Covid-19: Booster vaccine to be rolled out in autumn as UK secures 60m more Pfizer doses
نویسندگان
چکیده
ABSTRACT Accurate annotation of protein functions is important for a profound understanding molecular biology. A large number proteins remain uncharacterized because the sparsity available supporting information. For set proteins, only type information their amino acid sequence. In this paper, we propose DeepSeq – deep learning architecture that utilizes sequence to predict its associated functions. The prediction process does not require handcrafted features; rather, automatically extracts representations from input data. Results our experiments with indicate significant improvements in terms accuracy when compared other sequence-based methods. Our model achieves an overall validation 86.72%, F1 score 71.13%. Moreover, using learned features and without any changes DeepSeq, successfully solved different problem i.e. function localization, no human intervention. Finally, discuss how same can be used solve even more complicated problems such as 2D 3D structure well protein-protein interactions.
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ژورنال
عنوان ژورنال: BMJ
سال: 2021
ISSN: ['0959-8138']
DOI: https://doi.org/10.1136/bmj.n1116