Lukas M. Weber

Molecular Biology · 2016–2020

A researcher in the Science corpus: 4 papers; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 79 citations into it; #10,485 of 17,773 by trust here, #8,381 by citations
• Biophysics — 27 citations into it; #722 of 1,196 by trust here, #787 by citations
• Representation & Self-Supervised Learning — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it

Whom Lukas M. Weber trusts overall

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

1. Nikesh Kotecha
2. Sean Bendall
3. Peter O. Krutzik
4. L. V. D. van der Maaten
5. Erin F. Simonds
6. Jonathan M. Irish
7. Garry P. Nolan
8. Hans-Peter Kriegel

Who trusts Lukas M. Weber overall

1. Malte D. Luecken
2. Anna C. Belkina
3. Fabian J Theis
4. Chris Ciccolella

Papers from Lukas M. Weber's perspective

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

1. Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum
2. CRITICAL ASSESSMENT OF AUTOMATED FLOW CYTOMETRY DATA ANALYSIS TECHNIQUES (Nature Methods)
3. A deep profiler's guide to cytometry. (Trends in immunology)
4. Automated Mapping of Phenotype Space with Single-Cell Data (Nature Methods)
5. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain (Science)
6. MAGMA: Generalized Gene-Set Analysis of GWAS Data (PLoS Comput. Biol.)
7. Partitioning heritability by functional annotation using genome-wide association summary statistics (Nature Genetics)
8. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
9. Gene Expression Elucidates Functional Impact of Polygenic Risk for Schizophrenia (Nature Neuroscience)
10. A survey of human brain transcriptome diversity at the single cell level (Proceedings of the National Academy of Sciences of the United States of America)

Their papers

• Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex (2020) — 1,067 citations
• Comparison of Clustering Methods for High-Dimensional Single-Cell Flow and Mass Cytometry Data (2016) — 362 citations
• High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy (2018) — 648 citations
• CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets (2017) — 442 citations