Repeated patterns detection in big data using classification and parallelism on LERP Reduced Suffix Arrays

Xylogiannopoulos, Konstantinos F.; Karampelas, Panagiotis; Alhajj, Reda

doi:10.1007/s10489-016-0766-2

Cited by 27 publications

(11 citation statements)

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“…The approaches on biological problems, which they will be described in the next sections of the paper, are applications of the Longest Expected Repeated Pattern Reduced Suffix Array (LERP-RSA) data structure [26], [27], [28] and the related family of algorithms such as ARPaD, SPaD and MPaD that are specifically designed for the LERP-RSA [27], [28]. Several applications of the aforementioned data structure and algorithms will be presented, as a pipeline of execution, that can either extract useful information directly from the dataset or the results generated, or can be used as an input for other type of meta analytics in biological sequences.…”

Section: Proposed Approachesmentioning

confidence: 99%

“…Although this type of data structure can have quadratic space complexity, which was one of the first disadvantage to bypass, with the use of the LERP reduction the data structure space complexity can be optimized to log-linear with regard to the input string. This has been proved with the Probabilistic Existence of Longest Expected Repeated Pattern Theorem [27], [28] that can be briefly stated as follows:…”

Section: A Lerp-rsa Data Structurementioning

confidence: 99%

“…The theorem builds us the necessary foundation to calculate the longest expected repeated pattern given a very small probability that a repeated pattern exists with longer length. Therefore, the length of the suffix strings used to create the LERP-RSA, can be reduced significantly by using the following, briefly stated, Lemma [27], [28]:…”

Section: A Lerp-rsa Data Structurementioning

confidence: 99%

“…The abovementioned Lemma is directly inducted from the Theorem and it has been proven in [27], [28]. Of course, the calculation of the longest repeated pattern can be performed by other methods, however, the use of the Lemma has some advantages since, e.g., building the suffix tree and determining the longest repeated pattern of a string on the suffix tree is a heavy computational process and in most of the cases it is impossible because of the string size.…”

Section: A Lerp-rsa Data Structurementioning

confidence: 99%

“…In order to achieve such results, the Multivariate Longest Expected Repeated Pattern Reduced Suffix Array (LERP-RSA) data structure will be used in combination with the All Repeated Patterns Detection (ARPaD) algorithm [26], [27], [28]. In brief LERP-RSA is a variation of the standard Suffix Array [25] data structure using though the actual, lexicographically sorted, suffix strings.…”

Section: Introductionmentioning

confidence: 99%

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Pattern Detection in Multiple Genome Sequences with Applications: The Case of All SARS-CoV-2 Complete Variants

Xylogiannopoulos

2021

Preprint

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Pattern detection and string matching are fundamental problems in computer science and the accelerated expansion of bioinformatics and computational biology have made them a core topic for both disciplines. The SARS-CoV-2 pandemic has made such problems more demanding with hundreds or thousands of new genome variants discovered every week, because of constant mutations, and the need for fast and accurate analyses. Medicines and, mostly, vaccines must be altered to adapt and efficiently address mutations. The need of computational tools for genomic analysis, such as sequence alignment, is very important, although, in most cases the resources and computational power needed is vast. The presented data structures and algorithms, specifically built for text mining and pattern detection, can help to address efficiently several bioinformatics problems. With a single execution of advanced algorithms, with limited space and time complexity, it is possible to acquire knowledge on all repeated patterns that exist in multiple genome sequences and this information can be used for further meta analyses. The potentials of the presented solutions are demonstrated with the analysis of more than 55,000 SARS-CoV-2 genome sequences (collected on March 10, 2021) and the detection of all repeated patterns with length up to 60 nucleotides in these sequences, something practically impossible with other algorithms due to its complexity. These results can be used to help provide answers to questions such as all variants common patterns, sequence alignment, palindromes and tandem repeats detection, genome comparisons, etc.

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Section: Proposed Approachesmentioning

confidence: 99%

Section: A Lerp-rsa Data Structurementioning

confidence: 99%

Section: A Lerp-rsa Data Structurementioning

confidence: 99%

Section: A Lerp-rsa Data Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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