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    From Discrete to Continuous: Turing's Morphogenesis

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    DNA Computing: a survey

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    A dynamic programming algorithm for Haplotype Asembly of Future-Generation Sequencing Reads

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    Invited talk on Algorithmic Methods for Haplotype Assembl

    Segment-based distances and similarities in genomic sequences

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    We address some problems arising in the analysis and representation of genomic data. The thesis is divided in two parts. Part~I contains studies on large scale mutations of genomes with particular attention to gene duplications. We prove some results on genomic syntenic distance, and investigate some properties of families of paralogous genes. These latter can also form a ground for genome comparisons. Part~II contains some studies on motif extraction which role in molecular biology is crucial for building genome maps and for many other applications at structures and similarities in biological sequences

    Bioinformatica

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    Le equazioni della natura

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    Uno sguardo sulla fisica del vivente radicalmente nuovo, capace di cogliere le dinamiche del continuo. È l’ultimo, coraggioso contributo di Turing alla scienza moderna

    DNA computing: a new computational paradigm using molecules

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    DNA computing appeared in the literature in 1994 when Leonard Adleman suggested to solve an NP-complete problem by using DNA molecules. Since one can store a large amount of molecules in a small volume, and since it is possible to apply operations to all of them in parallel, the result is a surprisingly interesting performance of DNA computations. In recent years, possible computationally complete models that might be implemented in a molecular biology laboratory have been suggested. Experiments are being performed in order to test the feasibility of DNA computations by using such models. We will report on some of the ideas, discussions, and results that have appeared in the literature so far, and we will stress some new issues in DNA computing that suggest a revisitation of complexity theory

    On-Line Pattern Matching on D-Texts (Invited Talk)

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    The Elastic Degenerate String Matching (EDSM) problem is defined as that of finding an occurrence of a pattern P of length m in an ED-text T. A D-text (Degenerate text) is a string that actually represents a set of similar and aligned strings (e.g. a pan-genome [The Computational Pan-Genomics Consortium, 2018]) by collapsing common fragments into a standard string, and representing variants with sets of alternative substrings. When such substrings are not bound to have the same size, then we talk about elastic D-strings (ED-strings). In [R.Grossi et al., 2017] we gave an O(nm²+N) time on-line algorithm for EDSM, where n is the length of T and N is its size, defined as the total number of letters. A fundamental toolkit of our algorithm is the O(m²+N) time solution of the later called Active Prefixes problem (AP). In [K.Aoyama et al., 2018], a O(m^{1.5} √{log m}+N) solution for AP was shown, leading to a O(nm^{1.5} √{log m}+N) time solution for EDSM. The natural open problem was thus whether the 1.5 exponent could furtherly be decreased. In [G.Bernardini et al., 2019], we prove several properties that answer this and other questions: we give a conditional O(nm^{1.5}+N) lower bound for EDSM, proving that a combinatorial algorithm solving EDSM in O(nm^{1.5-ε} +N) time would break the Boolean Matrix Multiplication (BMM) conjecture; we use this result as a hint to devise a non-combinatorial algorithm that solves EDSM in O(nm^{1.381}+N) time; we do so by successfully combining Fast Fourier Transform and properties of string periodicity. In my talk I will overview the results above, as well as some interesting side results: the extension to a dictionary rather than a single pattern [S.P.Pissis and A.Retha, 2018], the introduction of errors [G.Bernardini et al., 2020], and a notion of matching among D-strings with its linear time solution [M.Alzamel et al., 2020]

    BubbleBlower

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    Software per l'enumerazione di "bubble", ovvero coppie di cammini node-disjoint in grafi orientati
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