InterPro and InterProScan

By Nicola J. Mulder, Rolf Apweiler. 2007

322 citations recorded by the source corpus.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2c1c5133ea19440439494e7f3b6313eb8ded55e9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Dan Ofer
2. Michal Linial
3. Björn Usadel
4. G. Ponce-Soto
5. K. Krause
6. Mark Stitt
7. Kristina Gruden
8. Anthony M. Bolger

In Spectroscopy

1. Mark Stitt
2. Björn Usadel
3. Dan Ofer
4. Michal Linial

Citations in the corpus

• ProFET: Feature engineering captures high-level protein functions (2015, background): “Currently, there are (cid:2) 27000 such models (InterPro, Mulder and Apweiler, 2007) that cover 83% of all sequences in UniProtKB (2014_10).”
• MapMan4: A Refined Protein Classification and Annotation Framework Applicable to Multi-Omics Data Analysis. (2019, methodology): “Mercator4 and InterProScan inferences were compared with the gold standard annotation, and resulted in a Matthews Correlation Coefficient (MCC) of 0.16 for both Mercator4 and InterProScan (with Mercator4 yielding a slightly higher value), indicating that GO terms inferred are indeed meaningful and n”