A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

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

doi:10.1101/2022.11.20.517297

New Results

A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

View ORCID ProfileGagandeep Singh, Mohammed Alser, Alireza Khodamoradi, Kristof Denolf, Can Firtina, Meryem Banu Cavlak, Henk Corporaal, Onur Mutlu

doi: https://doi.org/10.1101/2022.11.20.517297

Gagandeep Singh

aETH Zürich

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for Gagandeep Singh
For correspondence: gagan.posted@gmail.com

Mohammed Alser

aETH Zürich

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Alireza Khodamoradi

bAMD

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Kristof Denolf

bAMD

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Can Firtina

aETH Zürich

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Meryem Banu Cavlak

aETH Zürich

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Henk Corporaal

cEindhoven University of Technology

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Onur Mutlu

aETH Zürich

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Abstract
Full Text
Info/History
Metrics
Data/Code
Preview PDF

https://bridges.monash.edu/articles/dataset/Raw_fast5s/7676174
https://bridges.monash.edu/articles/dataset/Reference_genomes/7676135

View the discussion thread.

PreviousNext

Posted December 08, 2022.

Download PDF

Data/Code

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Your Email *

Your Name *

Send To *

Enter multiple addresses on separate lines or separate them with commas.

You are going to email the following A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

Message Subject (Your Name) has forwarded a page to you from bioRxiv

Message Body (Your Name) thought you would like to see this page from the bioRxiv website.

Your Personal Message

CAPTCHA

This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

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

bioRxiv 2022.11.20.517297; doi: https://doi.org/10.1101/2022.11.20.517297

Share This Article:

Citation Tools

A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers

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

bioRxiv 2022.11.20.517297; doi: https://doi.org/10.1101/2022.11.20.517297

Citation Manager Formats

BibTeX
Bookends
EasyBib
EndNote (tagged)
EndNote 8 (xml)
Medlars
Mendeley
Papers
RefWorks Tagged
Ref Manager
RIS
Zotero

Tweet Widget
Facebook Like
Google Plus One

Subject Area

Genomics

Subject Areas

All Articles

Animal Behavior and Cognition (4224)
Biochemistry (9101)
Bioengineering (6748)
Bioinformatics (23932)
Biophysics (12081)
Cancer Biology (9489)
Cell Biology (13727)
Clinical Trials (138)
Developmental Biology (7614)
Ecology (11655)
Epidemiology (2066)
Evolutionary Biology (15475)
Genetics (10614)
Genomics (14291)
Immunology (9455)
Microbiology (22773)
Molecular Biology (9069)
Neuroscience (48836)
Paleontology (354)
Pathology (1479)
Pharmacology and Toxicology (2560)
Physiology (3821)
Plant Biology (8307)
Scientific Communication and Education (1467)
Synthetic Biology (2289)
Systems Biology (6168)
Zoology (1297)