Ecosyste.ms: Papers

An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.

Projects: pypi: BNPMDA

https://packages.ecosyste.ms/registries/pypi.org/packages/BNPMDA

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Latest release: over 5 years ago
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Papers Mentioning BNPMDA 18

A network embedding-based multiple information integration method for the MiRNA-disease association prediction
Cited by: 50
Author(s): Yuchong Gong, Yanqing Niu, Wen Zhang, LI Xiao-hong
Software Mentions: 3
Published: about 5 years ago

10.3390/cells8090977

A Novel Computational Model for Predicting microRNA–Disease Associations Based on Heterogeneous Graph Convolutional Networks
Cited by: 53
Author(s): Chunyan Li, Hongju Liu, Qian Hu, Jinlong Que, Junfeng Yao
Software Mentions: 3
Published: about 5 years ago

10.3389/fgene.2021.727744

Predicting miRNA-Disease Associations Based on Heterogeneous Graph Attention Networks
Cited by: 6
Author(s): Cun-Mei Ji, Yutian Wang, Jian Ni, Chun-Hou Zheng, Yansen Su
Software Mentions: 3
Published: about 3 years ago

10.1186/s13059-019-1811-3

Benchmark of computational methods for predicting microRNA-disease associations
Cited by: 32
Author(s): Zhou Huang, Leibo Liu, Yuanxu Gao, Jiangcheng Shi, Qinghua Cui, Jianwei Li, Yuan Zhou
Software Mentions: 2
Published: about 5 years ago

10.3390/ijms20153648

Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks
Cited by: 38
Author(s): Ping Xuan, Hao Sun, Xiao Wang, Tiangang Zhang, Shuxiang Pan
Software Mentions: 2
Published: over 5 years ago

10.1038/s41598-020-65633-6

Predicting miRNA-based disease-disease relationships through network diffusion on multi-omics biological data
Cited by: 14
Author(s): Marissa Sumathipala, Scott T. Weiss
Software Mentions: 2
Published: over 4 years ago

10.3389/fbioe.2020.00040

A Computational Study of Potential miRNA-Disease Association Inference Based on Ensemble Learning and Kernel Ridge Regression
Cited by: 30
Author(s): Lihong Peng, Liqian Zhou, Xing Chen, Xue Piao
Software Mentions: 1
Published: almost 5 years ago

10.3389/fgene.2019.01147

A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations
Cited by: 15
Author(s): Shiru Li, Minzhu Xie, Xinqiu Liu
Software Mentions: 1
Published: almost 5 years ago

10.1186/s12967-019-2063-4

WBNPMD: weighted bipartite network projection for microRNA-disease association prediction
Cited by: 12
Author(s): Guobo Xie, Zhiliang Fan, Yeping Sun, Cuiming Wu, Lei Ma
Software Mentions: 1
Published: about 5 years ago

10.3389/fgene.2019.01357

A Bipartite Network Module-Based Project to Predict Pathogen–Host Association
Cited by: 4
Author(s): Jie Li, Shiming Wang, Zhuo Chen, Yadong Wang
Software Mentions: 1
Published: almost 5 years ago

10.3389/fgene.2020.00389

MSFSP: A Novel miRNA–Disease Association Prediction Model by Federating Multiple-Similarities Fusion and Space Projection
Cited by: 11
Author(s): Yi Zhang, Min Chen, Xiaohui Cheng, Hanyan Wei
Software Mentions: 1
Published: over 4 years ago

10.1038/s41598-018-36297-0

Integrated analysis of microRNA and mRNA expression profiles in splenomegaly induced by non-cirrhotic portal hypertension in rats
Cited by: 3
Author(s): Junji Saruwatari, Chao Dong, Teruo Utsumi, Masanori Tanaka, Matthew McConnell, Yasuko Iwakiri
Software Mentions: 1
Published: almost 6 years ago

10.3390/ijms20010110

A Novel Approach Based on a Weighted Interactive Network to Predict Associations of MiRNAs and Diseases
Cited by: 17
Author(s): Haochen Zhao, Linai Kuang, Xin Feng, Quan Zou, Lei Wang
Software Mentions: 1
Published: almost 6 years ago

10.1186/s12859-020-03799-6

MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations
Cited by: 12
Author(s): Tian-Ru Wu, Meng-Meng Yin, Cui-Na Jiao, Ying-Lian Gao, Xiang-Zhen Kong, Jin-Xing Liu
Software Mentions: 1
Published: about 4 years ago

10.1186/s12920-019-0622-4

MiRNA-disease interaction prediction based on kernel neighborhood similarity and multi-network bidirectional propagation
Cited by: 10
Author(s): Yingjun Ma, Tingting He, Leixin Ge, Chenhao Zhang, Xingpeng Jiang
Software Mentions: 1
Published: almost 5 years ago

10.1186/s12859-020-3426-9

PESM: predicting the essentiality of miRNAs based on gradient boosting machines and sequences
Cited by: 8
Author(s): Yan Cheng, Fang‐Xiang Wu, Jianxin Wang, Guihua Duan
Software Mentions: 1
Published: over 4 years ago

10.3390/molecules24173099

Prediction of Disease-related microRNAs through Integrating Attributes of microRNA Nodes and Multiple Kinds of Connecting Edges
Cited by: 8
Author(s): Ping Xuan, Lingling Li, Tiangang Zhang, Yan Zhang, Yingying Song
Software Mentions: 1
Published: about 5 years ago

10.3390/cells8091040

Prediction of Potential miRNA–Disease Associations Through a Novel Unsupervised Deep Learning Framework with Variational Autoencoder
Cited by: 39
Author(s): Li Zhang, Xing Chen, Jun Yin
Software Mentions: 1
Published: about 5 years ago