DeepCellEss: cell line-specific essential protein prediction with attention-based interpretable deep learning
Motivation Protein essentiality is usually accepted to be a conditional trait and strongly
affected by cellular environments. However, existing computational methods often do not …
affected by cellular environments. However, existing computational methods often do not …
'Bingo'—a large language model-and graph neural network-based workflow for the prediction of essential genes from protein data
The identification and characterization of essential genes are central to our understanding of
the core biological functions in eukaryotic organisms, and has important implications for the …
the core biological functions in eukaryotic organisms, and has important implications for the …
Employing Machine Learning Techniques to Detect Protein-Protein Interaction: A Survey, Experimental, and Comparative Evaluations
K Taha - bioRxiv, 2023 - biorxiv.org
This survey paper provides an in-depth analysis of various machine learning techniques
and algorithms that are utilized in the detection of PPI (Protein-Protein Interactions). For …
and algorithms that are utilized in the detection of PPI (Protein-Protein Interactions). For …
GRA-GCN: dense granule protein prediction in Apicomplexa protozoa through graph convolutional network
H Shi, H Feng, Z Lu, W Xue, C Yang… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
Dense granule proteins (GRAs) are secreted by Apicomplexa protozoa, which are closely
related to an extensive variety of farm animal diseases. Predicting GRAs is an integral part in …
related to an extensive variety of farm animal diseases. Predicting GRAs is an integral part in …