Author

Karla Cristina do Vale Ferreira

Universidade Católica de BrasíliaORCID 0000-0001-7461-3860Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:benchmark study· 1 Research Focus:drug response / drug discovery· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Assay:protein sequence· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Octávio Luiz FrancoiD· 2 shared William Farias PortoiD· 2 shared Leonardo Ferreira Fialho· 1 shared Sérgio Amorim de AlencariD· 1 shared Suzana M. RibeiroiD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Octávio Luiz FrancoORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsBiochimica et Biophysica Acta (BBA) - General SubjectsPeer-reviewedDec 22, 2021

Sense the Moment: a highly sensitive antimicrobial activity predictor based on hydrophobic moment

William Farias Porto, Karla Cristina do Vale Ferreira, Suzana M. Ribeiro, Octávio Luiz Franco

This paper introduces a new antimicrobial activity predictor called 'Sense the Moment' that outperforms deep-learning methods in distinguishing antimicrobial peptides from shuffled versions.

28 citations

protein sequencemachine learning (classical)

𝕏 PostBluesky

BioinformaticsChemical Biology & Drug DesignPeer-reviewedMar 9, 2020

Benchmarking analysis of deleterious SNP prediction tools on CYP2D6 enzyme

Karla Cristina do Vale Ferreira, Leonardo Ferreira Fialho, Octávio Luiz Franco…·William Farias Porto

The paper evaluates 20 SNP prediction tools on CYP2D6 missense variants, finding FATHMM performs best with a Matthews correlation coefficient of 0.39.

7 citations

humanGWAS summary statistics

𝕏 PostBluesky