Ryan Feehan

Biochemistry, Genetics and Molecular BiologyMedicine

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 5 papers. Top paper: “Machine learning differentiates enzymatic and non-enzymatic metals in proteins”.

Machine learning differentiates enzymatic and non-enzymatic metals in proteins

Nature Communications(2021)10.1038/s41467-021-24070-3

N/A

0DataRank · unranked

61 citations

Meghan W. Franklin, Joanna S.G. Slusky, Ryan Feehan

Machine Learning Differentiates Enzymatic and Non-Enzymatic Metals in Proteins

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.02.01.429261

N/A

0DataRank · unranked

2 citations

Meghan W. Franklin, Joanna S.G. Slusky, Ryan Feehan

Membrane barrels are taller, fatter, inside-out soluble barrels

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.01.30.428970

N/A

0DataRank · unranked

1 citations

Ryan Feehan, Joanna S.G. Slusky, Rik Dhar

The energetics and evolution of oxidoreductases in deep time

Proteins Structure Function and Bioinformatics(2023)10.1002/prot.26563

N/A

0DataRank · unranked

13 citations

Nolan Fehon, Ryan Feehan, Michelle Miller, Andrew C. Mutter, Laryssa A. Rybak +13 more

The energetics and evolution of oxidoreductases in deep time

(2023)10.22541/au.168439504.41026088/v1

N/A

0DataRank · unranked

0 citations

Kenneth N. McGuinness, Nolan Fehon, Ryan Feehan, Michelle Miller, Andrew C. Mutter +12 more