Modeling aspects of the language of life through transfer-learning protein sequences

Modeling aspects of the language of life through transfer-learning protein sequences

Abstract Background Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning and evolutionary information. However, for some applications retrieving related proteins is becom...

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Bibliographic Details
Main Authors: Michael Heinzinger, Ahmed Elnaggar, Yu Wang, Christian Dallago, Dmitrii Nechaev, Florian Matthes, Burkhard Rost
Format: Article
Language:English
Published: BMC 2019-12-01
Series:BMC Bioinformatics
Subjects:
Machine Learning
Language Modeling
Sequence Embedding
Secondary structure prediction
Localization prediction
Transfer Learning
Online Access:https://doi.org/10.1186/s12859-019-3220-8

Internet

https://doi.org/10.1186/s12859-019-3220-8

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