Sipko van Dam

Molecular Biology · 2017

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Sipko van Dam trusts overall

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

  1. Patrik D'haeseleer
  2. Gerd Kempermann
  3. Réka Albert
  4. Peter Langfelder
  5. Mark D. Robinson
  6. Bin Zhang
  7. Bo Li
  8. Rhonda L. Bacher
  9. Yizong Cheng
  10. Steve Horvath

Papers from Sipko van Dam's perspective

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

  1. A scaling normalization method for differential expression analysis of RNA-seq data (Genome Biology)
  2. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome (BMC Bioinformatics)
  3. Using Bayesian Networks to Analyze Expression Data (Annual International Conference on Research in Computational Molecular Biology)
  4. Droplet barcoding for single cell transcriptomics applied to embryonic stem cells (Cell)
  5. Computational and analytical challenges in single-cell transcriptomics (Nature reviews genetics)
  6. Computational discovery of gene modules and regulatory networks (Nature Biotechnology)
  7. A General Framework for Weighted Gene Co-Expression Network Analysis (Statistical Applications in Genetics and Molecular Biology)
  8. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets
  9. Controlling the false discovery rate: a practical and powerful approach to multiple testing
  10. limma powers differential expression analyses for RNA-sequencing and microarray studies

Their papers