Michelle Turcotte

Molecular Biology · 2015–2019

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michelle Turcotte trusts overall

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

  1. Tom Minka
  2. Yingying Fan
  3. Albert-László Barabási
  4. Kim-Anh Lê Cao
  5. Nir Friedman

Papers from Michelle Turcotte's perspective

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

  1. Controlling the false discovery rate: a practical and powerful approach to multiple testing
  2. Molecular networks as sensors and drivers of common human diseases (Nature)
  3. The sparsity and bias of the Lasso selection in high-dimensional linear regression
  4. Expectation Propagation for approximate Bayesian inference
  5. Network Medicine: A Network-based Approach to Human Disease
  6. Bioconductor: open software development for computational biology and bioinformatics (Genome Biology)
  7. Unsupervised pattern discovery in human chromatin structure through genomic segmentation
  8. Using Bayesian Networks to Analyze Expression Data (Annual International Conference on Research in Computational Molecular Biology)
  9. Direct Clustering of a Data Matrix
  10. Finishing the euchromatic sequence of the human genome (Nature)

Their papers