Analysis of amino acid sequences with artificial neural networks

被引:1
|
作者
Wrede, P
Schneider, G
Schuchhardt, J
Muller, G
机构
[1] Freie Universität Berlin, Univ. Klin. Benjamin Franklin, Inst. Med./Tech. Physik L., D-12207 Berlin
关键词
D O I
10.1002/ciuz.19960300403
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Molecular bioinformatics is of increasing importance for the analysis of biological macromolecules like nucleic acids and proteins. For several years artificial neural networks have been of special attraction for these purposes. An overview of the function and architecture of neural networks is given and major fields of application are presented. The design of biologically active peptides is discussed in detail.
引用
收藏
页码:172 / 181
页数:10
相关论文
共 50 条
  • [1] Analysis of Amino Acid Mixtures by Voltammetric Electronic Tongues and Artificial Neural Networks
    Faura, Georgina
    Gonzalez-Calabuig, Andreu
    del Valle, Manel
    ELECTROANALYSIS, 2016, 28 (08) : 1894 - 1900
  • [2] Artificial Neural Networks for Predicting 3D Protein Shapes from Amino Acid Sequences
    Viktor, Herna L.
    Paquet, Eric
    Zhao, Jing
    2013 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2013,
  • [3] ANALYSIS AND DESIGN OF AMINO-ACID-SEQUENCES BY NEURAL NETWORKS AND SIMULATED MOLECULAR EVOLUTION
    WREDE, P
    SCHUCHHARDT, J
    TODT, T
    SCHNEIDER, G
    PROTEIN ENGINEERING, 1995, 8 : 10 - 10
  • [4] AMINO-ACID-SEQUENCE ANALYSIS AND DESIGN BY ARTIFICIAL NEURAL NETWORKS AND SIMULATED MOLECULAR EVOLUTION - AN EVALUATION
    SCHNEIDER, G
    SCHUCHHARDT, J
    WREDE, P
    ENDOCYTOBIOSIS AND CELL RESEARCH, 1995, 11 (01): : 1 - 18
  • [5] Convolutional neural networks with image representation of amino acid sequences for protein function prediction
    Sara, Samia Tasnim
    Hasan, Md Mehedi
    Ahmad, Ahsan
    Shatabda, Swakkhar
    COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2021, 92
  • [6] Structure optimization of an artificial neural filter detecting membrane-spanning amino acid sequences
    Lohmann, R
    Schneider, G
    Wrede, P
    BIOPOLYMERS, 1996, 38 (01) : 13 - 29
  • [7] Combining Artificial Neural Networks and GOR-V Information Theory to Predict Protein Secondary Structure from Amino Acid Sequences
    Subair, Saad Osman Abdalla
    Deris, Safaai
    INTERNATIONAL JOURNAL OF INTELLIGENT INFORMATION TECHNOLOGIES, 2005, 1 (04) : 53 - 72
  • [8] Artificial neural networks for prediction of mycobacterial promoter sequences
    Kalate, RN
    Tambe, SS
    Kulkarni, BD
    COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2003, 27 (06) : 555 - 564
  • [9] Artificial Neural Networks Generated by Low Discrepancy Sequences
    Keller, Alexander
    Van Keirsbilck, Matthijs
    MONTE CARLO AND QUASI-MONTE CARLO METHODS, MCQMC 2020, 2022, 387 : 291 - 311
  • [10] PREDICTION OF STRUCTURAL AND FUNCTIONAL FEATURES OF PROTEIN AND NUCLEIC-ACID SEQUENCES BY ARTIFICIAL NEURAL NETWORKS
    HIRST, JD
    STERNBERG, MJE
    BIOCHEMISTRY, 1992, 31 (32) : 7211 - 7218