Searching journal content for articles similar to Horsfield et al. 35 (4): 1025.

Displaying results 1-10 of 5739

For checked items

view abstracts
download to citation manager

Select this article
Method: Graph-based deep reinforcement learning for haplotype assembly with Ralphi
- Enzo Battistella,
- Anant Maheshwari,
- Barış Ekim,
- Bonnie Berger,
- and Victoria Popic
Genome Res. December 2025 35: 2617-2625; Published in Advance November 14, 2025, doi:10.1101/gr.280569.125
...and an actor-critic RL model to learn the read-to-haplotype assignment algorithm based on the MFC reward. We used a large set of fragment graph topologies derived from s from a diverse set of populations included in the 1000 Genomes Project to train Ralphi. To demonstrate the generalizability and adaptability...
Select this article
Method: Enhancing nanopore adaptive sampling for PromethION using readfish at scale
- Rory Munro,
- Alexander Payne,
- Nadine Holmes,
- Chris Moore,
- Inswasti Cahyani,
- and Matthew Loose
Genome Res. April 2025 35: 877-885; Published in Advance January 30, 2025, doi:10.1101/gr.279329.124
.... 2016) allows for the optimization of sequencing efficiency, reducing sequencing capacity wasted on DNA fragments that do not provide utility when answering a given biological question. The application of adaptive sampling to nanopore sequencing can address long-standing challenges inherent to other...
OPEN ACCESS ARTICLE
Select this article
Method: Graph-based self-supervised learning for repeat detection in metagenomic assembly
- Ali Azizpour,
- Advait Balaji,
- Todd J. Treangen,
- and Santiago Segarra
Genome Res. September 2024 34: 1468-1476; Published in Advance July 19, 2024, doi:10.1101/gr.279136.124
.... Graph-based algorithms can effectively represent the interconnections and overlapping patterns within s (Koutrouli et al. 2020), in which the nodes in the graph represent unique DNA sequences. Because of the tangled nature of repeated sequences within the assembly graph, exploiting graph structure...
Select this article
Method: Accurate and fast graph-based pangenome annotation and clustering with ggCaller
- Samuel T. Horsfield,
- Gerry Tonkin-Hill,
- Nicholas J. Croucher,
- and John A. Lees
Genome Res. September 2023 33: 1622-1637; Published in Advance August 24, 2023, doi:10.1101/gr.277733.123
...Accurate and fast graph-based pan annotation and clustering with ggCaller Samuel T. Horsfield1,2, Gerry Tonkin-Hill3, Nicholas J. Croucher1,4 and John A. Lees1,2,4 1MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London W12...
OPEN ACCESS ARTICLE
Select this article
Research: Assessing the readiness of Oxford Nanopore sequencing for clinical genomics applications
- Judith Arres,
- Santosh Elavalli,
- Shalini Behl,
- Daniel Matias Sanchez,
- Ayesha Al Ali,
- Abdelrahman Ahmed Yehia Abdelaziz Saad,
- Azza Attia,
- Cyla Minas,
- Sharika Pariyachery,
- Shariq Ahmed,
- Fatmah Aldhuhoori,
- Nitu Thulasidharan,
- Gurunath Katagi,
- Omar Soliman,
- Shilp Purohit,
- Vinay Kusuma,
- Raony Cardenas,
- Thyago Cardoso,
- Luis F. Paulin,
- Philippe Sanio,
- Joseph Mafofo,
- Haiguo Wu,
- Val Zvereff,
- Albarah El-Khani,
- Fahed Al Marzooqi,
- Tiago R. Magalhães,
- Fritz J. Sedlazeck,
- and Javier Quilez
Genome Res. March 2026 36: 460-471; Published in Advance February 11, 2026, doi:10.1101/gr.280134.124
...an optimized analysis pipeline (https://github.com/juditharres/Nanopore4Clinics) for comprehensive variant detection. This pipeline balances comprehensiveness and efficiency, ensuring fast turnaround times for both clinical cases and large-scale population studies. To establish ONT's performance and validate...
Select this article
Method: Real-time analysis and visualization of nanopore metagenomic samples with MARTi
- Ned Peel,
- Samuel Martin,
- Darren Heavens,
- Douglas W. Yu,
- Matthew D. Clark,
- and Richard M. Leggett
Genome Res. November 2025 35: 2488-2500; Published in Advance October 27, 2025, doi:10.1101/gr.280550.125
...increasingly used for detecting and characterizing pathogenic organisms (Taxt et al. 2020), outbreak surveillance (Quick et al. 2016; Yakovleva et al. 2022), and in situ sequencing (Burton et al. 2020; Latorre-Pérez et al. 2021), that is, taking the sequencer to the sample. Significantly, the ONT platform...
OPEN ACCESS ARTICLE
Select this article
Method: EnDeep4mC predicts DNA N⁴-methylcytosine sites using a dual-adaptive feature encoding framework in deep ensembles
- Shuyu Zhang,
- Quan Zou,
- Mengting Niu,
- Zhibin Lv,
- Antony Stalin,
- and Ximei Luo
Genome Res. March 2026 36: 589-599; Published in Advance February 17, 2026, doi:10.1101/gr.280977.125
..., requires efficient computational detection methods due to experimental limitations. Although machine learning predictors have been proposed, their performance could be enhanced through systematic optimization of feature encoding schemes. Here, we propose EnDeep4mC, a dual-adaptive framework integrating...
OPEN ACCESS ARTICLE
Select this article
Method: Measuring X-Chromosome inactivation skew for X-linked diseases with adaptive nanopore sequencing
- Sena A. Gocuk,
- James Lancaster,
- Shian Su,
- Jasleen K. Jolly,
- Thomas L. Edwards,
- Doron G. Hickey,
- Matthew E. Ritchie,
- Marnie E. Blewitt,
- Lauren N. Ayton,
- and Quentin Gouil
Genome Res. November 2024 34: 1954-1965; Published in Advance September 16, 2024, doi:10.1101/gr.279396.124
...on long-read whole- sequencing to simultaneously identify variants and investigate the contribution of skew to X-linked diseases in females. We used the Oxford Nanopore Technologies PromethION 24 platform and its adaptive sampling capacity to enrich X Chromosome reads. We sequenced peripheral samples...
Select this article
Method: A new compression strategy to reduce the size of nanopore sequencing data
- Kavindu Jayasooriya,
- Sasha P. Jenner,
- Pasindu Marasinghe,
- Udith Senanayake,
- Hassaan Saadat,
- David Taubman,
- Roshan Ragel,
- Hasindu Gamaarachchi,
- and Ira W. Deveson
Genome Res. July 2025 35: 1574-1582; Published in Advance May 15, 2025, doi:10.1101/gr.280090.124
...the size of the chain of sequential signal values that make up a raw nanopore read. Despite these savings, signal data in both formats remain ∼10× larger than their corresponding basecalled reads, or ∼1.7 TiB for a typical human sample at ∼40× coverage (Supplemental Table S1).The large size of raw ONT...
OPEN ACCESS ARTICLE
Select this article
Research: Nanopore direct RNA sequencing reveals METTL2A-mediated m³C sites in poly(A) RNA
- Shuhei Mitsutomi,
- Anzu Sugawara,
- Masahide Seki,
- Yutaka Suzuki,
- Sotaro Miyao,
- Haozhe Du,
- Kenji Takahashi,
- Yusuke Mizukami,
- Kenzui Taniue,
- and Nobuyoshi Akimitsu
Genome Res. November 2025 35: 2406-2417; Published in Advance October 30, 2025, doi:10.1101/gr.280269.124
..., long-read sequencing-based methods, using single-molecule real-time (SMRT) or nanopore sequencing technology, can directly detect modified bases, eliminating the need for such preprocessing (Moshitch-Moshkovitz et al. 2022; Kong et al. 2023). The SMRT sequencing platform has been adapted for direct RNA...

For checked items

view abstracts
download to citation manager

Searching journal content for articles similar to Horsfield et al. 35 (4): 1025.

Search Results

Modify Results

This search

Preprint Server

Current Issue

In This Issue

Citation format:
Results / page:
Results order: