biomedicalbigdatamininglab Goto Github PK
Type: Organization
Type: Organization
A curated list of network embedding techniques.
the desktop packege for the paper "Zhang, W., Zhu, X., Fu, Y., Tsuji, J., & Weng, Z. (2016). The prediction of human splicing branchpoints by multi-label learning. IEEE International Conference on Bioinformatics and Biomedicine (pp.254-259). IEEE Computer Society.'
Datasets and Code for "Predicting CircRNA-disease Associations through Linear Neighborhood Label Propagation Method"
data and source codes for paper "DeepiRNA: Predicting transposon-derived piRNAs with deep learning"
For each disease, a directed acyclic graph (DAG) is constructed based on hierarchical descriptors, in which nodes represent disease MeSH descriptors (or disease terms) and edges represent the relationship between the current node and its ancestors. Then compare the DAG Similarity.
The source code for the paper "Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data",Zhang et al. BMC Bioinformatics (2017) 18:18.
EPIHC: Improving Enhancer-Promoter Interaction Prediction by using Hybrid features and Communicative learning
Must-read papers on graph neural networks (GNN)
GraphCDR: A graph neural network method with contrastive learning for cancer drug response prediction
ItLnc-BXE: Identification of plant lncRNAs using a Bagging-XGBoost-ensemble method with multiple features
Code and Datasets for "Predicting Drug-Disease Associations through Layer Attention Graph Convolutional Networks"
LncPred-IEL: A Long Non-coding RNA Prediction Method using Iterative Ensemble Learning
The source codes for our paper submitted to Neurocomputing in 2017. We propose a linear label propagation method (LPLNP method) to predict unknown lncRNA-protein interactions. In this repository, you can find our dataset and code of individual LPLNP, intergrated LPLNP models, and other state-of-the-art methods. Please follow the Guideline.pdf.
MVGCN: a novel multi-view graph convolutional network (MVGCN) framework for link prediction in biomedical bipartite networks.
The source code for the paper "A genetic algorithm-based weighted ensemble method for predicting transposon-derived piRNAs",Zhang et al. (2016) 17: 329. doi:10.1186/s12859-016-1206-3
PredLnc-GFStack: a Global Sequence Feature Based on a Stacked Ensemble Learning Method for Predicting lncRNAs from Transcripts
最基础的gcn实现单关联预测
The source code for our paper "SFLLN: a sparse feature learning ensemble method with linear neighborhood regularization for predicting drug-drug interactions". In this repository, you can find our dataset "feature matrix.xls", "interaction matrix.txt" and source code "SFLLN.py". Please follow the "Readme.txt" for more details.
LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination
Code and dataset for "Sequence-based bacterial small RNAs prediction using ensemble learning strategies" Please kindly cite the paper if you use the code or the datasets.
tensor decomposition, python
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
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We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.