Author

Parya Aghasafari

University of California, DavisORCID 0000-0001-9138-8271Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:drug response / drug discovery· 2 Assay:electronic health records· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Colleen E. ClancyiD· 2 shared Igor V. VorobyoviD· 2 shared Pei‐Chi YangiD· 2 shared Divya C. KernikiD· 1 shared John R.D. DawsoniD· 1 shared Junko KurokawaiD· 1 shared Kauho Sakamoto· 1 shared Kevin R. DeMarcoiD· 1 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 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

Colleen E. ClancyORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 28, 2020

A deep learning algorithm to translate and classify cardiac electrophysiology: From induced pluripotent stem cell-derived cardiomyocytes to adult cardiac cells

Parya Aghasafari, Pei‐Chi Yang, Divya C. Kernik…·Colleen E. Clancy

This paper develops a deep learning model to classify and predict electrophysiological responses in cardiac cells across developmental stages using simulated and experimental data.

2 citations

electronic health recordsdeep learning

Systems BiologyCirculation ResearchPeer-reviewedMar 18, 2020

A computational pipeline to predict cardiotoxicity:From the atom to the rhythm

Pei‐Chi Yang, Kevin R. DeMarco, Parya Aghasafari…·Colleen E. Clancy

This paper develops a multiscale computational model to predict cardiotoxicity from drug chemistry to cardiac rhythm, validated using clinical data and showing high predictive accuracy for arrhythmia vulnerability.

85 citationstop 2%

humanelectronic health records