This dataset includes the data for training the protein function prediction models at github.com/stamakro/GCN-for-Structure-and-Function. For each protein, a pickle file is provided, containing its sequence, ELMo embedding and labels. It also includes the weights of the trained models that can be applied directly. README file at github.com/stamakro/GCN-for-Structure-and-Functio
This dataset includes; - Precomputed representation vectors of human proteins with various protein ...
© 2022 The Author(s)Deep learning technologies have been adopted to predict the functions of newly i...
With the development of next generation sequencing techniques, it is fast and cheap to determine pro...
Predicting the function of proteins is a crucial part of genome annotation, which can help in solvin...
Motivation: Machine-learning models trained on protein sequences and their measured functions can in...
Protein function prediction is a challenging but important task in bioinformatics. Many prediction m...
Conventional techniques for protein function prediction using similarities of amino acid sequences e...
Computationally annotating proteins with a molecular function is a difficult problem that is made ev...
The rapid increase in the number of proteins in sequence databases and the diversity of their functi...
Motivation: Computational approaches to protein function prediction infer protein function by findin...
Motivation: A central problem in bioinformatics is the assignment of function to sequenced open read...
Proteins are biologically diverse, and their function is rarely depicted by their structure. The pre...
Protein functions are often described using the Gene Ontology (GO) which is an ontology consisting...
Background We develop a probabilistic model for combining kernel matrices to predict the function o...
Protein function prediction is an important and challenging field in Bioinformatics. There are vario...
This dataset includes; - Precomputed representation vectors of human proteins with various protein ...
© 2022 The Author(s)Deep learning technologies have been adopted to predict the functions of newly i...
With the development of next generation sequencing techniques, it is fast and cheap to determine pro...
Predicting the function of proteins is a crucial part of genome annotation, which can help in solvin...
Motivation: Machine-learning models trained on protein sequences and their measured functions can in...
Protein function prediction is a challenging but important task in bioinformatics. Many prediction m...
Conventional techniques for protein function prediction using similarities of amino acid sequences e...
Computationally annotating proteins with a molecular function is a difficult problem that is made ev...
The rapid increase in the number of proteins in sequence databases and the diversity of their functi...
Motivation: Computational approaches to protein function prediction infer protein function by findin...
Motivation: A central problem in bioinformatics is the assignment of function to sequenced open read...
Proteins are biologically diverse, and their function is rarely depicted by their structure. The pre...
Protein functions are often described using the Gene Ontology (GO) which is an ontology consisting...
Background We develop a probabilistic model for combining kernel matrices to predict the function o...
Protein function prediction is an important and challenging field in Bioinformatics. There are vario...
This dataset includes; - Precomputed representation vectors of human proteins with various protein ...
© 2022 The Author(s)Deep learning technologies have been adopted to predict the functions of newly i...
With the development of next generation sequencing techniques, it is fast and cheap to determine pro...
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