Author

Nafiseh Sedaghat

Simon Fraser UniversityORCID 0000-0002-8675-8407Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:drug response / drug discovery· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:human· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Amir Hosein Safari· 2 shared Hooman Zabeti· 2 shared Leonid ChindelevitchiD· 2 shared Alpha Forna· 1 shared Maxwell Libbrecht· 1 shared Maxwell W. LibbrechtiD· 1 shared Nick DexteriD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 17 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

Amir Hosein Safari

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

An interpretable classification method for predicting drug resistance in M. tuberculosis

Hooman Zabeti, Nick Dexter, Amir Hosein Safari, Nafiseh Sedaghat, Maxwell W. Libbrecht, Leonid Chindelevitch

This paper introduces an interpretable classification method for predicting drug resistance in M. tuberculosis, achieving high accuracy and flexibility.

Algorithms for Molecular Biology · Aug 10, 2021Peer-reviewedBioinformatics

Predicting drug resistance in M. tuberculosis using a Long-term Recurrent Convolutional Networks architecture

Amir Hosein Safari, Nafiseh Sedaghat, Hooman Zabeti, Alpha Forna, Leonid Chindelevitch, Maxwell Libbrecht

The paper predicts drug resistance in M. tuberculosis using a gene burden-based approach with a Long-term Recurrent Convolutional Network (LRCN) architecture, showing improved performance over existing methods.

bioRxiv · Nov 7, 2020 · PreprintBioinformatics