We propose a way to combine formal grammars and artificial neural networks for biological sequences processing. Formal grammars encode the secondary structure of the sequence and neural networks deal with mutations and noise. In contrast to the classical way, when probabilistic grammars are used for secondary structure modeling, we propose to use arbitrary (not probabilistic) grammars which simplifies grammar creation. Instead of modeling the structure of the whole sequence, we create a grammar which only describes features of the secondary structure. Then we use undirected matrix-based parsing to extract features: the fact that some substring can be derived from some nonterminal is a feature. After that, we use a dense neural network to process features. In this paper, we describe in details all the parts of our receipt: a grammar, parsing algorithm, and network architecture. We discuss possible improvements and future work. Finally, we provide the results of tRNA and 16s rRNA processing which shows the applicability of our idea to real problems.

Язык оригиналаанглийский
Название основной публикацииBIOINFORMATICS 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
РедакторыElisabetta De Maria, Hugo Gamboa, Ana Fred
ИздательSciTePress
Страницы234-241
Число страниц8
ISBN (электронное издание)9789897583537
СостояниеОпубликовано - 1 янв 2019
Событие10th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019 - Prague, Чехия
Продолжительность: 22 фев 201924 фев 2019

конференция

конференция10th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019
Страна/TерриторияЧехия
ГородPrague
Период22/02/1924/02/19

    Предметные области Scopus

  • Биомедицинская техника
  • Электротехника и электроника

ID: 48534701