Prottrans: Toward understanding the language of life through self-supervised learning
Computational biology and bioinformatics provide vast data gold-mines from protein
sequences, ideal for Language Models (LMs) taken from Natural Language Processing …
sequences, ideal for Language Models (LMs) taken from Natural Language Processing …
Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins
Membrane proteins are unique in that they interact with lipid bilayers, making them
indispensable for transporting molecules and relaying signals between and across cells …
indispensable for transporting molecules and relaying signals between and across cells …
[HTML][HTML] Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications
Membrane proteins mediate a wide spectrum of biological processes, such as signal
transduction and cell communication. Due to the arduous and costly nature inherent to the …
transduction and cell communication. Due to the arduous and costly nature inherent to the …
Prediction of disease-associated nsSNPs by integrating multi-scale ResNet models with deep feature fusion
F Ge, Y Zhang, J Xu, A Muhammad… - Briefings in …, 2022 - academic.oup.com
More than 6000 human diseases have been recorded to be caused by non-synonymous
single nucleotide polymorphisms (nsSNPs). Rapid and accurate prediction of pathogenic …
single nucleotide polymorphisms (nsSNPs). Rapid and accurate prediction of pathogenic …
[HTML][HTML] MutTMPredictor: robust and accurate cascade XGBoost classifier for prediction of mutations in transmembrane proteins
F Ge, YH Zhu, J Xu, A Muhammad, J Song… - Computational and …, 2021 - Elsevier
Transmembrane proteins have critical biological functions and play a role in a multitude of
cellular processes including cell signaling, transport of molecules and ions across …
cellular processes including cell signaling, transport of molecules and ions across …
VEPAD-Predicting the effect of variants associated with Alzheimer's disease using machine learning
Introduction Alzheimer's disease (AD) is a complex and heterogeneous disease that affects
neuronal cells over time and it is prevalent among all neurodegenerative diseases. Next …
neuronal cells over time and it is prevalent among all neurodegenerative diseases. Next …
MPAD: A Database for Binding Affinity of Membrane Protein–protein Complexes and their Mutants
Membrane protein complexes are crucial for a large variety of biological functions which are
mainly dictated by their binding affinity. Due to the intricate nature of their structure, however …
mainly dictated by their binding affinity. Due to the intricate nature of their structure, however …
Recent advances in features generation for membrane protein sequences: From multiple sequence alignment to pre‐trained language models
Membrane proteins play a crucial role in various cellular processes and are essential
components of cell membranes. Computational methods have emerged as a powerful tool …
components of cell membranes. Computational methods have emerged as a powerful tool …
MPTherm-pred: analysis and prediction of thermal stability changes upon mutations in transmembrane proteins
The stability of membrane proteins differs from globular proteins due to the presence of
nonpolar membrane-spanning regions. Using a dataset of 929 membrane protein mutations …
nonpolar membrane-spanning regions. Using a dataset of 929 membrane protein mutations …
TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion
Z Yan, F Ge, Y Liu, Y Zhang, F Li… - Journal of Chemical …, 2024 - ACS Publications
Studying the effect of single amino acid variations (SAVs) on protein structure and function is
integral to advancing our understanding of molecular processes, evolutionary biology, and …
integral to advancing our understanding of molecular processes, evolutionary biology, and …