T. G. Belgard

Molecular Biology · 2016

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

Subfields

Whom T. G. Belgard trusts overall

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

  1. Peter Langfelder
  2. Steve Horvath

Papers from T. G. Belgard's perspective

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

  1. A General Framework for Weighted Gene Co-Expression Network Analysis (Statistical Applications in Genetics and Molecular Biology)
  2. Eigengene networks for studying the relationships between co-expression modules (BMC Systems Biology)
  3. Fast R Functions for Robust Correlations and Hierarchical Clustering (Journal of Statistical Software)
  4. HTSeq—a Python framework to work with high-throughput sequencing data (bioRxiv)
  5. The Elements of Statistical Learning
  6. Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks (BMC Genomics)
  7. A prediction-based resampling method for estimating the number of clusters in a dataset (Genome Biology)
  8. Derivative Estimation and Testing in Generalized Additive Models
  9. Statistical significance for genomewide studies (Proceedings of the National Academy of Sciences of the United States of America)
  10. STATISTICAL METHODS FOR IDENTIFYING DIFFERENTIALLY EXPRESSED GENES IN REPLICATED cDNA MICROARRAY EXPERIMENTS

Their papers