Scalable, Real-Time, and Information-Rich Sequence Search Over SRA

Jun 1, 2022
Comp Bio
Prashant Pandey
Prashant Pandey
Assistant Professor

My research interests lie at the intersection of Systems and Algorithms. I design and build theoretically well-founded data structures for big data problems in computational biology, streaming, and file systems.

Publications

An Incrementally Updatable and Scalable System for Large-Scale Sequence Search using the Bentley-Saxe Transformation
Fatemeh Almodaresi, Jamshed Khan, Sergey Madaminov, Michael Ferdman, Rob Johnson, Prashant Pandey, Rob Patro
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VariantStore: an index for large-scale genomic variant search
Prashant Pandey, Yinjie Gao, Carl Kingsford
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Distributed-Memory k-mer Counting on GPUs
Israt Nisa, Prashant Pandey, Marquita Ellis, Leonid Oliker, Aydin Buluc, Katherine Yelick
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Locality Sensitive Hashing for the Edit Distance
Guillaume Marcais, Dan DeBlasio, Prashant Pandey, Carl Kingsford
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An Efficient, Scalable and Exact Representation of High-Dimensional Color Information Enabled via de Bruijn Graph Search Problem
Fatemeh Almodaresi, Prashant Pandey, Michael Ferdman, Rob Johnson, Rob Patro
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Mantis: A Fast, Small, and Exact Large-Scale Sequence-Search Index
Prashant Pandey, Fatemeh Almodaresi, Michael A. Bender, Michael Ferdman, Rob Johnson, and Rob Patro
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Rainbowfish: A Succinct Colored de Bruijn Graph Representation
Fatemeh Almodaresi, Prashant Pandey, and Rob Patro
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deBGR: An Efficient and Near-Exact Representation of the Weighted de Bruijn Graph
Prashant Pandey, Michael A. Bender, Rob Johnson, and Rob Patro
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Squeakr: An Exact and Approximate K-Mer Counting System
Prashant Pandey, Michael A. Bender, Rob Johnson, and Rob Patro
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