Auto-Encoding Amino Acid Sequences with LSTM – Markus PROMBERGER
Markus PROMBERGER
Bachelor's thesis
Auto-Encoding Amino Acid Sequences with LSTM
Auto-Encoding Amino Acid Sequences with LSTM
Abstract:
In this thesis a sequence to sequence autoencoder for amino acid sequences is constructed. The latent representation of the autoencoder is then used to classify the amino acid sequences according to their animal kingdom. The data consists of sequences from three different kingdoms, mammals, fish and birds. The thesis includes the preprocessing necessary for the data, the construction of the sequence …moreAbstract:
In this thesis a sequence to sequence autoencoder for amino acid sequences is constructed. The latent representation of the autoencoder is then used to classify the amino acid sequences according to their animal kingdom. The data consists of sequences from three different kingdoms, mammals, fish and birds. The thesis includes the preprocessing necessary for the data, the construction of the sequence …more
Language used: English
Date on which the thesis was submitted / produced: 8. 3. 2022
Thesis defence
- Supervisor: prof. Dr. Sepp Hochreiter
Citation record
ISO 690-compliant citation record:
PROMBERGER, Markus. \textit{Auto-Encoding Amino Acid Sequences with LSTM}. Online. Bachelor's thesis. České Budějovice: University of South Bohemia in České Budějovice, Faculty of Science. 2022. Available from: https://theses.cz/id/blj2u9/.
The right form of listing the thesis as a source quoted
PROMBERGER, Markus. Auto-Encoding Amino Acid Sequences with LSTM. České Budějovice, 2022. bakalářská práce (Bc.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta
Full text of thesis
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Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH, Přírodovědecká fakultaUNIVERSITY OF SOUTH BOHEMIA IN ČESKÉ BUDĚJOVICE
Faculty of ScienceBachelor programme / field:
Applied Informatics / Bioinformatics
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