Author

Shubham Chandak

Stanford UniversityORCID 0000-0002-1130-9762Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Assay:DNA methylation· 2 Assay:whole-genome sequencing· 2 Organism:bacteria (other)· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:human· 1

Frequent Co-Authors

Tsachy WeissmaniD· 3 shared Kedar TatwawadiiD· 2 shared Aleksei AksimentieviD· 1 shared Alvaro Gonzalo HernandeziD· 1 shared Bach PhamiD· 1 shared Billy T. LauiD· 1 shared Chao PaniD· 1 shared Charles M. SchroederiD· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersBioinformatics

Tsachy WeissmanORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Magnetic DNA random access memory with nanopore readouts and exponentially-scaled combinatorial addressing

Billy T. Lau, Shubham Chandak, Sharmili Roy, Kedar Tatwawadi, Mary K. Wootters, Tsachy Weissman, Hanlee P. Ji

This paper introduces MDRAM, a DNA-based random access memory system that enables efficient and scalable readouts using nanopore sequencing and magnetic bead conjugation.

Scientific Reports · May 25, 2023Peer-reviewedSynthetic Biology

NanoSpring: reference-free lossless compression of nanopore sequencing reads using an approximate assembly approach

Qingxi Meng, Shubham Chandak, Yifan Zhu, Tsachy Weissman

NanoSpring compresses nanopore sequencing reads with a reference-free approximate assembly approach, achieving lower bit per base rates than gzip and competitive performance with CoLoRd.

Scientific Reports · Feb 6, 2023Peer-reviewedBioinformatics

Expanding the Molecular Alphabet of DNA-Based Data Storage Systems with Neural Network Nanopore Readout Processing

S. Kasra Tabatabaei, Bach Pham, Chao Pan, Jingqian Liu, Shubham Chandak, Spencer A. Shorkey, Alvaro Gonzalo Hernandez, Aleksei Aksimentiev, Min Chen, Charles M. Schroeder, Olgica Milenković

This paper introduces an extended 11-letter DNA alphabet for data storage, using nanopore readout and neural networks to improve accuracy and density.

Nano Letters · Feb 25, 2022Peer-reviewedSynthetic Biology

Impact of lossy compression of nanopore raw signal data on basecalling and consensus accuracy

Shubham Chandak, Kedar Tatwawadi, Srivatsan Sridhar, Tsachy Weissman

This study evaluates the impact of lossy compression on nanopore sequencing data, showing minimal effects on basecalling and consensus accuracy while significantly reducing storage needs.

Bioinformatics · Nov 24, 2020Peer-reviewedBioinformatics