Oct 5, 2020 · In this work, we propose a deep Encoder-Decoder model to learn unified representation of biological sequences. It combines the advantages of pre ...
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Oct 2, 2020 · A Unified Deep Biological Sequence Representation Learning with Pretrained Encoder-Decoder Model. Authors: Author Picture Hai-Cheng Yi.
Oct 2, 2020 · A Unified Deep Biological Sequence Representation Learning with Pretrained Encoder-Decoder Model. October 2020. October 2020. DOI:10.1007/978-3 ...
BioSeq2vec: learning deep representation of biological sequences using LSTM Encoder-Decoder - haichengyi/bioseq2vec.
May 28, 2021 · The model is first pretrained with DNA sequences from other cell lines, where feature information was extracted from other sequences, and then ...
Apr 20, 2024 · Our model combines both GNNs and ESM to encode the protein in a fused representation while a pretrained GPT-2 decodes the protein's text ...
... sequence-based deep representation learning. Nat ... DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome.
Particularly, the successful encoding of words via representation learning has been recognized as an essential research area because the performance of NLP and ...
Feb 27, 2021 · In particular, the successful encoding of words via representation learning has been recognized as an essential research area because the ...
May 10, 2024 · Our unified framework decomposes medical coding into four main components, i.e., encoder modules for text feature extraction, mechanisms for ...