Publications

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Publications listed by type


Journal papers ↑

  1. MetaProb 2: Metagenomic Reads Binning Based on Assembly Using Minimizers and K-Mers Statistics
    Francesco Andreace, Cinzia Pizzi and Matteo Comin. In Journal of Computational Biology, 28, 11, 1052-1062, 2021.

  2. K2Mem: Discovering Discriminative K-mers from Sequencing Data for Metagenomic Reads Classification
    Davide Storato and Matteo Comin. In IEEE/ACM Transactions on Computational Biology and Bioinformatics, , , 1-1, 2021.

  3. Fast Alignment of Reads to a Variation Graph with application to SNP Detection
    Maurilio Monsu and Matteo Comin. In Journal of Integrative Bioinformatics, , , 20210032, 2021.

  4. Comparison of microbiome samples: methods and computational challenges
    M. Comin, B. Di Camillo, C. Pizzi and F. Vandin. In Briefings in Bioinformatics, 22, 1, 88-95, 2021. (Impact Factor 5.4)

  5. Iterative Spaced Seed Hashing: Closing the Gap between Spaced Seed Hashing and k-mer Hashing
    E. Petrucci, L. Noé, C. Pizzi and M. Comin. In Journal of Computational Biology, 27, 2, 223-233, 2020.

  6. MetaCon: Unsupervised clustering of metagenomic contigs with probabilistic k-mers statistics and coverage
    J. Qian and M. Comin. In BMC Bioinformatics, 20, 2019. (Impact Factor 2.9)

  7. Better quality score compression through sequence-based quality smoothing
    Y. Shibuya and M. Comin. In BMC Bioinformatics, 20, 2019. (Impact Factor 2.9)

  8. Indexing k-mers in linear space for quality value compression
    Y. Shibuya and M. Comin. In Journal of Bioinformatics and Computational Biology, 17, 5, 2019.

  9. Benchmarking of alignment-free sequence comparison methods
    A. Zielezinski, H.Z. Girgis, G. Bernard, C.-A. Leimeister, K. Tang, T. Dencker, A.K. Lau, S. Röhling, J.J. Choi, M.S. Waterman, M. Comin, S.-H. Kim, S. Vinga, J.S. Almeida, C.X. Chan, B.T. James, F. Sun, B. Morgenstern and W.M. Karlowski. In Genome Biology, 20, 1, 2019. (Impact Factor 18.3)

  10. Efficient computation of spaced seed hashing with block indexing
    S. Girotto, M. Comin and C. Pizzi. In BMC Bioinformatics, 19, 2018. (Impact Factor 3.2)

  11. FSH: Fast spaced seed hashing exploiting adjacent hashes
    S. Girotto, M. Comin and C. Pizzi. In Algorithms for Molecular Biology, 13, 1, 2018. (Impact Factor 1.43)

  12. Fast and sensitive classification of short metagenomic reads with SKraken
    J. Qian, D. Marchiori and M. Comin. In Communications in Computer and Information Science, 881, 212-226, 2018.

  13. Higher recall in metagenomic sequence classification exploiting overlapping reads
    S. Girotto, M. Comin and C. Pizzi. In BMC genomics, 18, 917, 2017. (Impact Factor 3.7)

  14. Metagenomic reads binning with spaced seeds
    S. Girotto, M. Comin and C. Pizzi. In Theoretical Computer Science, 698, 88-99, 2017.

  15. Fast comparison of genomic and meta-genomic reads with alignment-free measures based on quality values
    M. Comin and M. Schimd. In BMC Medical Genomics, 9, 2016. (Impact Factor 2.72)

  16. On the comparison of regulatory sequences with multiple resolution Entropic Profiles
    M. Comin and M. Antonello. In BMC Bioinformatics, 17, 1, 2016. (Impact Factor 2.58)

  17. Clustering of reads with alignment-free measures and quality values
    M. Comin, A. Leoni and M. Schimd. In Algorithms for Molecular Biology, 10, 1, 2015. (Impact Factor 1.61)

  18. Parallel continuous flow: A parallel suffix tree construction tool for whole genomes
    M. Comin and M. Farreras. In Journal of Computational Biology, 21, 4, 330-344, 2014. (Impact Factor 1.67)

  19. Fast entropic profiler: An informationtheoretic approach for the discovery of patterns in genomes
    M. Comin and M. Antonello. In IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11, 3, 500-509, 2014. (Impact Factor 1.7)

  20. Filtering degenerate patterns with application to protein sequence analysis
    M. Comin and D. Verzotto. In Algorithms, 6, 2, 352-370, 2013.

  21. Ultrametric networks: A new tool for phylogenetic analysis
    A. Apostolico, M. Comin, A. Dress and L. Parida. In Algorithms for Molecular Biology, 8, 1, 2013. (Impact Factor 1.61)

  22. Fast computation of entropic profiles for the detection of conservation in genomes
    M. Comin and M. Antonello. In Proceedings of Pattern Recognition in Bioinformatics 2013, Lecture Notes in BIoinformatics (LNBI), 7986 LNBI, 277-288, 2013.

  23. Alignment-free phylogeny of whole genomes using underlying subwords
    M. Comin and D. Verzotto. In Algorithms for Molecular Biology, 7, 1, 2012. (Impact Factor 1.61)

  24. The irredundant class method for remote homology detection of protein sequences
    M. Comin and D. Verzotto. In Journal of Computational Biology, 18, 12, 1819-1829, 2011. (Impact Factor 1.86)

  25. VARUN: Discovering extensible motifs under saturation constraints
    A. Apostolico, M. Comin and L. Parida. In IEEE/ACM Transactions on Computational Biology and Bioinformatics, 7, 4, 752-762, 2010. (Impact Factor 2.1)

  26. Binding balls: fast detection of binding sites using a property of spherical Fourier transform.
    M. Comin, C. Guerra and F. Dellaert. In Journal of computational biology : a journal of computational molecular cell biology, 16, 11, 1577-1591, 2009. (Impact Factor 1.7)

  27. Mining overrepsented 3d patterns of secondary structures in proteins
    M. Comin, C. Guerra and G. Zanotti. In Journal of Bioinformatics and Computational Biology, 6, 6, 1067-1087, 2008. (Impact Factor 1.3)

  28. Algorithmic re-structuring and data replication for protein structure comparison on a GRID
    G. Ciriello, M. Comin and C. Guerra. In Future Generation Computer Systems, 23, 3, 391-397, 2007. (Impact Factor 1.86)

  29. Mining, compressing and classifying with extensible motifs
    A. Apostolico, M. Comin and L. Parida. In Algorithms for Molecular Biology, 1, 1, 2006. (Impact Factor 1.61)

  30. Bridging Lossy and Lossless Compression by Motif Pattern Discovery
    A. Apostolico, M. Comin and L. Parida. In Electronic Notes in Discrete Mathematics, 21, 219-225, 2005.

  31. PROuST: A comparison method of three-dimensional structures of proteins using indexing techniques
    M. Comin, C. Guerra and G. Zanotti. In Journal of Computational Biology, 11, 6, 1061-1072, 2004. (Impact Factor 3.78)

  32. Grid deployment of bioinformatics applications: A case study in protein similarity determination
    M. Comin, C. Ferrari and C. Guerra. In Parallel Processing Letters, 14, 2, 163-176, 2004.

Conference papers ↑

  1. Boosting Metagenomic Classification with Reads Overlap Graphs
    M. Cavattoni and M. Comin. In Bioinformatics Research and Applications, 521–533, 2021.

  2. Indexing K-mers in Linear Space with Application to SNP Detection
    F. Andreace, M. Marcolin and M. Comin. In Annual Meeting of the Bioinformatics Italian Society, BITS 2021, 2021.

  3. Fast Alignment of Reads to a Variation Graph with application to SNP Detection
    M. Monsu and M. Comin. In International Applied Bioinformatics Conference (iABC ’21), 2021.

  4. Improving Metagenomic Classification Using Discriminative k-mers from Sequencing Data
    D. Storato and M. Comin. In In Proceedings of the 16th International Symposium on Bioinformatics Research and Applications. Lecture Notes in Bioinformatics, 12304 LNBI : 68-81, 2020.

  5. Indexing k-mers in linear-space for quality value compression
    Y. Shibuya and M. Comin. In BIOINFORMATICS 2019 - 10th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019, 21-29, 2019.

  6. Iterative Spaced Seed Hashing: Closing the Gap Between Spaced Seed Hashing and k-mer Hashing
    E. Petrucci, L. Noé, C. Pizzi and M. Comin. In In Proceedings of the 15th International Symposium on Bioinformatics Research and Applications. Lecture Notes in Bioinformatics, 11490 LNBI : 208-219, 2019.

  7. Data-driven smart bike-sharing system by implementing machine learning algorithms
    J. Qian, L. Pianura and M. Comin. In Proceedings - 2018 6th International Conference on Enterprise Systems, ES 2018, 50-55, 2018.

  8. Better quality score compression through sequence-based quality smoothing
    Y. Shibuya and M. Comin. In 15th Annual Meeting of the Bioinformatics Italian Society, 2018. abstract

  9. Binning metagenomic reads with probabilistic sequence signatures based on spaced seeds
    S. Girotto, M. Comin and C. Pizzi. In 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017, 2017.

  10. Fast spaced seed hashing
    S. Girotto, M. Comin and C. Pizzi. In 17th International Workshop on Algorithms in Bioinformatics (WABI 2017). Leibniz International Proceedings in Informatics, LIPIcs, 88 2017.

  11. SKraken: Fast and sensitive classification of short metagenomic reads based on filtering uninformative k-mers
    D. Marchiori and M. Comin. In BIOINFORMATICS 2017 - 8th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017, 3 : 59-67, 2017.

  12. Higher recall in metagenomic sequence classification exploiting Overlapping Reads
    S. Girotto, M. Comin and C. Pizzi. In IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2016, 2016.

  13. MetaProb: Accurate metagenomic reads binning based on probabilistic sequence signatures
    S. Girotto, C. Pizzi and M. Comin. In In Proceedings of 15th European Conference on Computational Biology 2016. Bioinformatics, 32 : i567-i575, 2016. (Impact Factor 5.76)

  14. Fast alignment-free comparison for regulatory sequences using multiple resolution entropic profiles
    M. Comin and M. Antonello. In BIOINFORMATICS 2015 - 6th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 8th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015, 172-177, 2015.

  15. Assembly-free genome comparison based on next-generation sequencing reads and variable length patterns
    M. Comin and M. Schimd. In Proceedings of the 4th Annual RECOMB Satellite Workshop at Massively Parallel Sequencing. BMC Bioinformatics, 15 2014. (Impact Factor 2.67)

  16. Beyond fixed-resolution alignment-free measures for mammalian enhancers sequence comparison
    M. Comin and D. Verzotto. In Proceeding of the 12-th Asia Pacific Bioinformatics Conference 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11 : 628-637, 2014. (Impact Factor 1.7)

  17. QCluster: Extending alignment-free measures with quality values for reads clustering
    M. Comin, A. Leoni and M. Schimd. In Proceedings of the 14th Workshop on Algorithms in Bioinformatics (WABI) 2014. Lecture Notes in Bioinformatics, 8701 LNBI : 1-13, 2014.

  18. Reducing the space of degenerate patterns in protein remote homology detection
    M. Comin and D. Verzotto. In Proceedings - International Workshop on Database and Expert Systems Applications, DEXA, 76-80, 2013.

  19. Efficient parallel construction of suffix trees for genomes larger than main memory
    M. Comin and M. Farreras. In Proceedings of the 20th European MPI 2013, ACM International Conference Proceeding Series, 211-216, 2013.

  20. Whole-genome phylogeny by virtue of unic subwords
    M. Comin and D. Verzotto. In Proceedings - International Workshop on Database and Expert Systems Applications, DEXA, 190-194, 2012.

  21. Classification of protein sequences by means of irredundant patterns
    M. Comin and D. Verzotto. In Proceedings of Asia-Pacific Bioinformatics Conference, 2010. BMC Bioinformatics, 11 2010. (accepted 28%, Impact Factor 3.02)

  22. Subtle motif discovery for detection of dna regulatory sites
    M. Comin and L. Parida. In Proceedings of Asia Pacific Bioinformatics Conference (APBC2007), Series on Advances in Bioinformatics and Computational Biology, 5 : 27-36, 2007. (accepted 17%)

  23. Mining over-represented 3D patterns of Secondary structures in proteins
    M. Comin, C. Guerra and G. Zanotti. In Proceedings of 7th International Workshop on Data Mining in Bioinformatics (BIOKDD ’07). ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 19-26, 2007. (accepted 25%)

  24. Application re-strusturing and data management on a GRID enviroment: A case study for bioinformatics
    G. Ciriello, M. Comin and C. Guerra. In 20th International Parallel and Distributed Processing Symposium, IPDPS, 2006 : 9, 2006.

  25. High-Performance Protein Structure Comparison
    G. Ciriello and M. Comin. In In Proceedings of RECOMB, 2006. abstract

  26. Conservative extraction of over-represented extensible motifs
    A. Apostolico, M. Comin and L. Parida. In Proceeding of the 13th Annual International conference on Intelligent Systems for Molecular Biology (ISMB 2005), Supplement of Bioinformatics, i9-i18, 2005. (accepted 13%, Impact Factor 6.02)

  27. Modelling a protein structure comparison application on the Grid using PROTEUS
    M. Cannataro, M. Comin, C. Ferrari, C. Guerra, A. Guzzo and P. Veltri. In SAG 2004, Lecture Notes in Computer Science, 3458 : 75-85, 2005.

  28. Motifs in Ziv-Lempel-Welch clef
    A. Apostolico, M. Comin and L. Parida. In Data Compression Conference Proceedings, 72-81, 2004. (accepted 20%)

  29. Off-line Compression by Extensible Motifs
    A. Apostolico, M. Comin and L. Parida. In Proceedings of IEEE DCC Data Compression Conference, Computer Society Press, 450, 2005.

Book chapters and invited contributions ↑

  1. Comin, M., & Schimd, M. (2017). Assembly-free techniques for NGS data. In Algorithms for Next-Generation Sequencing Data: Techniques, Approaches, and Applications (pp. 327–355). https://doi.org/10.1007/978-3-319-59826-0_14

  2. Comin, M., & Verzotto, D. (2015). Alignment-Free Measures for Whole-Genome Comparison. In Pattern Recognition in Computational Molecular Biology: Techniques and Approaches, edited by M. Elloumi, C. S. Iliopoulos, J.T.L. Wang and A.Y. Zomaya (pp. 43–64). https://doi.org/10.1002/9781119078845.ch3

  3. Comin, M., & Verzotto, D. (2013). Comparing ranking and filtering motifs with character classes: application to biological sequence analysis. In in Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data, edited by M. Elloumi and A. Y. Zomaya. Wiley.

  4. Comin, M., & Guerra, C. (2013). Protein Structure Comparison, High Performance Computing. In in Encyclopedia of System Biology, edited by W. Dubitzky, O. Wolkenhauer, K.H. Cho and H. Yokota. Springer.

  5. Comin, M., & Verzotto, D. (2010). Remote Homology Detection of Protein Sequences. In in Dagstuhl Proceedings 10231 "Structure Discovery in Biology: Motifs, Networks and Phylogenies (Vol. 2741).

  6. Comin, M., Guerra, C., & Zanotti, G. (2009). Invariant geometric properties of secondary structure elements in proteins. In Biological Data Mining, edited by J. Chen and S. Lonardi (pp. 27–48).

  7. Comin, M., & Parida, L. (2008). Detection of subtle variations as consensus motifs. In SAIL: String Algorithms, Information and Learning edited by R. Giancarlo and S. Lonardi. Theoretical Computer Science (Vol. 395, Numbers 2-3, pp. 158–170). https://doi.org/10.1016/j.tcs.2008.01.017

  8. Apostolico, A., Comin, M., & Parida, L. (2006). Bridging lossy and lossless compression by motif pattern discovery. In General Theory of Information Transfer and Combinatorics,Lecture Notes in Computer Science: Vol. 4123 LNCS (pp. 793–813). https://doi.org/10.1007/11889342_51

Patents ↑

  1. Method and apparatus for detection consensus motifs in data sequences
    L. Parida and M. Comin. 2008. United States Patent Application 20080167850, filed

  2. Methods and systems for conservative extraction of over-represented extensible motifs
    A. Apostolico, L. Parida and M. Comin. 2011. US Patent 7865313

  3. Method and structure for lossy compression of continuous data with extensible motifs
    L. Parida, A. Apostolico and M. Comin. 2007. US Patent 7259701