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BasecRAWller: Streaming Nanopore Basecalling Directly from Raw Signal

https://doi.org/10.1101/133058
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1038/nbt.4060openalex-snapshot
Nanopore sequencing and assembly of a human genome with ultra-long reads
inferredcites →https://doi.org/10.1038/nmeth.3930openalex-snapshot
Real-time selective sequencing using nanopore technology
inferredcites →https://doi.org/10.1093/bioinformatics/btw569openalex-snapshot
Nanocall: an open source basecaller for Oxford Nanopore sequencing data
inferredcites →https://doi.org/10.1101/094672openalex-snapshot
De novo Identification of DNA Modifications Enabled by Genome-Guided Nanopore Signal Processing
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot
Long Short-Term Memory
inferredcites →https://doi.org/10.1371/journal.pone.0178751openalex-snapshot
DeepNano: Deep recurrent neural networks for base calling in MinION nanopore reads
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-981-15-0690-1_19openalex-snapshot
Genomics and Transcriptomics Advance in Plant Sciences
inferred← citeshttps://doi.org/10.1016/j.csbj.2024.09.016openalex-snapshot
BaseNet: A transformer-based toolkit for nanopore sequencing signal decoding
inferred← citeshttps://doi.org/10.1016/j.tig.2021.09.001openalex-snapshot
Beyond sequencing: machine learning algorithms extract biology hidden in Nanopore signal data
inferred← citeshttps://doi.org/10.1016/j.xinn.2021.100153openalex-snapshot
Applications and potentials of nanopore sequencing in the (epi)genome and (epi)transcriptome era
inferred← citeshttps://doi.org/10.1038/s41587-021-01108-xopenalex-snapshot
Nanopore sequencing technology, bioinformatics and applications
inferred← citeshttps://doi.org/10.1038/s41598-026-41649-2openalex-snapshot
Low power reprogrammable DNA basecaller with an efficient HMM accelerator for real time nanopore sequencing
inferred← citeshttps://doi.org/10.1063/5.0037938openalex-snapshot
Deep learning for nanopore ionic current blockades
inferred← citeshttps://doi.org/10.1093/bioinformatics/btaa237openalex-snapshot
Portable nanopore analytics: are we there yet?
inferred← citeshttps://doi.org/10.1093/bioinformatics/bty223openalex-snapshot
DeepSimulator: a deep simulator for Nanopore sequencing
inferred← citeshttps://doi.org/10.1093/gigascience/giy037openalex-snapshot
Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning
inferred← citeshttps://doi.org/10.1093/hmg/ddx287openalex-snapshot
The potential impact of nanopore sequencing on human genetics
inferred← citeshttps://doi.org/10.1101/2020.02.25.956771openalex-snapshot
Pair consensus decoding improves accuracy of neural network basecallers for nanopore sequencing
inferred← citeshttps://doi.org/10.1101/2020.07.25.220855openalex-snapshot
NanoReviser: An Error-correction Tool for Nanopore Sequencing Based on a Deep Learning Algorithm
inferred← citeshttps://doi.org/10.1101/2020.11.09.374165openalex-snapshot
An End-to-end Oxford Nanopore Basecaller Using Convolution-augmented Transformer
inferred← citeshttps://doi.org/10.1101/2022.10.19.512968openalex-snapshot
Language-Informed Basecalling Architecture for Nanopore Direct RNA Sequencing
inferred← citeshttps://doi.org/10.1101/694919openalex-snapshot
Nanopore base-calling from a perspective of instance segmentation
inferred← citeshttps://doi.org/10.1109/bibm49941.2020.9313290openalex-snapshot
An End-to-end Oxford Nanopore Basecaller Using Convolution-augmented Transformer
inferred← citeshttps://doi.org/10.1109/tbme.2022.3150420openalex-snapshot
Mixed-Weight Neural Bagging for Detecting $m^6A$ Modifications in SARS-CoV-2 RNA Sequencing
inferred← citeshttps://doi.org/10.1111/dgd.12608openalex-snapshot
Nanopore sequencing: Review of potential applications in functional genomics
inferred← citeshttps://doi.org/10.1186/s12859-020-3459-0openalex-snapshot
Nanopore basecalling from a perspective of instance segmentation
inferred← citeshttps://doi.org/10.1186/s12859-023-05151-0openalex-snapshot
DeepSelectNet: deep neural network based selective sequencing for oxford nanopore sequencing
inferred← citeshttps://doi.org/10.1186/s13059-018-1462-9openalex-snapshot
From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy
inferred← citeshttps://doi.org/10.1186/s13059-019-1727-yopenalex-snapshot
Performance of neural network basecalling tools for Oxford Nanopore sequencing
inferred← citeshttps://doi.org/10.1186/s13059-020-02255-1openalex-snapshot
Pair consensus decoding improves accuracy of neural network basecallers for nanopore sequencing
inferred← citeshttps://doi.org/10.1186/s13059-023-02903-2openalex-snapshot
Comprehensive benchmark and architectural analysis of deep learning models for nanopore sequencing basecalling
inferred← citeshttps://doi.org/10.1261/rna.063503.117openalex-snapshot
The RNA modification landscape in human disease
inferred← citeshttps://doi.org/10.12688/f1000research.12012.2openalex-snapshot
The long reads ahead: de novo genome assembly using the MinION
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1006583openalex-snapshot
Deepbinner: Demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks
inferred← citeshttps://doi.org/10.18174/577300openalex-snapshot
From squiggle to sequence: bioinformatics in the era of single-molecule biopolymer analysis
inferred← citeshttps://doi.org/10.25781/kaust-2w40wopenalex-snapshot
Towards Structured Prediction in Bioinformatics with Deep Learning
inferred← citeshttps://doi.org/10.3389/fgene.2019.01332openalex-snapshot
Causalcall: Nanopore Basecalling Using a Temporal Convolutional Network
inferred← citeshttps://doi.org/10.3389/fgene.2020.00900openalex-snapshot
NanoReviser: An Error-Correction Tool for Nanopore Sequencing Based on a Deep Learning Algorithm
inferred← citeshttps://doi.org/10.3389/fgene.2022.1037134openalex-snapshot
Modification mapping by nanopore sequencing
inferred← citeshttps://doi.org/10.3390/bios11070214openalex-snapshot
Nanopore Technology and Its Applications in Gene Sequencing
inferred← citeshttps://doi.org/10.3390/nano12183135openalex-snapshot
Nanopore Detection Assisted DNA Information Processing
inferred← citeshttps://doi.org/10.3390/s22062275openalex-snapshot
Basecalling Using Joint Raw and Event Nanopore Data Sequence-to-Sequence Processing
inferred← citeshttps://doi.org/10.3390/s23156787openalex-snapshot
Estimated Nucleotide Reconstruction Quality Symbols of Basecalling Tools for Oxford Nanopore Sequencing
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