Zeynab Mousavikhamene

EngineeringPharmacology, Toxicology and PharmaceuticsMedicine

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 1 paper. Top paper: “Morphological features of single cells enable accurate automated classification of cancer from non-cancer cell lines”.

Morphological features of single cells enable accurate automated classification of cancer from non-cancer cell lines

Scientific Reports(2021)10.1038/s41598-021-03813-8

N/A

0DataRank · unranked

38 citations

Daniel J. Sykora, Milan Mrksich, Neda Bagheri, Zeynab Mousavikhamene