Browsing Faculty Publications (CoM) by Author "Zehra, Binte"
Now showing items 1-4 of 4
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Analyzing single cell transcriptome data from severe COVID-19 patients
Nassir, Nasna; Tambi, Richa; Bankapur, Asma; Karuvantevida, Noushad; Zehra, Binte; Begum, Ghausia; Hameid, Reem Abdel; Ahmed, Awab; Shabestari, Seyed Ali Safizadeh; Hachim, Mahmood Yaseen; Alsheikh-Ali, Alawi; Berdiev, Bakhrom; Al Heialy, Saba; Uddin, Mohammed (2022)SUMMARY: We describe the protocol for identifying COVID-19 severity specific cell types and their regulatory marker genes using single-cell transcriptomics data. We construct COVID-19 comorbid disease-associated gene list ... -
Construction of copy number variation landscape and characterization of associated genes in a Bangladeshi cohort of neurodevelopmental disorders.
Karuvantevida, Noushad; Begum, Ghausia; Zehra, Binte; Nassir, Nasna; Uddin, Mohammed (2023)Introduction: Copy number variations (CNVs) play a critical role in the pathogenesis of neurodevelopmental disorders (NDD) among children. In this study, we aim to identify clinically relevant CNVs, genes and their ... -
Lack of ethnic diversity in single-cell transcriptomics hinders cell type detection and precision medicine inclusivity
Kosaji, Noor; Zehra, Binte; Nassir, Nasna; Tambi, Richa; Berdiev, Bakhrom K.; Uddin, Mohammed (2023)Abstract: Perhaps one of the most revolutionary next generation sequencing technologies is single-cell (SC) transcriptomics, which was recognized by Nature in 2013 as the method of the year. SC-technologies delve deep ... -
Single-cell transcriptome identifies FCGR3B upregulated subtype of alveolar macrophages in patients with critical COVID-19
Nassir, Nasna; Tambi, Richa; Bankapur, Asma; Al Heialy, Saba; Karuvantevida, Noushad; Zehra, Binte; Begum, Ghausia; Hameid, Reem Abdel; Ahmed, Awab; Shabestari, Seyed Ali Safizadeh; Kandasamy, Richard K; Loney, Tom; Tayoun, Ahmad Abou; Nowotny, Norbert; Hachim, Mahmood Yaseen; Berdiev, Bakhrom; Alsheikh-Ali, Alawi; Uddin, Mohammed (2021)Summary: Understanding host cell heterogeneity is critical for unraveling disease mechanism. Utilizing large-scale single-cell transcriptomics, we analyzed multiple tissue specimens from patients with life-threatening ...