Virpi Leppa

Molecular Biology · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Virpi Leppa trusts

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

  1. Steve Horvath (in Molecular Biology)

Papers from Virpi Leppa's perspective

Ordered by how strongly the researchers Virpi Leppa 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. Fast R Functions for Robust Correlations and Hierarchical Clustering (Journal of Statistical Software)
  3. Eigengene networks for studying the relationships between co-expression modules (BMC Systems Biology)
  4. HTSeq—a Python framework to work with high-throughput sequencing data (bioRxiv)
  5. The Elements of Statistical Learning
  6. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias (Bioinform.)
  7. Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks (BMC Genomics)
  8. Derivative Estimation and Testing in Generalized Additive Models
  9. A prediction-based resampling method for estimating the number of clusters in a dataset (Genome Biology)
  10. Statistical significance for genomewide studies (Proceedings of the National Academy of Sciences of the United States of America)

Their papers