Sam Behjati
Molecular Biology · 2013–2020
A researcher in the Science corpus: 9 papers; trusts 14 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 114 citations into it; #10,383 of 17,773 by trust here, #1,857 by citations
- Cancer Research — 52 citations into it; #828 of 1,780 by trust here, #221 by citations
- Biophysics — 6 citations into it
- Computational Biology & Bioinformatics — 5 citations into it
Whom Sam Behjati trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Aaron T. L. Lun
- Mark D. Robinson
- Anand Rajaraman
- Rahul Satija
- F. Alexander Wolf
- Laleh Haghverdi
- Andrew W. Butler
- Alicia Oshlack
- Jeffrey D. Ullman
- John C. Marioni
Who trusts Sam Behjati overall
Papers from Sam Behjati's perspective
Ordered by how strongly the researchers Sam Behjati trusts endorse each paper. Same corpus, a different order for every researcher.
- Spatial reconstruction of single-cell gene expression
- A scaling normalization method for differential expression analysis of RNA-seq data (Genome Biology)
- SCANPY: large-scale single-cell gene expression data analysis
- Massively parallel digital transcriptional profiling of single cells
- Diffusion pseudotime robustly reconstructs lineage branching
- Batch effects in single-cell RNA sequencing data are corrected by matching mutual nearest neighbours (Nature Biotechnology)
- Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes and progenitors (Science)
- Full-length RNA-seq from single cells using Smart-seq2 (Nature Protocols)
- Integrating single-cell transcriptomic data across different conditions, technologies, and species
- A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor (F1000Research)
Their papers
- Signatures of mutational processes in human cancer (2013) — 9,146 citations
- Decoding human fetal liver haematopoiesis (2019) — 515 citations
- SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data (2018) — 1,280 citations
- A cell atlas of human thymic development defines T cell repertoire formation (2020) — 648 citations
- Single cell transcriptomes from human kidneys reveal the cellular identity of renal tumors (2018) — 671 citations
- Prediction of acute myeloid leukaemia risk in healthy individuals (2018) — 766 citations
- High-throughput epitope discovery reveals frequent recognition of neo-antigens by CD4+ T cells in human melanoma (2014) — 654 citations
- Tumor Exome Analysis Reveals Neoantigen-Specific T-Cell Reactivity in an Ipilimumab-Responsive Melanoma (2013) — 827 citations
- Distinct H3F3A and H3F3B driver mutations define chondroblastoma and giant cell tumor of bone (2013) — 775 citations