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Qiaolin Deng

Researcher at Karolinska Institutet

Publications -  49
Citations -  6603

Qiaolin Deng is an academic researcher from Karolinska Institutet. The author has contributed to research in topics: Dopamine & Stem cell. The author has an hindex of 21, co-authored 43 publications receiving 5123 citations. Previous affiliations of Qiaolin Deng include Tongji University & Ludwig Institute for Cancer Research.

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Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells

TL;DR: Applying Smart-Seq to circulating tumor cells from melanomas, it is found that although gene expression estimates from single cells have increased noise, hundreds of differentially expressed genes could be identified using few cells per cell type.
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Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells.

TL;DR: It is concluded that independent and stochastic allelic transcription generates abundant random monoallelic expression in the mammalian cell.
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Single-Cell RNA-Seq Reveals Lineage and X Chromosome Dynamics in Human Preimplantation Embryos

TL;DR: A comprehensive transcriptional map of human embryo development, including the sequenced transcriptomes of 1,529 individual cells from 88 human preimplantation embryos, shows that cells undergo an intermediate state of co-expression of lineage-specific genes, followed by a concurrent establishment of the trophectoderm, epiblast, and primitive endoderm lineages, which coincide with blastocyst formation.
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Identification of Intrinsic Determinants of Midbrain Dopamine Neurons

TL;DR: It is shown that the homeodomain proteins Lmx1a and Msx1 function as determinants of midbrain dopamine neurons, cells that degenerate in patients with Parkinson's disease, and suggest that they may be essential tools in cell replacement strategies in Parkinson’s disease.
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Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq

TL;DR: This work generates electrophysiological and molecular profiles of 58 neocortical cells and shows that gene expression patterns can be used to infer the morphological and physiological properties such as axonal arborization and action potential amplitude of individual neurons.