Jan Aerts
Molecular Biology · 2004–2018
A researcher in the Science corpus: 8 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 188 citations into it
- Genetics — 93 citations into it
- Statistical and Nonlinear Physics — 8 citations into it
Whom Jan Aerts trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman (in Statistical and Nonlinear Physics)
- Sudhir Kumar (in Molecular Biology)
- Koichiro Tamura (in Molecular Biology)
- Masatoshi Nei (in Molecular Biology)
Papers from Jan Aerts's perspective
Ordered by how strongly the researchers Jan Aerts trusts endorse each paper. Same corpus, a different order for every researcher.
- Gene Ontology: tool for the unification of biology
- A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae (Nature)
- A comprehensive two-hybrid analysis to explore the yeast protein interactome (Proceedings of the National Academy of Sciences of the United States of America)
- Network motifs in the transcriptional regulation network of Escherichia coli (Nature Genetics)
- Lethality and centrality in protein networks
- Hierarchical Organization of Modularity in Metabolic Networks (Science)
- The large-scale organization of metabolic networks (Nature)
- Topological and causal structure of the yeast transcriptional regulatory network (Nature Genetics)
- Collective dynamics of ‘small-world’ networks
- Functional organization of the yeast proteome by systematic analysis of protein complexes (Nature)
Their papers
- Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution (2004) — 2,677 citations
- SCENIC: Single-cell regulatory network inference and clustering (2017) — 5,132 citations
- Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project (2008) — 565 citations
- Using graph theory to analyze biological networks (2011) — 792 citations
- GRNBoost2 and Arboreto: efficient and scalable inference of gene regulatory networks (2018) — 517 citations
- Genome-wide association study of copy number variation in 16,000 cases of eight common diseases and 3,000 shared controls (2010) — 710 citations
- Genome-Wide Survey of SNP Variation Uncovers the Genetic Structure of Cattle Breeds (2009) — 839 citations
- Origins and functional impact of copy number variation in the human genome (2009) — 1,997 citations