Deep Genomics and Proteomics: Language Model-Based Embedding of Biological Sequences and Their Applications in Bioinformatics

Author:

Asgari Ehsaneddin,Mofrad Mohammad R.K.

Publisher

Elsevier

Reference45 articles.

1. Continuous distributed representation of biological sequences for deep proteomics and genomics;Asgari;PLoS One,2015

2. Comparing fifty natural languages and twelve genetic languages using word embedding language divergence (WELD) as a quantitative measure of language distance;Asgari,2016

3. Representation learning: a review and new perspectives;Bengio;IEEE Trans. Pattern Anal. Mach. Intell.,2013

4. Phylogenetic grammar induction;Berg-Kirkpatrick,2010

5. Global discriminative learning for higher-accuracy computational gene prediction;Bernal;PLoS Comput. Biol.,2007

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