Author

Meryem Banu Cavlak

ETH ZurichORCID 0000-0003-4475-6945Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3 Genomics· 1

Signature Assays, Organisms & Methods

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Assay:long-read sequencing· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Approach:experimental assay· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Can FırtınaiD· 4 shared Onur MutluiD· 4 shared Gagandeep SinghiD· 3 shared Mohammed AlseriD· 3 shared Can AlkaniD· 2 shared Joël LindeggeriD· 2 shared Nika Mansouri GhiasiiD· 2 shared Alireza KhodamoradiiD· 1 shared

Activity by Year

2022-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 34 mutual co-author links

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4 shared papersBioinformatics

Can FırtınaORCID

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4 papers

Recent·Most cited

TargetCall: Eliminating the Wasted Computation in Basecalling via Pre-Basecalling Filtering

Meryem Banu Cavlak, Gagandeep Singh, Mohammed Alser, Can Fırtına, Joël Lindegger, Mohammad Sadrosadati, Nika Mansouri Ghiasi, Can Alkan, Onur Mutlu

TargetCall filters out off-target reads before basecalling to reduce computational waste, improving basecalling performance and efficiency.

Frontiers in Genetics · Oct 28, 2024Peer-reviewedBioinformatics

AirLift: A Fast and Comprehensive Technique for Remapping Alignments between Reference Genomes

Jeremie S. Kim, Can Fırtına, Meryem Banu Cavlak, Damla Senol Cali, Nastaran Hajinazar, Mohammed Alser, Can Alkan, Onur Mutlu

AirLift remaps reads from one reference genome to another efficiently and accurately, reducing execution time by up to 27.4x compared to full mapping.

IEEE Transactions on Computational Biology and Bioinformatics · Aug 19, 2024Peer-reviewedBioinformatics

RawHash: Enabling Fast and Accurate Real-Time Analysis of Raw Nanopore Signals for Large Genomes

Can Fırtına, Nika Mansouri Ghiasi, Joël Lindegger, Gagandeep Singh, Meryem Banu Cavlak, Haiyu Mao, Onur Mutlu

RawHash enables fast and accurate real-time analysis of nanopore raw signals for large genomes, outperforming existing methods in throughput and accuracy.

Bioinformatics · May 24, 2023Peer-reviewedBioinformatics

A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

Gagandeep Singh, Mohammed Alser, Kristof Denolf, Can Fırtına, Alireza Khodamoradi, Meryem Banu Cavlak, Henk Corporaal, Onur Mutlu

This paper introduces RUBICON, a framework for designing efficient deep learning-based genomic basecallers, and demonstrates its effectiveness with RUBICALL, a hardware-optimized mixed-precision basecaller that outperforms existing methods.

bioRxiv · Nov 20, 2022 · PreprintGenomics