Author

Ananth Kalyanaraman

Washington State UniversityORCID 0000-0003-3495-2264Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:genome assembly· 2 Assay:whole-genome sequencing· 2 Research Focus:clustering· 1 Approach:experimental assay· 1 Approach:graph neural network· 1 Organism:plant (other)· 1

Frequent Co-Authors

Bala KrishnamoorthyiD· 1 shared Methun KamruzzamaniD· 1 shared Oieswarya BhowmikiD· 1 shared Paola Pesántez‐CabreraiD· 1 shared Patrick S. SchnableiD· 1 shared Priyanka GhoshiD· 1 shared Sriram KrishnamoorthyiD· 1 shared Stefan Hey· 1 shared

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2017-2025 · peak 2/yr

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8 top collaborators · 7 mutual co-author links

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1 shared paperBioinformatics

Bala KrishnamoorthyORCID

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4 papers

Recent·Most cited

BioinformaticsiSciencePeer-reviewedOct 30, 2025

Tile-X: A vertex reordering approach for scalable long read assembly

Oieswarya Bhowmik, Ananth Kalyanaraman

Tile-X improves long read assembly by precomputing read ordering, enhancing scalability and efficiency without sacrificing quality.

1 citation

whole-genome sequencinggraph neural network

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BioinformaticsIEEE Transactions on Computational Biology and BioinformaticsPeer-reviewedOct 23, 2019

Hyppo-X: A Scalable Exploratory Framework for Analyzing Complex Phenomics Data

Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorthy…·Patrick S. Schnable

Hyppo-X is a framework for exploring complex phenomics data to extract hypotheses about environmental influences on phenotypic traits in plants.

12 citations

plant (other)statistical model

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BioinformaticsbioRxivPreprintJan 17, 2019

PaKman: Scalable Assembly of Large Genomes on Distributed Memory Machines

Priyanka Ghosh, Sriram Krishnamoorthy, Ananth Kalyanaraman

PaKman improves large-scale genome assembly by reducing communication and I/O overhead, achieving near-linear speedups on 8K cores and outperforming existing tools.

DOI 10.1101/523068

whole-genome sequencingstatistical model

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BioinformaticsIEEE Transactions on Computational Biology and BioinformaticsPeer-reviewedNov 22, 2017

Efficient Detection of Communities in Biological Bipartite Networks

Paola Pesántez‐Cabrera, Ananth Kalyanaraman

The paper introduces an efficient algorithm for community detection in biological bipartite networks, showing improved speed and comparable quality to existing methods.

33 citations

statistical modelclustering

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