USING DEEP LEARNING NEURAL NETWORKS FOR INVERSE PROTEIN FOLDING PREDICTIONS

被引:0
|
作者
La Fleur, Alyssa [1 ]
Almaw, Tersa [1 ]
Ojennus, Deanna [1 ]
Jones, Kent [1 ]
机构
[1] Whitworth Univ, Spokane, WA USA
关键词
D O I
暂无
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
ABS318
引用
收藏
页码:139 / 139
页数:1
相关论文
共 50 条
  • [21] DE-NOVO AND INVERSE FOLDING PREDICTIONS OF PROTEIN-STRUCTURE AND DYNAMICS
    GODZIK, A
    KOLINSKI, A
    SKOLNICK, J
    [J]. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 1993, 7 (04) : 397 - 438
  • [22] Deep neural networks for accurate predictions of crystal stability
    Weike Ye
    Chi Chen
    Zhenbin Wang
    Iek-Heng Chu
    Shyue Ping Ong
    [J]. Nature Communications, 9
  • [23] Surrogate optimization of deep neural networks for groundwater predictions
    Mueller, Juliane
    Park, Jangho
    Sahu, Reetik
    Varadharajan, Charuleka
    Arora, Bhavna
    Faybishenko, Boris
    Agarwal, Deborah
    [J]. JOURNAL OF GLOBAL OPTIMIZATION, 2021, 81 (01) : 203 - 231
  • [24] Deep neural networks for accurate predictions of crystal stability
    Ye, Weike
    Chen, Chi
    Wang, Zhenbin
    Chu, Iek-Heng
    Ong, Shyue Ping
    [J]. NATURE COMMUNICATIONS, 2018, 9
  • [25] Surrogate optimization of deep neural networks for groundwater predictions
    Juliane Müller
    Jangho Park
    Reetik Sahu
    Charuleka Varadharajan
    Bhavna Arora
    Boris Faybishenko
    Deborah Agarwal
    [J]. Journal of Global Optimization, 2021, 81 : 203 - 231
  • [26] An Adversarial Approach for Explaining the Predictions of Deep Neural Networks
    Rahnama, Arash
    Tseng, Andrew
    [J]. 2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 3247 - 3256
  • [27] Adaptive Inverse Control Using an Online Learning Algorithm for Neural Networks
    Luis Calvo-Rolle, Jose
    Fontenla-Romero, Oscar
    Perez-Sanchez, Beatriz
    Guijarro-Berdinas, Bertha
    [J]. INFORMATICA, 2014, 25 (03) : 401 - 414
  • [28] Deep Neural Network Based Predictions of Protein Interactions Using Primary Sequences
    Li, Hang
    Gong, Xiu-Jun
    Yu, Hua
    Zhou, Chang
    [J]. MOLECULES, 2018, 23 (08):
  • [29] Active Training Trajectory Generation for Inverse Dynamics Model Learning with Deep Neural Networks
    Zhou, Siqi
    Schoellig, Angela P.
    [J]. 2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), 2019, : 1784 - 1790
  • [30] Harnessing protein folding neural networks for peptide–protein docking
    Tomer Tsaban
    Julia K. Varga
    Orly Avraham
    Ziv Ben-Aharon
    Alisa Khramushin
    Ora Schueler-Furman
    [J]. Nature Communications, 13