Author

Ariya Shajii

MIT Computer Science and Artificial Intelligence LaboratoryORCID 0000-0002-6163-1848Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:genome assembly· 2 Assay:long-read sequencing· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Research Focus:benchmarking· 1 Approach:experimental assay· 1 Organism:human· 1 Research Focus:phylogenetics / evolution· 1

Frequent Co-Authors

Bonnie BergeriD· 2 shared Ibrahim NumanagićiD· 2 shared Alexander T. LeightoniD· 1 shared Haley W. GreenyeriD· 1 shared Saman P. AmarasingheiD· 1 shared

Activity by Year

2017-2020 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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2 shared papersBioinformatics

Bonnie BergerORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 29, 2020

A Python-based optimization framework for high-performance genomics

Ariya Shajii, Ibrahim Numanagić, Alexander T. Leighton…·Bonnie Berger

The paper introduces Seq, a Python-based framework that improves performance in genomics by combining Python's usability with C/C++ efficiency, achieving speedups over existing implementations.

3 citations

whole-genome sequencinglong-read sequencing

𝕏 PostBluesky

BioinformaticsbioRxivPreprintNov 16, 2017

Latent variable model for aligning barcoded short-reads improves downstream analyses

Ariya Shajii, Ibrahim Numanagić, Bonnie Berger

EMA improves barcoded read alignment for third-generation sequencing, leading to more accurate genotyping and phasing with fewer false positives and better handling of homologous regions.

21 citations

humanlong-read sequencing

𝕏 PostBluesky