Byungjin Hwang
Molecular Biology · 2018
A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 52 citations into it; #12,302 of 17,773 by trust here, #14,176 by citations
- Cancer Research — 11 citations into it; #1,039 of 1,780 by trust here, #1,546 by citations
- Biomedical Engineering — 7 citations into it
- Immunology — 6 citations into it
Whom Byungjin Hwang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark D. Robinson
- Sam T. Roweis
- Dominic Grün
- Aaron T. L. Lun
- Nir Friedman
- Todd Thorsen
- Ziv Bar-Joseph
- Jun Li
- Ilya Shmulevich
- Florian Buettner
Who trusts Byungjin Hwang overall
Papers from Byungjin Hwang's perspective
Ordered by how strongly the researchers Byungjin Hwang trusts endorse each paper. Same corpus, a different order for every researcher.
- Massively parallel single cell RNA-Seq for marker-free decomposition of tissues into cell types (Science)
- Droplet barcoding for single cell transcriptomics applied to embryonic stem cells (Cell)
- Single-Cell RNA-Seq Reveals Dynamic, Random Monoallelic Gene Expression in Mammalian Cells
- Accounting for technical noise in single-cell RNA-seq experiments (Nature Methods)
- mRNA-Seq whole-transcriptome analysis of a single cell (Nature Methods)
- Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B cell Development (Cell)
- Full-Length mRNA-Seq from single cell levels of RNA and individual circulating tumor cells (Nature Biotechnology)
- CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. (Cell Reports)
- Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets
- A scaling normalization method for differential expression analysis of RNA-seq data (Genome Biology)
Their papers
- Single-cell RNA sequencing technologies and bioinformatics pipelines (2018) — 1,502 citations