, Florencio CC, Kok J. (2010) StReBio'09, ACM SIGKDD Explorations Newsletter, volume 11, no. 2, pages 88-89, DOI:10.1145/1809400.1809418.
• Kimmig A, Costa F. (2010) Link and node prediction in metabolic networks with probabilistic logic, Analysis of Complex Networks, European Conference on Machine Learning (ECML).
• Costa F. (2010) Augmented molecular graph kernel QSARs, 5th Joint Sheffield Conference on Chemoinformatics, (poster).
• Kimmig A, Costa F. (2010) Link and Node Prediction in Metabolic Network with Probabilistic Logic, 7th International Symposium on Networks in Bioinformatics (ISNB).
• Costa F, De Grave K. (2010) Fast neighborhood subgraph pairwise distance kernel, Proceedings of the 26th International Conference on Machine Learning.
• Grave KD, Costa F. (2010) Molecular Graph Augmentation with Rings and Functional Groups, Journal of Chemical Information and Modeling, volume 50, no. 9, pages 1660-1668, DOI:10.1021/ci9005035. [PDF]
• Schietgat L, Costa F, Ramon J, De Raedt L. (2010) Effective feature construction by maximum common subgraph sampling, Machine Learning, volume 83, no. 2, pages 137-161, DOI:10.1007/s10994-010-5193-8. [PDF]

2009

• Costa Florêncio C, Costa F, Ramon J, Kok J. (2009) Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics, StReBio '09: Preface, Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics, StReBio '09.
• Schietgat L, Costa F, Ramon J, De Raedt L. (2009) Maximum Common Subgraph Mining: A Fast and Effective Approach towards Feature Generation, 7th International Workshop on Mining and Learning with Graphs (MLG).
• Ramon J, Costa F. (2009) Handling missing values and censored data in PCA of pharmacological matrices, KDD Workshop on Statistical and Relational Learning in Bioinformatics.

2008

• Costa F, Bringmann B. (2008) Towards Combining Pattern Mining and Graph Kernels, Mining Complex Data (MCD) held at International Conference on Data Mining series (ICDM),.
• Costa F, Bringmann B. (2008) Towards Structural Feature Selection, Machine learning and intelligent optimization in bioinformatics (MALIOB) Workshop held at Learning and Intelligent OptimizatioN (Lion 3).
• Vullo A, Passerini A, Frasconi P, Costa F, Pollastri G. (2008) On the convergence of protein structure and dynamics. Statistical learning studies of pseudo folding pathways, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 4973 LNCS, pages 200-211, DOI:10.1007/978-3-540-78757-0_18.
• Costa F, Passerini A, Lippi M, Frasconi P. (2008) A semiparametric generative model for efficient structured-output supervised learning, Annals of Mathematics and Artificial Intelligence, volume 54, no. 1-3, pages 207-222, DOI:10.1007/s10472-009-9137-6.
• Costa F, Menchetti S, Frasconi P. (2008) Comparing sequence classification algorithms for protein subcellular localization, Studies in Computational Intelligence, volume 77, pages 23-48, DOI:10.1007/978-3-540-73954-8_2.

2007

• Ceroni A, Costa F, Frasconi P. (2007) Classification of small molecules by two- and three-dimensional decomposition kernels, Bioinformatics, volume 23, no. 16, pages 2038-2045, DOI:10.1093/bioinformatics/btm298. [PDF]

2006

• Costa F, Menchetti S, Ceroni A, Passerini A, Frasconi P. (2006) Decomposition Kernels for Natural Language Processing, Workshop on Learning Structured Information in Natural Language Applications at the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL).
• Costa F, Passerini A, Frasconi P. (2006) Learning Structured Outputs via Kernel Dependency Estimation and Stochastic Grammars, Mining and Learning with Graphs (MLG) held at European Conference on Machine Learning (ECML).

2005

• Menchetti S, Costa F, Frasconi P. (2005) Weighted Decomposition Kernels for Protein Subcellular Localization, Annual Meeting of the Bioinformatics Italian Society (BITS).
• Cerbioni K, Palanca E, Starita A, Costa F, Frasconi P. (2005) A Grid Focused Community Crawling Architecture for Medical Information Retrieval Services, 2nd International Conference on Computational Intelligence in Medicine and Healthcare, BIOPATTERN Conference.
• Menchetti S, Costa F, Frasconi P, Pontil M. (2005) Wide coverage natural language processing using kernel methods and neural networks for structured data, Pattern Recognition Letters, volume 26, no. 12, pages 1896-1906, DOI:10.1016/j.patrec.2005.03.011.
• Menchetti S, Costa F, Frasconi P. (2005) Weighted decomposition kernels, ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning, pages 585-592, DOI:10.1145/1102351.1102425.
• Costa F, Frasconi P, Lombardo V, Sturt P, Soda G. (2005) Ambiguity resolution analysis in incremental parsing of natural language, IEEE Trans Neural Netw, volume 16, no. 4, pages 959-971, DOI:10.1109/TNN.2005.849837. [PDF]

2004

• Costa F, Frasconi P. (2004) Distributed community crawling, Proceedings of the 13th International World Wide Web Conference on Alternate Track, Papers and Posters, WWW Alt. 2004, pages 362-363, DOI:10.1145/1013367.1013476.
• Costa F, Frasconi P. (2004) Distributed community crawling, Thirteenth International World Wide Web Conference Proceedings, WWW2004, pages 1094-1095.

2003

• Menchetti S, Costa F, Frasconi P, Pontil M. (2003) Comparing Convolution Kernels and Recursive Neural Networks for Learning Preferences on Structured Data, International Workshop on Artificial Neural Networks in Pattern Recognition (IAPR).
• Sturt P, Costa F, Lombardo V, Frasconi P. (2003) Learning first-pass structural attachment preferences with dynamic grammars and recursive neural networks, Cognition, volume 88, no. 2, pages 133-169, DOI:10.1016/s0010-0277(03)00026-x. [PDF]
• Costa F, Frasconi P, Lombardo V. (2003) Towards Incremental Parsing of Natural Language Using Recursive Neural Networks, Applied Intelligence, volume 19, pages 9-25, DOI:10.1023/A:1023860521975.

2002

• Costa F, Frasconi P, Sturt P, Lombardo V. (2002) Exploring the effect of experience on a recursive neural network model of structural preferences, 15th Annual Conference on Human Sentence Processing (CUNY).
• Costa F, Frasconi P, Lombardo V, Sturt P, Soda G. (2002) Enhancing first-pass attachment prediction, 15th European Conference on Artificial Intelligence (ECAI).

2001

• Costa F, Sturt P, Lombardo V, Frasconi P. (2001) The effect of experience on a hybrid model of human first-pass attachment preferences, Annual Conference on Architectures and Mechanisms for Language Processing (AMLAP).
• Sturt P, Lombardo V, Costa F, Frasconi P. (2001) A wide-coverage model of first-pass structural preferences in human parsing, 14th Annual Conference on Human Sentence Processing (CUNY).
• Costa F, Lombardo V, Frasconi P, Soda G. (2001) Wide coverage incremental parsing by learning attachment preferences, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 2175, pages 297-307.

2000

• Costa F, Frasconi P, LOmbardo V, Soda G. (2000) Learning to Rank Structured Alternatives: An Application to Incremental Processing of Natural Language, Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries (ICML).
• Costa F, Frasconi P, Lombardo V, Soda G. (2000) Learning to ranking structured alternatives: an application to incremental processing of Natural Language, Conference of the Italian Association for Artificial Intelligence (AIIA).
• Costa F, Frasconi P, Lombardo V, Soda G. (2000) Learning Incremental Syntactic Structures with Recursive Neural Networks, Conference on Knowledge-Based Engineering Systems (KES), volume 2, pages 458-461.
• Sturt P, Lombardo V, Costa F, Frasconi P. (2000) An Experience-Based Model of Incremental Parsing using Dynamic Grammars and Recursive Neural Networks, Annual Conference on Architectures and Mechanisms for Language Processing (AMLAP).

1999

• Costa F, Frasconi P, Soda G. (1999) Recursive Connectionist Networks for Trees with Large Outdegree, Conference of the Italian Association for Artificial Intelligence (AIIA).
• Costa F, Frasconi P, Soda G. (1999) A topological transformation for hidden recursive models architecture networks, ESANN.

Showing 91 publications from Symplectic.