Ziv Bar-Joseph

Molecular Biology · 2002–2019

A researcher in the Science corpus: 9 papers; trusts 47 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

Whom Ziv Bar-Joseph trusts overall

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

  1. Patrick O. Brown
  2. Sofia Wichert
  3. David Botstein
  4. Nir Friedman
  5. Marco Ramoni
  6. Audrey P. Gasch
  7. Olga G. Troyanskaya
  8. Amos Maritan
  9. George M. Church
  10. Konstantinos Fokianos

Who trusts Ziv Bar-Joseph overall

  1. Byungjin Hwang
  2. Andy M. Yip
  3. Yanjun Qi
  4. Carolin Strobl
  5. Meghana Kshirsagar
  6. Michael Hecker
  7. Miron Bartosz Kursa
  8. Víctor Martínez
  9. J. Lee
  10. Steve Horvath

Papers from Ziv Bar-Joseph's perspective

Ordered by how strongly the researchers Ziv Bar-Joseph trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Genomic expression programs in the response of yeast cells to environmental changes. (Molecular Biology of the Cell)
  2. Singular value decomposition for genome-wide expression data processing and modeling. (Proceedings of the National Academy of Sciences of the United States of America)
  3. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. (Molecular Biology of the Cell)
  4. Functional organization of the yeast proteome by systematic analysis of protein complexes (Nature)
  5. Using Bayesian Networks to Analyze Expression Data (Annual International Conference on Research in Computational Molecular Biology)
  6. Network motifs in the transcriptional regulation network of Escherichia coli (Nature Genetics)
  7. A comprehensive two-hybrid analysis to explore the yeast protein interactome (Proceedings of the National Academy of Sciences of the United States of America)
  8. MIPS: analysis and annotation of proteins from whole genomes in 2005 (Nucleic Acids Res.)
  9. A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae (Nature)
  10. Controlling the false discovery rate: a practical and powerful approach to multiple testing

Their papers