Ian Sillitoe

Molecular Biology · 2001–2022

A researcher in the Science corpus: 17 papers; trusts 2 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Molecular Biology — 221 citations into it; #16,698 of 17,773 by trust here, #2,360 by citations

Whom Ian Sillitoe trusts overall

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

1. Kazutaka Katoh
2. Douglas L. Theobald
3. Sean R. Eddy
4. Christine A. Orengo
5. Jaina Mistry
6. Robert D. Finn
7. Minoru Kanehisa
8. Oliver Redfern
9. William S. J. Valdar
10. Daron M. Standley

Who trusts Ian Sillitoe overall

1. Erik Nijkamp
2. Sheng Wang
3. Hua Cheng
4. Ronghui You
5. Robert D. Finn
6. Roman A. Laskowski
7. Juyong Lee
8. Namrata Anand
9. Kevin E. Wu
10. Jiaxiang Wu

Papers from Ian Sillitoe's perspective

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

1. Basic local alignment search tool.
2. The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB data
3. The SWISS-PROT protein sequence data bank and its supplement TrEMBL
4. Data growth and its impact on the SCOP database: new developments
5. The Universal Protein Resource (UniProt)
6. Hidden Markov models for detecting remote protein homologies
7. SIFTS: Structure Integration with Function, Taxonomy and Sequences resource
8. The Impact of Structural Genomics: Expectations and Outcomes (Science)
9. MODBASE: a database of annotated comparative protein structure models and associated resources
10. InterPro: the integrative protein signature database

Their papers

• CATH: an expanded resource to predict protein function through structure and sequence (2016) — 377 citations
• Extending CATH: increasing coverage of the protein structure universe and linking structure with function (2010) — 137 citations
• The InterPro protein families database: the classification resource after 15 years (2014) — 1,300 citations
• The CATH domain structure database: new protocols and classification levels give a more comprehensive resource for exploring evolution (2006) — 300 citations
• InterPro in 2017—beyond protein family and domain annotations (2016) — 1,390 citations
• InterPro in 2019: improving coverage, classification and access to protein sequence annotations (2018) — 1,309 citations
• Genome3D: exploiting structure to help users understand their sequences (2014) — 47 citations
• Gene3D: expanding the utility of domain assignments (2015) — 68 citations
• Gene3D: a domain-based resource for comparative genomics, functional annotation and protein network analysis (2011) — 114 citations
• Review: what can structural classifications reveal about protein evolution? (2001) — 50 citations
• Gene3D: Extensive prediction of globular domains in proteins (2017) — 185 citations
• The InterPro protein families and domains database: 20 years on (2020) — 1,852 citations
• The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations
• InterPro in 2022 (2022) — 1,929 citations
• CATH: increased structural coverage of functional space (2020) — 432 citations
• MSAViewer: interactive JavaScript visualization of multiple sequence alignments (2016) — 160 citations
• CATH: comprehensive structural and functional annotations for genome sequences (2014) — 439 citations