Allon Wagner

Molecular Biology · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 207 citations into it; #5,303 of 17,773 by trust here, #3,712 by citations
• Cancer Research — 49 citations into it
• Computer Networks and Communications — 5 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Allon Wagner trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Dominic Grün
2. Mark Newman
3. Neil D. Lawrence
4. Johann A. Gagnon-Bartsch
5. L. V. D. van der Maaten
6. Zdravko I. Botev
7. Sean Bendall
8. Karthik Shekhar
9. Andrew McDavid
10. Greg Finak

Who trusts Allon Wagner overall

1. Romain Lopez
2. F. Alexander Wolf
3. Jiarui Ding
4. Jeffrey C. Regier
5. Fabian J Theis
6. Anne Condon
7. Philipp Angerer
8. Nir Yosef
9. Malte D. Luecken
10. J. Doyle

Papers from Allon Wagner's perspective

Ordered by how strongly the researchers Allon Wagner trusts endorse each paper. Same corpus, a different order for every researcher.

1. Massively parallel single cell RNA-Seq for marker-free decomposition of tissues into cell types (Science)
2. Single cell RNA Seq reveals dynamic paracrine control of cellular variation (Nature)
3. Accounting for technical noise in single-cell RNA-seq experiments (Nature Methods)
4. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets
5. Full-Length mRNA-Seq from single cell levels of RNA and individual circulating tumor cells (Nature Biotechnology)
6. Droplet barcoding for single cell transcriptomics applied to embryonic stem cells (Cell)
7. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
8. Bayesian approach to single-cell differential expression analysis (Nature Methods)
9. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. (Cell Reports)
10. Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments (Bioinform.)

Their papers

• The Human Cell Atlas (2017) — 1,788 citations
• Revealing the vectors of cellular identity with single-cell genomics (2016) — 608 citations