In this paper, we propose a pattern-based protein function annotation framework, employing protein interaction networks, to predict annotation functions of ...
Abstract. In this paper, we propose a pattern-based protein function annotation framework, employing protein interaction networks, to predict annotation ...
People also ask
What are protein function prediction methods?
How can you predict the function of a protein from structure?
What are network based methods for gene function prediction?
What are the methods for predicting protein protein interactions?
Predicting protein function is crucial for understanding biological life processes, preventing diseases and developing new drug targets.
In this review, we survey the growing body of works on functional annotation of proteins via their network of interactions.
Jun 27, 2022 · We introduce GLIDER, a method that replaces a protein-protein interaction or association network with a new graph-based similarity network.
TAWFN: a deep learning framework for protein function prediction
academic.oup.com › article › btae571
Sep 23, 2024 · A method that combines CNN and GCN into a unified framework called the two-model adaptive weight fusion network (TAWFN) for protein function prediction.
May 26, 2021 · We introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model ...
Feb 27, 2023 · ProteInfer, an important new tool that analyses protein sequences to predict their functions. It is based on a single convolutional neural network scan for all ...
Aug 12, 2020 · We presented NPF (Network Propagation for Functions prediction), an integrative protein function predicting framework assisted by network propagation and ...
Jul 1, 2024 · Exploring protein function prediction holds profound significance in comprehending both intracellular and extracellular biological processes ...