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 *

106 related articles for article (PubMed ID: 30991099)

  • 1. Hybrid model for efficient prediction of poly(A) signals in human genomic DNA.
    Albalawi F; Chahid A; Guo X; Albaradei S; Magana-Mora A; Jankovic BR; Uludag M; Van Neste C; Essack M; Laleg-Kirati TM; Bajic VB
    Methods; 2019 Aug; 166():31-39. PubMed ID: 30991099
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Omni-PolyA: a method and tool for accurate recognition of Poly(A) signals in human genomic DNA.
    Magana-Mora A; Kalkatawi M; Bajic VB
    BMC Genomics; 2017 Aug; 18(1):620. PubMed ID: 28810905
    [TBL] [Abstract][Full Text] [Related]  

  • 3. SANPolyA: a deep learning method for identifying Poly(A) signals.
    Yu H; Dai Z
    Bioinformatics; 2020 Apr; 36(8):2393-2400. PubMed ID: 31904817
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DeeReCT-PolyA: a robust and generic deep learning method for PAS identification.
    Xia Z; Li Y; Zhang B; Li Z; Hu Y; Chen W; Gao X
    Bioinformatics; 2019 Jul; 35(14):2371-2379. PubMed ID: 30500881
    [TBL] [Abstract][Full Text] [Related]  

  • 5. POLYAR, a new computer program for prediction of poly(A) sites in human sequences.
    Akhtar MN; Bukhari SA; Fazal Z; Qamar R; Shahmuradov IA
    BMC Genomics; 2010 Nov; 11():646. PubMed ID: 21092114
    [TBL] [Abstract][Full Text] [Related]  

  • 6. DeepGSR: an optimized deep-learning structure for the recognition of genomic signals and regions.
    Kalkatawi M; Magana-Mora A; Jankovic B; Bajic VB
    Bioinformatics; 2019 Apr; 35(7):1125-1132. PubMed ID: 30184052
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences.
    Kalkatawi M; Rangkuti F; Schramm M; Jankovic BR; Kamau A; Chowdhary R; Archer JA; Bajic VB
    Bioinformatics; 2012 Jan; 28(1):127-9. PubMed ID: 22088842
    [TBL] [Abstract][Full Text] [Related]  

  • 8. DeepPASTA: deep neural network based polyadenylation site analysis.
    Arefeen A; Xiao X; Jiang T
    Bioinformatics; 2019 Nov; 35(22):4577-4585. PubMed ID: 31081512
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Splice2Deep: An ensemble of deep convolutional neural networks for improved splice site prediction in genomic DNA.
    Albaradei S; Magana-Mora A; Thafar M; Uludag M; Bajic VB; Gojobori T; Essack M; Jankovic BR
    Gene; 2020 Dec; 763S():100035. PubMed ID: 34493371
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Poly(A) motif prediction using spectral latent features from human DNA sequences.
    Xie B; Jankovic BR; Bajic VB; Song L; Gao X
    Bioinformatics; 2013 Jul; 29(13):i316-25. PubMed ID: 23813000
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Complex Selection on Human Polyadenylation Signals Revealed by Polymorphism and Divergence Data.
    Kainov YA; Aushev VN; Naumenko SA; Tchevkina EM; Bazykin GA
    Genome Biol Evol; 2016 Jul; 8(6):1971-9. PubMed ID: 27324920
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prediction of non-canonical polyadenylation signals in human genomic sequences based on a novel algorithm using a fuzzy membership function.
    Kamasawa M; Horiuchi J
    J Biosci Bioeng; 2009 May; 107(5):569-78. PubMed ID: 19393560
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks.
    Avsec Ž; Barekatain M; Cheng J; Gagneur J
    Bioinformatics; 2018 Apr; 34(8):1261-1269. PubMed ID: 29155928
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Implications of polyadenylation in health and disease.
    Curinha A; Oliveira Braz S; Pereira-Castro I; Cruz A; Moreira A
    Nucleus; 2014; 5(6):508-19. PubMed ID: 25484187
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genome-wide identification of dominant polyadenylation hexamers for use in variant classification.
    Shiferaw HK; Hong CS; Cooper DN; Johnston JJ; Nisc ; Biesecker LG
    Hum Mol Genet; 2023 Nov; 32(23):3211-3224. PubMed ID: 37606238
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Characterization and prediction of mRNA alternative polyadenylation sites in rice genes.
    Wu X; Zhao C; Su Y
    Biomed Mater Eng; 2014; 24(6):3779-85. PubMed ID: 25227094
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species.
    Zheng Y; Wang H; Zhang Y; Gao X; Xing EP; Xu M
    PLoS Comput Biol; 2020 Nov; 16(11):e1008297. PubMed ID: 33151940
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identification and characterization of polyadenylation signal (PAS) variants in human genomic sequences based on modified EST clustering.
    Kamasawa M; Horiuchi J
    In Silico Biol; 2008; 8(3-4):347-61. PubMed ID: 19032167
    [TBL] [Abstract][Full Text] [Related]  

  • 19. [Analysis, identification and correction of some errors of model refseqs appeared in NCBI Human Gene Database by in silico cloning and experimental verification of novel human genes].
    Zhang DL; Ji L; Li YD
    Yi Chuan Xue Bao; 2004 May; 31(5):431-43. PubMed ID: 15478601
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Chromatin accessibility prediction via a hybrid deep convolutional neural network.
    Liu Q; Xia F; Yin Q; Jiang R
    Bioinformatics; 2018 Mar; 34(5):732-738. PubMed ID: 29069282
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.