A framework for predicting lncRNAs expression in human dendritic cells in response to M. tuberculosis infection

Faizah Aplop, Saharuddin Mohamad


Tuberculosis (TB) is an air-borne infectious diseases caused by M. tuberculosis bacteria that primarily affects human lungs. Existing vaccine does not work well due to the evolvement and latent movement of this bacteria. Developing an effective vaccine to combat Tuberculosis is very difficult as the interaction between the bacteria and human immune system is not fully understood. With recent advancement of transcriptome profiling analysis, long noncoding ribonukleat acids (lncRNAs) are found to be widely expressed in immune system. However, the role of lncRNAs is still not been widely explored in understanding human immune response to TB infection. In this paper, we propose a general framework for predicting lncRNAs being expressed in human dendritic cells. By incorporating deep learning method with RNA-seq data analysis, we intend to identify and characterize the lncRNAs found in dendritic cells from two groups of TB resistant patients through their RNA-seq expression data.


Convolutional neural networks; Dendritic cells; lncRNAs; RNA-seq expression analysis; Tuberculosis

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DOI: https://doi.org/10.11591/eei.v12i2.4289


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Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).