Author

Francesca Frau

Sanofi (Germany)ORCID 0000-0001-6954-9665Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Genetic & Genomic Medicine· 2 Genetics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Research Focus:GWAS / association mapping· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1

Frequent Co-Authors

Adem Y. DawediD· 2 shared Andrea MariiD· 2 shared Angus G. JonesiD· 2 shared Anubha MahajaniD· 2 shared Ewan R. PearsoniD· 2 shared François N. PattouiD· 2 shared Gary Steven FrostiD· 2 shared Hartmut Ruetten· 2 shared

Activity by Year

2019-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 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 papersGenetic & Genomic Medicine

Adem Y. DawedORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Genetic & Genomic MedicinemedRxivPreprintOct 16, 2020

Genome-Wide Polygenic Risk Score Identifies Individuals at Elevated Parkinson's Disease Risk

Yingnan Han, Erin A. Teeple, Srinivas Shankara…·Dinesh Kumar

This paper computes a genome-wide polygenic risk score for Parkinson's Disease using 6.2 million variants and finds it strongly associates with increased disease risk and earlier onset.

7 citations

humanwhole-genome sequencing

𝕏 PostBluesky

Genetic & Genomic MedicinePLoS MedicinePeer-reviewedJun 19, 2020

Predicting and elucidating the etiology of fatty liver disease using a machine learning-based approach: an IMI DIRECT study

Naeimeh Atabaki‐Pasdar, Mattias Ohlsson, Ana Viñuela…·Paul W. Franks

This study develops machine learning models to predict liver fat content using multi-omic and clinical data from NAFLD patients, achieving higher accuracy than existing tools.

97 citationstop 1%

humanmetabolomics

𝕏 PostBluesky

GeneticsDiabetes CarePeer-reviewedMar 18, 2019

Variation in the plasma membrane monoamine transporter (PMAT, encoded in SLC29A4) and organic cation transporter 1 (OCT1, encoded in SLC22A1) and gastrointestinal intolerance to metformin in type 2 diabetes: an IMI DIRECT study

Adem Y. Dawed, Kaixin Zhou, Nienke van Leeuwen…·A. Forman

This study investigates the association between genetic variants in PMAT and OCT1 transporters and metformin gastrointestinal intolerance in type 2 diabetes patients.

72 citationstop 2%

humanstatistical model

𝕏 PostBluesky