Alberto Paccanaro
Molecular Biology · with Zhang · 2006–2019
A researcher in the Science corpus: 6 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 169 citations into it
- Cell Biology — 12 citations into it
- Computational Theory and Mathematics — 12 citations into it
- Statistical and Nonlinear Physics — 8 citations into it
Whom Alberto Paccanaro trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Alberto Paccanaro's perspective
Ordered by how strongly the researchers Alberto Paccanaro trusts endorse each paper. Same corpus, a different order for every researcher.
- A comprehensive two-hybrid analysis to explore the yeast protein interactome (Proceedings of the National Academy of Sciences of the United States of America)
- A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae (Nature)
- An efficient algorithm for large-scale detection of protein families. (Nucleic Acids Research)
- MIPS: analysis and annotation of proteins from whole genomes in 2005 (Nucleic Acids Res.)
- Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants (Science)
- Global analysis of protein expression in yeast (Nature)
- Subcellular localization of the yeast proteome. (Genes & Development)
- DIP: the Database of Interacting Proteins
- Emergence of Scaling in Random Networks
- Global analysis of protein localization in budding yeast (Nature)
Their papers
- A large-scale evaluation of computational protein function prediction (2013) — 1,002 citations
- Global landscape of protein complexes in the yeast Saccharomyces cerevisiae (2006) — 3,074 citations
- A Census of Human Soluble Protein Complexes (2012) — 844 citations
- Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins (2009) — 402 citations
- Detecting overlapping protein complexes in protein-protein interaction networks (2012) — 1,237 citations
- The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations