Laura L. Elo
Molecular Biology · 2013–2016
A researcher in the Science corpus: 3 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 129 citations into it
- Cancer Research — 26 citations into it
- Genetics — 20 citations into it
- Spectroscopy — 7 citations into it
Whom Laura L. Elo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Gordon K. Smyth
- Mark D. Robinson
- Cole Trapnell
- Jun Li
- Thomas J. Hardcastle
- Charlotte Soneson
- Sonia Tarazona
- Alicia Oshlack
Papers from Laura L. Elo's perspective
Ordered by how strongly the researchers Laura L. Elo trusts endorse each paper. Same corpus, a different order for every researcher.
- edgeR: a Bioconductor package for differential expression analysis of digital gene expression data (Bioinform.)
- A scaling normalization method for differential expression analysis of RNA-seq data (Genome Biology)
- Ultrafast and memory-efficient alignment of short DNA sequences to the human genome (Genome Biology)
- Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments (BMC Bioinformatics)
- Mapping and quantifying mammalian transcriptomes by RNA-Seq (Nature Methods)
- Understanding mechanisms underlying human gene expression variation with RNA sequencing (Nature)
- baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data (BMC Bioinformatics)
- RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. (Genome Research)
- Moderated statistical tests for assessing differences in tag abundance (Bioinform.)
- Detecting differential usage of exons from RNA-seq data (Genome Research)
Their papers
- A survey of best practices for RNA-seq data analysis (2016) — 2,568 citations
- Comparison of software packages for detecting differential expression in RNA-seq studies (2013) — 404 citations
- A systematic evaluation of normalization methods in quantitative label-free proteomics (2016) — 326 citations