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 *

170 related articles for article (PubMed ID: 10743560)

  • 21. PaleAle 5.0: prediction of protein relative solvent accessibility by deep learning.
    Kaleel M; Torrisi M; Mooney C; Pollastri G
    Amino Acids; 2019 Sep; 51(9):1289-1296. PubMed ID: 31388850
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A hybrid genetic-neural system for predicting protein secondary structure.
    Armano G; Mancosu G; Milanesi L; Orro A; Saba M; Vargiu E
    BMC Bioinformatics; 2005 Dec; 6 Suppl 4(Suppl 4):S3. PubMed ID: 16351752
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Dimensionality reduction for protein secondary structure and solvent accesibility prediction.
    Aydin Z; Kaynar O; Görmez Y
    J Bioinform Comput Biol; 2018 Oct; 16(5):1850020. PubMed ID: 30353781
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Statistical geometry based prediction of nonsynonymous SNP functional effects using random forest and neuro-fuzzy classifiers.
    Barenboim M; Masso M; Vaisman II; Jamison DC
    Proteins; 2008 Jun; 71(4):1930-9. PubMed ID: 18186470
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction.
    Torrisi M; Kaleel M; Pollastri G
    Sci Rep; 2019 Aug; 9(1):12374. PubMed ID: 31451723
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.
    Babaei S; Geranmayeh A; Seyyedsalehi SA
    Comput Methods Programs Biomed; 2010 Dec; 100(3):237-47. PubMed ID: 20472322
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Protein structural motif prediction in multidimensional phi-psi space leads to improved secondary structure prediction.
    Mooney C; Vullo A; Pollastri G
    J Comput Biol; 2006 Oct; 13(8):1489-502. PubMed ID: 17061924
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Accurate contact predictions using covariation techniques and machine learning.
    Kosciolek T; Jones DT
    Proteins; 2016 Sep; 84 Suppl 1(Suppl Suppl 1):145-51. PubMed ID: 26205532
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Protein secondary structure prediction using nearest-neighbor methods.
    Yi TM; Lander ES
    J Mol Biol; 1993 Aug; 232(4):1117-29. PubMed ID: 8371270
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A novel approach to the recognition of protein architecture from sequence using Fourier analysis and neural networks.
    Shepherd AJ; Gorse D; Thornton JM
    Proteins; 2003 Feb; 50(2):290-302. PubMed ID: 12486723
    [TBL] [Abstract][Full Text] [Related]  

  • 31. NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.
    Petersen B; Lundegaard C; Petersen TN
    PLoS One; 2010 Nov; 5(11):e15079. PubMed ID: 21152409
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Matching protein beta-sheet partners by feedforward and recurrent neural networks.
    Baldi P; Pollastri G; Andersen CA; Brunak S
    Proc Int Conf Intell Syst Mol Biol; 2000; 8():25-36. PubMed ID: 10977063
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Improved prediction of the number of residue contacts in proteins by recurrent neural networks.
    Pollastri G; Baldi P; Fariselli P; Casadio R
    Bioinformatics; 2001; 17 Suppl 1():S234-42. PubMed ID: 11473014
    [TBL] [Abstract][Full Text] [Related]  

  • 34. LGANN: a parallel system combining a local genetic algorithm and neural networks for the prediction of secondary structure of proteins.
    Vivarelli F; Giusti G; Villani M; Campanini R; Fariselli P; Compiani M; Casadio R
    Comput Appl Biosci; 1995 Jun; 11(3):253-60. PubMed ID: 7583693
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Peptides secondary structure prediction with neural networks: a criterion for building appropriate learning sets.
    Ruggiero C; Sacile R; Rauch G
    IEEE Trans Biomed Eng; 1993 Nov; 40(11):1114-21. PubMed ID: 8307594
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Computational prediction of secondary and supersecondary structures.
    Chen K; Kurgan L
    Methods Mol Biol; 2013; 932():63-86. PubMed ID: 22987347
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks.
    Fang C; Shang Y; Xu D
    Sci Rep; 2018 Oct; 8(1):15741. PubMed ID: 30356073
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Multifaceted analysis of training and testing convolutional neural networks for protein secondary structure prediction.
    Shapovalov M; Dunbrack RL; Vucetic S
    PLoS One; 2020; 15(5):e0232528. PubMed ID: 32374785
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.
    Wang S; Peng J; Ma J; Xu J
    Sci Rep; 2016 Jan; 6():18962. PubMed ID: 26752681
    [TBL] [Abstract][Full Text] [Related]  

  • 40. PSSM-based prediction of DNA binding sites in proteins.
    Ahmad S; Sarai A
    BMC Bioinformatics; 2005 Feb; 6():33. PubMed ID: 15720719
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.