Exploring Plausible Therapeutic Targets for Alzheimer's Disease using Multi-omics Approach, Machine Learning and Docking.

The progressive deterioration of neurons leads to Alzheimer's disease (AD), and developing a drug for this disorder is challenging. Substantial gene/transcriptome variability from multiple cell types leads to downstream pathophysiologic consequences that represent the heterogeneity of this disease. Identifying potential biomarkers for promising therapeutics is strenuous due to the fact that the transcriptome, epigenetic, or proteome changes detected in patients are not clear whether they are the cause or consequence of the disease, which eventually makes the drug discovery efforts intricate.

Alz-Disc: A Tool to Discriminate Disease-causing and Neutral Mutations in Alzheimer's Disease.

Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder that affects the neuronal system and leads to memory loss. Many coding gene variants are associated with this disease and it is important to characterize their annotations.

Methods: We collected the Alzheimer's disease-causing and neutral mutations from different databases.

Exploring the selective vulnerability in Alzheimer disease using tissue specific variant analysis.

The selective vulnerability of distinct regions of the brain is a critical factor in neurodegenerative disorders. In Alzheimer's disease (AD), neurons in hippocampus situated in medial temporal lobe are immensely damaged. Identifying tissue-specific variants is essential in order to perceive the selective vulnerability in AD.

NGS meta data analysis for identification of SNP and INDEL patterns in human airway transcriptome: A preliminary indicator for lung cancer.

High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. It is also an efficient way to discover coding SNPs and when multiple individuals with different genetic backgrounds were used, RNA-Seq is very effective for the identification of SNPs. The objective of this study was to perform SNP and INDEL discoveries in human airway transcriptome of healthy never smokers, healthy current smokers, smokers without lung cancer and smokers with lung cancer.