
Полина Лунина
Публикации
Improved Architecture of Artificial Neural Network for Secondary Structure Analysis
Ноябрь 2019
Semyon Grigorev and Polina Lunina
The Composition of Dense Neural Networks and Formal Grammars for Secondary Structure Analysis
Март 2019
Semyon Grigorev and Polina Lunina
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 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.