These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

169 related articles for article (PubMed ID: 37252813)

  • 1. Accelerated nanopore basecalling with SLOW5 data format.
    Samarakoon H; Ferguson JM; Gamaarachchi H; Deveson IW
    Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37252813
    [TBL] [Abstract][Full Text] [Related]  

  • 2. RODAN: a fully convolutional architecture for basecalling nanopore RNA sequencing data.
    Neumann D; Reddy ASN; Ben-Hur A
    BMC Bioinformatics; 2022 Apr; 23(1):142. PubMed ID: 35443610
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Flexible and efficient handling of nanopore sequencing signal data with slow5tools.
    Samarakoon H; Ferguson JM; Jenner SP; Amos TG; Parameswaran S; Gamaarachchi H; Deveson IW
    Genome Biol; 2023 Apr; 24(1):69. PubMed ID: 37024927
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Performance of neural network basecalling tools for Oxford Nanopore sequencing.
    Wick RR; Judd LM; Holt KE
    Genome Biol; 2019 Jun; 20(1):129. PubMed ID: 31234903
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SACall: A Neural Network Basecaller for Oxford Nanopore Sequencing Data Based on Self-Attention Mechanism.
    Huang N; Nie F; Ni P; Luo F; Wang J
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(1):614-623. PubMed ID: 33211664
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Simulation of nanopore sequencing signal data with tunable parameters.
    Gamaarachchi H; Ferguson JM; Samarakoon H; Liyanage K; Deveson IW
    Genome Res; 2024 Jun; 34(5):778-783. PubMed ID: 38692839
    [TBL] [Abstract][Full Text] [Related]  

  • 7. NanoSplicer: accurate identification of splice junctions using Oxford Nanopore sequencing.
    You Y; Clark MB; Shim H
    Bioinformatics; 2022 Aug; 38(15):3741-3748. PubMed ID: 35639973
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Fast nanopore sequencing data analysis with SLOW5.
    Gamaarachchi H; Samarakoon H; Jenner SP; Ferguson JM; Amos TG; Hammond JM; Saadat H; Smith MA; Parameswaran S; Deveson IW
    Nat Biotechnol; 2022 Jul; 40(7):1026-1029. PubMed ID: 34980914
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Basecalling Using Joint Raw and Event Nanopore Data Sequence-to-Sequence Processing.
    Napieralski A; Nowak R
    Sensors (Basel); 2022 Mar; 22(6):. PubMed ID: 35336445
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Estimated Nucleotide Reconstruction Quality Symbols of Basecalling Tools for Oxford Nanopore Sequencing.
    Kuśmirek W
    Sensors (Basel); 2023 Jul; 23(15):. PubMed ID: 37571570
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Lokatt: a hybrid DNA nanopore basecaller with an explicit duration hidden Markov model and a residual LSTM network.
    Xu X; Bhalla N; Ståhl P; Jaldén J
    BMC Bioinformatics; 2023 Dec; 24(1):461. PubMed ID: 38062356
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Pair consensus decoding improves accuracy of neural network basecallers for nanopore sequencing.
    Silvestre-Ryan J; Holmes I
    Genome Biol; 2021 Jan; 22(1):38. PubMed ID: 33468205
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Streamlining remote nanopore data access with slow5curl.
    Wong B; Ferguson JM; Do JY; Gamaarachchi H; Deveson IW
    Gigascience; 2024 Jan; 13():. PubMed ID: 38608279
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores.
    Cozzuto L; Delgado-Tejedor A; Hermoso Pulido T; Novoa EM; Ponomarenko J
    Methods Mol Biol; 2023; 2624():185-205. PubMed ID: 36723817
    [TBL] [Abstract][Full Text] [Related]  

  • 15. NanoDJ: a Dockerized Jupyter notebook for interactive Oxford Nanopore MinION sequence manipulation and genome assembly.
    Rodríguez-Pérez H; Hernández-Beeftink T; Lorenzo-Salazar JM; Roda-García JL; Pérez-González CJ; Colebrook M; Flores C
    BMC Bioinformatics; 2019 May; 20(1):234. PubMed ID: 31072312
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identifying and correcting repeat-calling errors in nanopore sequencing of telomeres.
    Tan KT; Slevin MK; Meyerson M; Li H
    Genome Biol; 2022 Aug; 23(1):180. PubMed ID: 36028900
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Poretools: a toolkit for analyzing nanopore sequence data.
    Loman NJ; Quinlan AR
    Bioinformatics; 2014 Dec; 30(23):3399-401. PubMed ID: 25143291
    [TBL] [Abstract][Full Text] [Related]  

  • 18. GAVISUNK: genome assembly validation via inter-SUNK distances in Oxford Nanopore reads.
    Dishuck PC; Rozanski AN; Logsdon GA; Porubsky D; Eichler EE
    Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36321867
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Halcyon: an accurate basecaller exploiting an encoder-decoder model with monotonic attention.
    Konishi H; Yamaguchi R; Yamaguchi K; Furukawa Y; Imoto S
    Bioinformatics; 2021 Jun; 37(9):1211-1217. PubMed ID: 33165508
    [TBL] [Abstract][Full Text] [Related]  

  • 20. WarpSTR: determining tandem repeat lengths using raw nanopore signals.
    Sitarčík J; Vinař T; Brejová B; Krampl W; Budiš J; Radvánszky J; Lucká M
    Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37326967
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.