Jean-Philippe Fortin

Molecular Biology · 2016–2017

A researcher in the Science corpus: 3 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jean-Philippe Fortin trusts overall

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

  1. W. Johnson
  2. The Cancer Genome Atlas Research Network
  3. Andrew E. Jaffe
  4. Jeffrey T. Leek
  5. Jovana Maksimovic
  6. Rafael A. Irizarry
  7. Mark Jenkinson
  8. William S. Cleveland
  9. Sandrine Dudoit
  10. Benjamin M. Bolstad

Who trusts Jean-Philippe Fortin overall

  1. Wanding Zhou
  2. Timothy Triche
  3. Meichen Yu

Papers from Jean-Philippe Fortin's perspective

Ordered by how strongly the researchers Jean-Philippe Fortin trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Using control genes to correct for unwanted variation in microarray data. (Biostatistics)
  2. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm (IEEE Transactions on Medical Imaging)
  3. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias (Bioinform.)
  4. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. (Biostatistics)
  5. White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. (Cerebral Cortex)
  6. STATISTICAL METHODS FOR IDENTIFYING DIFFERENTIALLY EXPRESSED GENES IN REPLICATED cDNA MICROARRAY EXPERIMENTS
  7. DNA methylation arrays as surrogate measures of cell mixture distribution (BMC Bioinformatics)
  8. A global optimisation method for robust affine registration of brain images (Medical Image Anal.)
  9. Differential DNA Methylation in Purified Human Blood Cells: Implications for Cell Lineage and Studies on Disease Susceptibility (PLoS ONE)
  10. Multi-Atlas Segmentation with Joint Label Fusion (IEEE Transactions on Pattern Analysis and Machine Intelligence)

Their papers