Skip to Main content Skip to Navigation
Conference papers

Functional Annotation of Proteins using Domain Embedding based Sequence Classification

Abstract : Due to the recent advancement in genomic sequencing technologies, the number of protein sequences in public databases is growing exponentially. The UniProt Knowledgebase (UniProtKB) is currently the largest and most comprehensive resource for protein sequence and annotation data. The May 2019 release of the Uniprot Knowledge base (UniprotKB) contains around 158 million protein sequences. For the complete exploitation of this huge knowledge base, protein sequences need to be annotated with functional properties such as Enzyme Commission (EC) numbers and Gene Ontology terms. However, there is only about half a million sequences (UniprotKB/SwissProt) are reviewed and functionally annotated by expert curators using information extracted from the published literature and computational analyses. The manual annotation by experts are expensive, slow and insufficient to fill the gap between the annotated and unannotated protein sequences. In this paper, we present an automatic functional annotation technique using neural network based based word embedding exploiting domain and family information of proteins. Domains are the most conserved regions in protein sequences and constitute the building blocks of 3D protein structures. To do the experiment, we used fastText a , a library for learning of word embeddings and text classification developed by Facebook's AI Research lab. The experimental results show that domain embeddings perform much better than k-mer based word embeddings. a
Complete list of metadata

Cited literature [40 references]  Display  Hide  Download
Contributor : BIshnu SARKER Connect in order to contact the contributor
Submitted on : Tuesday, September 10, 2019 - 7:29:13 PM
Last modification on : Saturday, July 23, 2022 - 3:53:01 AM
Long-term archiving on: : Saturday, February 8, 2020 - 12:04:03 AM


Files produced by the author(s)



Bishnu Sarker, David W. Ritchie, Sabeur Aridhi. Functional Annotation of Proteins using Domain Embedding based Sequence Classification. KDIR 2019 - 11th International Conference on Knowledge Discovery and Information Retrieval, Sep 2019, Vienna, Austria. pp.163-170, ⟨10.5220/0008353401630170⟩. ⟨hal-02283430⟩



Record views


Files downloads