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Deciphering the Language of Nature: A transformer-based language model
  for deleterious mutations in proteins

Deciphering the Language of Nature: A transformer-based language model for deleterious mutations in proteins

27 October 2021
Theodore Jiang
Li Fang
Kai Wang
    MedIm
ArXivPDFHTML

Papers citing "Deciphering the Language of Nature: A transformer-based language model for deleterious mutations in proteins"

4 / 4 papers shown
Title
ALPHAGMUT: A Rationale-Guided Alpha Shape Graph Neural Network to
  Evaluate Mutation Effects
ALPHAGMUT: A Rationale-Guided Alpha Shape Graph Neural Network to Evaluate Mutation Effects
Boshen Wang
Bowei Ye
Lin Xu
Jie Liang
19
0
0
13 Jun 2024
On The Computational Complexity of Self-Attention
On The Computational Complexity of Self-Attention
Feyza Duman Keles
Pruthuvi Maheshakya Wijewardena
C. Hegde
47
107
0
11 Sep 2022
Tranception: protein fitness prediction with autoregressive transformers
  and inference-time retrieval
Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval
Pascal Notin
M. Dias
J. Frazer
Javier Marchena-Hurtado
Aidan N. Gomez
D. Marks
Y. Gal
53
172
0
27 May 2022
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,435
0
26 Sep 2016
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