Journal of Proteomics & Bioinformatics
Open Access
ISSN: 0974-276X
ISSN: 0974-276X
Department of Computational Data Science and Engineering, North Carolina Agricultural and Technical State University, Greensboro, USA
Research
NLPARG: Comparative Neural Word Embedding Approaches for Antibiotic Resistance Prediction
Author(s): Daniel Ananey Obiri and Kristen L Rhinehardt*
Antibiotic resistance increasingly has become a threat to global health as it hampers the efficacy of current antibiotics and the development of new antibiotic drugs. Appropriate identification of Antibiotic Resistance Genes (ARGs) is fundamental to the administration of the right antibiotics and for epidemiological purposes. However, mechanisms for identifying antimicrobial resistance such as minimum inhibitory concentration are tedious and time consuming. Also, using sequence similarity-based models have also not been able to identify novel ARGs which are highly diverse compared to known genes. To explore ARGs among genomic sequences, we comparatively applied three-word embedding techniques, Global Vectors (GloVe), Skip-Gram (SG) and Continuous Bag of Words (CBOW) to bacterial sequences and subsequently using the word vectors as embedding layers in Bidirectional Recurrent Neural Net.. View More»
DOI:
10.35248/0974-276X.23.16.654