KMS Of Academy of mathematics and systems sciences, CAS
| Molecular Sparse Representation by a 3D Ellipsoid Radial Basis Function Neural Network via L1 Regularization | |
| Gui, Sheng1,2,3; Chen, Zhaodi3; Lu, Benzhuo1,2; Chen, Minxin3 | |
| 2020-12-28 | |
| Source Publication | JOURNAL OF CHEMICAL INFORMATION AND MODELING
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| ISSN | 1549-9596 |
| Volume | 60Issue:12Pages:6054-6064 |
| Abstract | The three-dimensional structures and shapes of biomolecules provide essential information about their interactions and functions. Unfortunately, the computational cost of bio-molecular shape representation is an active challenge which increases rapidly as the number of atoms increase. Recent developments in sparse representation and deep learning have shown significant improvements in terms of time and space. A sparse representation of molecular shape is also useful in various other applications, such as molecular structure alignment, docking, and coarse-grained molecular modeling. We have developed an ellipsoid radial basis function neural network (ERBFNN) and an algorithm for sparsely representing molecular shape. To evaluate a sparse representation model of molecular shape, the Gaussian density map of the molecule is approximated using ERBFNN with a relatively small number of neurons. The deep learning models were trained by optimizing a nonlinear loss function with L1 regularization. Experimental results reveal that our algorithm can represent the original molecular shape with a relatively higher accuracy and fewer scale of ERBFNN. Our network in principle is applicable to the multiresolution sparse representation of molecular shape and coarse-grained molecular modeling. Executable files are available at https://github.com/SGUI-LSEC/SparseGaussianMolecule. The program was implemented in PyTorch and was run on Linux. |
| DOI | 10.1021/acs.jcim.0c00585 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Key Research and Development Program of China[2016YF-B0201304] ; China NSF (NSFC)[11771435] ; China NSF (NSFC)[21573274] |
| WOS Research Area | Pharmacology & Pharmacy ; Chemistry ; Computer Science |
| WOS Subject | Chemistry, Medicinal ; Chemistry, Multidisciplinary ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications |
| WOS ID | WOS:000608875100046 |
| Publisher | AMER CHEMICAL SOC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/58035 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Lu, Benzhuo; Chen, Minxin |
| Affiliation | 1.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, State Key Lab Sci & Engn Comp, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China 3.Soochow Univ, Dept Math, Suzhou 215006, Peoples R China |
| Recommended Citation GB/T 7714 | Gui, Sheng,Chen, Zhaodi,Lu, Benzhuo,et al. Molecular Sparse Representation by a 3D Ellipsoid Radial Basis Function Neural Network via L1 Regularization[J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING,2020,60(12):6054-6064. |
| APA | Gui, Sheng,Chen, Zhaodi,Lu, Benzhuo,&Chen, Minxin.(2020).Molecular Sparse Representation by a 3D Ellipsoid Radial Basis Function Neural Network via L1 Regularization.JOURNAL OF CHEMICAL INFORMATION AND MODELING,60(12),6054-6064. |
| MLA | Gui, Sheng,et al."Molecular Sparse Representation by a 3D Ellipsoid Radial Basis Function Neural Network via L1 Regularization".JOURNAL OF CHEMICAL INFORMATION AND MODELING 60.12(2020):6054-6064. |
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