Shanrong Zhao
Molecular Biology · 2014–2020
A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 60 citations into it
- Cancer Research — 11 citations into it
Whom Shanrong Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark D. Robinson
- A. Jetten
- Bo Li
- Yoav Benjamini
- Ciaran Evans
- Ali Mortazavi
- Nicolas L. Bray
- Svitlana Tyekucheva
- Rob Patro
- Benjamin M. Bolstad
Who trusts Shanrong Zhao overall
Papers from Shanrong Zhao's perspective
Ordered by how strongly the researchers Shanrong Zhao trusts endorse each paper. Same corpus, a different order for every researcher.
- Controlling the false discovery rate: a practical and powerful approach to multiple testing
- A scaling normalization method for differential expression analysis of RNA-seq data (Genome Biology)
- edgeR: a Bioconductor package for differential expression analysis of digital gene expression data (Bioinform.)
- RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. (Genome Research)
- A comparison of normalization methods for high density oligonucleotide array data based on variance and bias (Bioinform.)
- Mapping and quantifying mammalian transcriptomes by RNA-Seq (Nature Methods)
- RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome (BMC Bioinformatics)
- Biases in Illumina transcriptome sequencing caused by random hexamer priming (Nucleic Acids Research)
- A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis (Briefings Bioinform.)
- Ultrafast and memory-efficient alignment of short DNA sequences to the human genome (Genome Biology)
Their papers
- Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells (2014) — 976 citations
- Applications of machine learning in drug discovery and development (2019) — 2,480 citations
- Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols (2020) — 354 citations