2D regular expressions represent rational relations over two alphabets Σ and Δ. In standard 2D expressions (S2D-RE) the basic terms are generators of Σ⋆×Δ⋆, while in generalised 2D expressions (2D-RE) the basic terms are pairs of (ordinary) regular expressions over one alphabet (1D). In this paper we study the average state complexity of partial derivative standard transducers (TPD) for both S2D-RE and 2D-RE. For S2D-RE we obtain the same asymptotic bounds as for partial derivative automata. For 2D-RE, while in the worst case the number of states of TPD can be O(n2), where n is the size of the expression, asymptotically and on average that value is bounded from above by O(n32). We also show that asymptotically and on average the alphabetic size of a 2D-RE is half of its size. All results are obtained in the framework of analytic combinatorics considering generating functions of parametrised combinatorial classes defined implicitly by algebraic curves. In particular, we generalise the methods developed in previous work to a broad class of analytic functions.

BACKGROUND: Studies exploring the potential of Chaos Game Representations (CGR) of genomic sequences to act as "genomic signatures" (to be species- and genome-specific) showed that CGR patterns of nuclear and organellar DNA sequences of the same organism can be very different. While the hypothesis that CGRs of mitochondrial DNA sequences can act as genomic signatures was validated for a snapshot of all sequenced mitochondrial genomes available in the NCBI GenBank sequence database, to our knowledge no such extensive analysis of CGRs of nuclear DNA sequences exists to date. RESULTS: We analyzed an extensive dataset, totalling 1.45 gigabase pairs, of nuclear/nucleoid genomic sequences (nDNA) from 42 different organisms, spanning all major kingdoms of life. Our computational experiments indicate that CGR signatures of nDNA of two different origins cannot always be differentiated, especially if they originate from closely-related species such as H. sapiens and P. troglodytes or E. coli and E. fergusonii. To address this issue, we propose the general concept of additive DNA signature of a set (collection) of DNA sequences. One particular instance, the composite DNA signature, combines information from nDNA fragments and organellar (mitochondrial, chloroplast, or plasmid) genomes. We demonstrate that, in this dataset, composite DNA signatures originating from two different organisms can be differentiated in all cases, including those where the use of CGR signatures of nDNA failed or was inconclusive. Another instance, the assembled DNA signature, combines information from many short DNA subfragments (e.g., 100 basepairs) of a given DNA fragment, to produce its signature. We show that an assembled DNA signature has the same distinguishing power as a conventionally computed CGR signature, while using shorter contiguous sequences and potentially less sequence information. CONCLUSIONS: Our results suggest that, while CGR signatures of nDNA cannot always play the role of genomic signatures, composite and assembled DNA signatures (separately or in combination) could potentially be used instead. Such additive signatures could be used, e.g., with raw unassembled next-generation sequencing (NGS) read data, when high-quality sequencing data is not available, or to complement information obtained by other methods of species identification or classification.

BACKGROUND: Motivated by the general need to identify and classify species based on molecular evidence, genome comparisons have been proposed that are based on measuring mostly Euclidean distances between Chaos Game Representation (CGR) patterns of genomic DNA sequences. RESULTS: We provide, on an extensive dataset and using several different distances, confirmation of the hypothesis that CGR patterns are preserved along a genomic DNA sequence, and are different for DNA sequences originating from genomes of different species. This finding lends support to the theory that CGRs of genomic sequences can act as graphic genomic signatures. In particular, we compare the CGR patterns of over five hundred different 150,000 bp genomic sequences spanning one complete chromosome from each of six organisms, representing all kingdoms of life: H. sapiens (Animalia; chromosome 21), S. cerevisiae (Fungi; chromosome 4), A. thaliana (Plantae; chromosome 1), P. falciparum (Protista; chromosome 14), E. coli (Bacteria - full genome), and P. furiosus (Archaea - full genome). To maximize the diversity within each species, we also analyze the interrelationships within a set of over five hundred 150,000 bp genomic sequences sampled from the entire aforementioned genomes. Lastly, we provide some preliminary evidence of this method's ability to classify genomic DNA sequences at lower taxonomic levels by comparing sequences sampled from the entire genome of H. sapiens (class Mammalia, order Primates) and of M. musculus (class Mammalia, order Rodentia), for a total length of approximately 174 million basepairs analyzed. We compute pairwise distances between CGRs of these genomic sequences using six different distances, and construct Molecular Distance Maps, which visualize all sequences as points in a two-dimensional or three-dimensional space, to simultaneously display their interrelationships. CONCLUSION: Our analysis confirms, for this dataset, that CGR patterns of DNA sequences from the same genome are in general quantitatively similar, while being different for DNA sequences from genomes of different species. Our assessment of the performance of the six distances analyzed uses three different quality measures and suggests that several distances outperform the Euclidean distance, which has so far been almost exclusively used for such studies.

A (combinatorial) channel consists of pairs of words representing all possible input-output channel situations. In a past paper, we formalized the intuitive concept of “largest amount of errors” detectable by a given language L, by defining the maximal error-detecting capabilities of L with respect to a given class of channels, and we showed how to compute all maximal error-detecting capabilities (channels) of a given regular language with respect to the class of rational channels and a class of channels involving only the substitution-error type. In this paper we resolve the problem for channels involving any combination of the basic error types: substitution, insertion, deletion. Moreover, we consider the problem of finding the inverses of these channels, in view of the fact that L is error-detecting for γ if and only if it is error-detecting for the inverse of γ. We also discuss a natural method of reducing the problem of computing (inner) distances of a given regular language L to the problem of computing maximal error-detecting capabilities of L.

The edit distance (or Levenshtein distance) between two words is the smallest number of substitutions, insertions, and deletions of symbols that can be used to transform one of the words into the other. In this paper we consider the problem of computing the edit distance of a regular language (also known as constraint system), that is, the set of words accepted by a given finite automaton. This quantity is the smallest edit distance between any pair of distinct words of the language. We show that the problem is of polynomial time complexity. We distinguish two cases depending on whether the given automaton is deterministic or nondeterministic. In the latter case the time complexity is higher.

We investigate the problem of designing pairs (p,s) of words with the property that, if each word of a coded message is prefixed by p and suffixed by s, the resulting set of coded messages is error detecting with finite delay. We consider (combinatorial) channels permitting any combination of the substitution, insertion, and deletion (SID) error types, and address the cases of both scattered and burst errors. A pair (p,s) with the above property is evaluated in terms of three parameters: redundancy, delay of decoding, and frequency of the detectable errors. In the case of SID channels with burst errors, we provide a complete and explicit characterization of their error-detecting pairs (p,s), which involves the period of the word sp.

SID channels are discrete channels represented by expressions that involve combinations of the error types substitution, insertion, and deletion. In this correspondence, a simple distance is defined that generalizes the Hamming and Levenshtein distances. For a certain class of SID channels, the distance is used to obtain a necessary and sufficient condition for the error-correcting capability that corresponds to the channel in question. Moreover, it is shown that for many SID channels whose expressions include the insertion type, their error-correcting codes coincide with those for SID channels whose expressions result by replacing the insertion type with the deletion type.

A nonprobabilistic mathematical model is introduced of discrete channels that involve the error types substitution, insertion, and deletion. The model is based on the novelty that errors can be expressed as strings over an alphabet of basic error symbols. Some general conditions on errors are defined which bound the error effects on messages, obtaining thus the class of bounded error effects channels (BEE channels). These channels can be used to model, for instance, scattered errors and bursts of errors of any combination of the three error types. A general notion of error-correcting code is defined and a characterization of the error-correcting codes for a given BEE channel is obtained. Then, an algorithm is presented that tests, for a given finite code (not necessarily of fixed length) and a given description of a BEE channel, whether the code is error-correcting for the channel defined by the given description. This result can be considered as an extension of the well-known theorem of Sardinas and Patterson (1953) for testing the unique decodability of a given finite code. In this sense, it can be said that unique decodability is decidable also in the presence of errors.