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Classification of Exon and Intron Boundaries

Milo B.

The goal was to accurately classify exon and intron boundaries based on DNA sequences. Scientists can learn more about proteins if divisions between exons and introns are clear. We used multiple different machine learning approaches including a logistic regression model, a multilayer perceptron, a LSTM, and a model that included a LSTM, autoencoder and a multilayer perceptron. LSTMs performed well, pointing to the idea that order of nucleotides is important when classifying DNA sequences.

The goal was to accurately classify exon and intron boundaries based on DNA sequences. Scientists can learn more about proteins if divisions between exons and introns are clear. We used multiple different machine learning approaches including a logistic regression model, a multilayer perceptron, a LSTM, and a model that included a LSTM, autoencoder and a multilayer perceptron. LSTMs performed well, pointing to the idea that order of nucleotides is important when classifying DNA sequences.

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Milo B.
Samuel Kwong

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