Layal Shaheen- Master of Science in Applied Bioinformatics
- PhD Student at Moscow Institute of Physics and Technology
Layal Shaheen
- Master of Science in Applied Bioinformatics
- PhD Student at Moscow Institute of Physics and Technology
PhD student in Bioinformatics
About
4
Publications
201
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Introduction
Bioinformatician, mainly focused on Genetic research. Currently working on building PRS models for different diseases.
Current institution
Publications
Publications (4)
Background
Polygenic risk score (PRS) prediction is widely used to assess the risk of diagnosis and progression of many diseases. Routinely, the weights of individual SNPs are estimated by the linear regression model that assumes independent and linear contribution of each SNP to the phenotype. However, for complex multifactorial diseases such as A...
Background
COVID-19 disease has infected more than 772 million people, leading to 7 million deaths. Although the severe course of COVID-19 can be prevented using appropriate treatments, effective interventions require a thorough research of the genetic factors involved in its pathogenesis.
Methods
We conducted a genome-wide association study (GWAS...
Background
Polygenic risk score (PRS) prediction is widely used to assess the risk of diagnosis and progression of many diseases. Routinely, the weights of individual SNPs are estimated by the linear regression model that assumes independent and linear contribution of each SNP to the phenotype. However, for complex multifactorial diseases such as A...
Single-cell ATAC-seq (scATAC-seq) is a recently developed approach that provides means to investigate open chromatin at single cell level, to assess epigenetic regulation and transcription factors binding landscapes. The sparsity of the scATAC-seq data calls for imputation. Similarly, preprocessing (filtering) may be required to reduce computationa...
