A Graph Convolutional Network-based solution for PHI prediction.
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Updated
Sep 21, 2022 - Python
A Graph Convolutional Network-based solution for PHI prediction.
Prediction of protein-protein interaction between anti-crispr protein (acr) and CRISPR-associated (cas) protein using machine learning algorithm
Protein Protein Interaction Analysis With The Help Of Data Science And Machine Learning. ( Hubs: PARKIN,PINK1,DJ1 )
Post-acquisition targeted search (PATS) by Yu (Tom) Gao @ Yates Lab
Jupyter notebooks for BFG-PCA related simulation and analysis.
This code was written and used to perform the comparative interactome analysis of β-arrestin1 and 2.
Measuring gene pleiotropy through Gene Ontologies and Protein Interactions
InteractoMIX: a suite of computational tools to exploit interactomes in biological and clinical research.
This repository contains codes for the regeneration of figures 3b and 3g in Tam, C., Kukimoto-Niino, M., Miyata-Yabuki, Y. et al. Targeting Ras-binding domain of ELMO1 by computational nanobody design. Commun Biol 6, 284 (2023).
Backend for the EvoPPI application
Comprehensive human PPI network and TF network
A python solution towards classifying different protein-protein interactions among Protein Sequences.
Analysis of AP-MS data
A method designed for proteome-scale sequence-based evaluation of protein-protein interfaces as defined by structural models of protein-protein interaction complexes.
A novel insight into neurological disorders through HDAC6 protein-protein interactions
PlantPathoPPI: An Ensemble-based Machine Learning Architecture for Prediction of Protein-Protein Interactions between Plants and Pathogens
Project for the Advanced Genomics course of "Bioinformatics for Computational Genomics" MSc
Incorporating Triplet Error for Predicting PPIs using Deep Learning
Scipion framework plugin for the use of tools provided in the Rosetta software suite. Currently it has protocols for the use of the Rosetta DARC docking software
Sequence based PPI prediction algorithm is developed using Xgboost. Around 73,000 positive and negative interacting protein pairs were extracted from Pan’s PPI dataset
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