Conference
SMF: Approximate Algorithm for the Planted (l, d) Motif Finding Problem in DNA Sequences.
| Τίτλος: | SMF: Approximate Algorithm for the Planted (l, d) Motif Finding Problem in DNA Sequences. |
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| Συγγραφείς: | Al-Shaikhli, Hasnaa, de Doncker, Elise |
| Πηγή: | Proceedings of the International Conference on Bioinformatics & Computational Biology (BIOCOMP) (American Council on Science & Education); 2018, p123-129, 7p |
| Θεματικοί όροι: | Big data, Nucleotide sequencing, Prediction models, Nucleotide sequence, Electronic data processing, Simulation methods & models |
| Περίληψη: | Motif discovery is the problem of finding common substrings within a set of biological strings. Therefore, it can be applied to find Transcription Factors Binding Sites (TFBS) that have common patterns (motifs). The Planted (l; d) Motif Problem (PMP) is a classic version of motif discovery where l is the motif length and d represents the maximum allowed mutation distance. In this paper we present an approximate algorithm, Strong Motif Finder (SMF), to return the k highest ranked (strongest) motifs. We propose a scoring function, Motif Strength Score (MSS), which ranks the motifs discovered in the course of the SMF algorithm. We compare the performance of SMF with the APMotif and MEME algorithms with respect to execution time and prediction accuracy. We use several performance metrics at both the nucleotide and the site level. The algorithms are tested on simulated datasets, and results of SMF are also given for real DNA datasets of orthologous regularity regions from multiple species, without using their related phylogenetic tree. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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