Search Results - "Ranjan, Bobby"
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scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data
Published in BMC bioinformatics (12-04-2021)“…Clustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on…”
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DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data
Published in Nature communications (06-10-2021)“…Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines…”
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Systematic immune cell dysregulation and molecular subtypes revealed by single-cell RNA-seq of subjects with type 1 diabetes
Published in Genome medicine (27-03-2024)“…Type 1 diabetes mellitus (T1DM) is a prototypic endocrine autoimmune disease resulting from an immune-mediated destruction of pancreatic insulin-secreting…”
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Lineage-dependent gene expression programs influence the immune landscape of colorectal cancer
Published in Nature genetics (01-06-2020)“…Immunotherapy for metastatic colorectal cancer is effective only for mismatch repair-deficient tumors with high microsatellite instability that demonstrate…”
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Composite mathematical modeling of calcium signaling behind neuronal cell death in Alzheimer's disease
Published in BMC systems biology (11-04-2018)“…Alzheimer's disease (AD) is a progressive neurological disorder, recognized as the most common cause of dementia affecting people aged 65 and above. AD is…”
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Paternal microbiome perturbations impact offspring fitness
Published in Nature (London) (16-05-2024)“…The gut microbiota operates at the interface of host–environment interactions to influence human homoeostasis and metabolic networks 1 – 4 . Environmental…”
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RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data
Published in Nucleic acids research (07-09-2021)“…Abstract The transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised…”
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