Publications

Jessica Gliozzo, Giosuè Cataldo Marinò, Bonometti Arturo, Marco Frasca, Dario Malchiodi. Resource-Limited Automated Ki67 Index Estimation in Breast Cancer. ICBRA, 2023.

Giosuè Cataldo Marinò, Flavio Furia, Dario Malchiodi, Marco Frasca. Efficient and Compact Representations of Deep Neural Networks via Entropy Coding. IEEE Access, 2023.

Lorenzo Carfagna, Giovanni Manzini. Compressibility Measures for Two-Dimensional Data. SPIRE, 2023.

Paolo Ferragina, Mariagiovanna Rotundo, Giorgio Vinciguerra. Engineering a Textbook Approach to Index Massive String Dictionaries. SPIRE, 2023.

Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo. Neural networks as building blocks for the design of efficient learned indexes. Neural Comput. Appl., 2023.

Paolo Ferragina, Marco Frasca, Giosuè Cataldo Marinò, Giorgio Vinciguerra. On nonlinear learned string indexing. IEEE Access, 2023.

PDF Code Dataset DOI

Raffaele Giancarlo, Giovanni Manzini, Antonio Restivo, Giovanna Rosone, Marinella Sciortino. A New Class of String Transformations for Compressed Text Indexing. Inf. Comput., 2023.

Paolo Ferragina, Hans-Peter Lehmann, Peter Sanders, Giorgio Vinciguerra. Learned monotone minimal perfect hashing. ESA, 2023.

Alessio Conte, Nicola Cotumaccio, Travis Gagie, Giovanni Manzini, Nicola Prezza, Marinella Sciortino. Computing matching statistics on Wheeler DFAs. DCC, 2023.

Fabio Fassetti, Simona E. Rombo, Cristina Serrao. Discriminative Pattern Discovery for the Characterization of Different Network Populations. Bioinformatics, 2023.

Dario Malchiodi, Davide Raimondi, Giacomo Fumagalli, Raffaele Giancarlo, Marco Frasca. A Critical Analysis of Classifier Selection in Learned Bloom Filters: the Essentials. EANN, 2023.

Domenico Amato, Raffaele Giancarlo, Giosuè Lo Bosco. Learned Sorted Table Search and Static Indexes in Small-Space Data Models. Data, 2023.

Giosuè Cataldo Marinò, Alessandro Petrini, Dario Malchiodi, Marco Frasca. Deep neural networks compression: A comparative survey and choice recommendations. Neurocomputing, 2022.

Lorenzo Di Rocco, Umberto Ferraro Petrillo, Simona E. Rombo. DIAMIN: a software library for the distributed analysis of large-scale molecular interaction networks. BMC Bioinformatics, 2022.

Paolo Ferragina, Giovanni Manzini, Giorgio Vinciguerra. Compressing and querying integer dictionaries under linearities and repetitions. IEEE Access, 2022.

PDF DOI Block-$ε$ tree code LZ$_ε$ code

Antonio Boffa, Paolo Ferragina, Francesco Tosoni, Giorgio Vinciguerra. Compressed string dictionaries via data-aware subtrie compaction. SPIRE, 2022.

Code DOI PDF Submitted version

Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo. Standard versus uniform binary search and their variants in learned static indexing: The case of the searching on sorted data benchmarking software platform. Software: Practice and Experience, 2022.

Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo. Learned Sorted Table Search and Static Indexes in Small Model Space. AIxIA, 2022.

Domenico Amato, Giosuè Lo Bosco, Raffaele Giancarlo. On the Suitability of Neural Networks as Building Blocks for the Design of Efficient Learned Indexes. EANN, 2022.

Paolo Ferragina, Giovanni Manzini, Travis Gagie, Dominik Köppl, Gonzalo Navarro, Manuel Striani, Francesco Tosoni. Improving Matrix Vector Multiplication via Lossless Grammar Compressed Matrices. PVLDB, 15(10), 2022.

Mariella Bonomo, Raffaele Giancarlo, Daniele Greco, Simona E. Rombo. Topological ranks reveal functional knowledge encoded in biological networks: a comparative analysis. Briefings in Bioinformatics, 2022.

Antonio Boffa, Paolo Ferragina, Giorgio Vinciguerra. A learned approach to design compressed rank/select data structures. ACM Trans. Algorithms, 2022.

PDF Code DOI Experiments code & datasets

Antonio Fariña, Travis Gagie, Szymon Grabowski, Giovanni Manzini, Gonzalo Navarro, Alberto Ordóñez. Efficient and compact representations of some non-canonical prefix-free codes. Theor. Comput. Sci., 2022.

Giacomo Fumagalli, Davide Raimondi, Raffaele Giancarlo, Dario Malchiodi, Marco Frasca. On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters. ICPRAM, 2022.

Giuseppe Cattaneo, Umberto Ferraro Petrillo, Raffaele Giancarlo, Francesco Palini, Chiara Romualdi. The power of word-frequency-based alignment-free functions: a comprehensive large-scale experimental analysis. Bioinformatics, 2021.

Paolo Ferragina, Giovanni Manzini, Giorgio Vinciguerra. Repetition- and linearity-aware rank/select dictionaries. ISAAC, 2021.

Travis Gagie, Garance Gourdel, Giovanni Manzini. Compressing and Indexing Aligned Readsets. WABI, 2021.

Lavinia Egidi, Felipe A. Louza, Giovanni Manzini. Space Efficient Merging of de Bruijn Graphs and Wheeler Graphs. Algorithmica, 2021.

Ylenia Galluzzo, Raffaele Giancarlo, Mario Randazzo, Simona E. Rombo. Burrows Wheeler Transform on a Large Scale: Algorithms Implemented in Apache Spark. 2021.

Filippo Geraci, Giovanni Manzini. EZcount: An all-in-one software for microRNA expression quantification from NGS sequencing data. Computers in Biology and Medicine, 2021.

Paolo Ferragina, Fabrizio Lillo, Giorgio Vinciguerra. On the performance of learned data structures. Theor. Comput. Sci., 2021.

Christina Boucher, Travis Gagie, Tomohiro I, Dominik Köppl, Ben Langmead, Giovanni Manzini, Gonzalo Navarro, Alejandro Pacheco, Massimiliano Rossi. PHONI: Streamed Matching Statistics with Multi-Genome References. DCC, 2021.

Marco Oliva, Massimiliano Rossi, Jouni Sirén, Giovanni Manzini, Tamer Kahveci, Travis Gagie, Christina Boucher. Efficiently merging $r$-indexes. DCC, 2021.

Umberto Ferraro Petrillo, Francesco Palini, Giuseppe Cattaneo, Raffaele Giancarlo. FASTA/Q data compressors for MapReduce-Hadoop genomics: space and time savings made easy. BMC Bioinformatics, 2021.

Paolo Ferragina, Giorgio Vinciguerra. Learning Based Compressed Data Structures (Poster). Stanford Compression Workshop, 2021.

Poster Abstract PDF

Umberto Ferraro Petrillo, Francesco Palini, Giuseppe Cattaneo, Raffaele Giancarlo. Alignment-Free Genomic Analysis via a Big Data Spark Platform. Bioinformatics, 2021.

Giosuè Cataldo Marinò, Gregorio Ghidoli, Marco Frasca, Dario Malchiodi. Compression Strategies and Space Conscious Representations for Deep Neural Networks. ICPR, 2021.

Giosuè Cataldo Marinò, Gregorio Ghidoli, Marco Frasca, Dario Malchiodi. Reproducing the sparse Huffman Address Map compression for deep neural networks. RRPR, 2021.

PDF Code Slides Video DOI

Christina Boucher, Ondřej Cvacho, Travis Gagie, Jan Holub, Giovanni Manzini, Gonzalo Navarro, Massimiliano Rossi. PFP Compressed Suffix Trees. ALENEX, 2021.

Antonio Boffa, Paolo Ferragina, Giorgio Vinciguerra. A “learned” approach to quicken and compress rank/select dictionaries. ALENEX, 2021.

PDF Code DOI Experiments code & datasets

Simona E. Rombo, Domenico Ursino. Integrative bioinformatics and omics data source interoperability in the next-generation sequencing era—Editorial. Briefings in Bioinformatics, 2021.

Mariella Bonomo, Armando La Placa, Simona E. Rombo. Identifying the $k$ Best Targets for an Advertisement Campaign via Online Social Networks. KDIR, 2020.

Travis Gagie, Tomohiro I, Giovanni Manzini, Gonzalo Navarro, Hiroshi Sakamoto, Louisa Seelbach Benkner, Yoshimasa Takabatake. Practical Random Access to SLP-Compressed Texts. SPIRE, 2020.

Domenico Amato, Giosuè Lo Bosco, Riccardo Rizzo. CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification. BMC Bioinformatics, 2020.

Mariella Bonomo, Armando La Placa, Simona E. Rombo. Prediction of lncRNA-disease associations from tripartite graphs. DMAH, 2020.

Mario Randazzo, Simona E. Rombo. A Big Data Approach for Sequences Indexing on the Cloud via Burrows Wheeler Transform. AAI4H, 2020.

Paolo Ferragina, Fabrizio Lillo, Giorgio Vinciguerra. Why are learned indexes so effective?. ICML, 2020.

PDF Code Slides Video

Paolo Ferragina, Giorgio Vinciguerra. The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds. PVLDB, 13(8), 2020.

PDF Code Project Slides Video DOI

Alan Kuhnle, Taher Mun, Christina Boucher, Travis Gagie, Ben Langmead, Giovanni Manzini. Efficient Construction of a Complete Index for Pan-Genomics Read Alignment. Journal of Computational Biology 27:4, 2020.

Raffaele Giancarlo, Giovanni Manzini, Antonio Restivo, Giovanna Rosone, Marinella Sciortino. The Alternating BWT: An algorithmic perspective. Theor. Comput. Sci., 812, 2020.

Lavinia Egidi, Giovanni Manzini. Lightweight merging of compressed indices based on BWT variants. Theor. Comput. Sci., 812, 2020.

Paolo Ferragina, Giorgio Vinciguerra. Learned data structures. Oneto L., Navarin N., Sperduti A., Anguita D. (eds) Recent Trends in Learning From Data. Studies in Computational Intelligence, vol 896. Springer, 2020.

Travis Gagie, Tomohiro I, Giovanni Manzini, Gonzalo Navarro, Hiroshi Sakamoto, Yoshimasa Takabatake. Rpair: Rescaling RePair with Rsync. SPIRE, 2019.

Raffaele Giancarlo, Giovanni Manzini, Giovanna Rosone, Marinella Sciortino. A New Class of Searchable and Provably Highly Compressible String Transformations. CPM, 2019.

Raffaele Giancarlo, Simona E. Rombo, Filippo Utro. DNA combinatorial messages and Epigenomics: The case of chromatin organization and nucleosome occupancy in eukaryotic genomes. Theor. Comput. Sci., 792, 2019.

Umberto Ferraro Petrillo, Mara Sorella, Giuseppe Cattaneo, Raffaele Giancarlo, Simona E. Rombo. Analyzing big datasets of genomic sequences: fast and scalable collection of $k$-mer statistics. BMC Bioinformatics 20, 138, 2019.