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Structure-based protein function prediction using graph convolutional networks

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Toward a molecular understanding of protein solubility: increased negative surface charge correlates with increased solubility

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Graph Neural Networks and Their Current Applications in Bioinformatics

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Topological determinants of protein folding

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Assortative mixing in Protein Contact Networks and protein folding kinetics

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Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map

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Solubility-Weighted Index: fast and accurate prediction of protein solubility

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Computational analysis of the amino acid interactions that promote or decrease protein solubility

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Cancer Somatic Mutations Disrupt Functions of the EphA3 Receptor Tyrosine Kinase through Multiple Mechanisms

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AUTO-MUTE 2.0: A Portable Framework with Enhanced Capabilities for Predicting Protein Functional Consequences upon Mutation

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Residue interaction network analysis of Dronpa and a DNA clamp

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DSResSol: A Sequence-Based Solubility Predictor Created with Dilated Squeeze Excitation Residual Networks

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Develop machine learning-based regression predictive models for engineering protein solubility

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HuVarBase: A human variant database with comprehensive information at gene and protein levels

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Predicting disease-associated substitution of a single amino acid by analyzing residue interactions

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Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix

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Graph Classification with 2D Convolutional Neural Networks

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Efficient Identification of Critical Residues Based Only on Protein Structure by Network Analysis

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Towards more accurate prediction of protein folding rates: a review of the existing web-based bioinformatics approaches

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Applying graph theory to protein structures: an Atlas of coiled coils

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Topological determinants of protein unfolding rates

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Mutational Profiling of Kinases in Human Tumours of Pancreatic Origin Identifies Candidate Cancer Genes in Ductal and Ampulla of Vater Carcinomas

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Amino Acid Network for the Discrimination of Native Protein Structures from Decoys

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Structure-based rebuilding of coevolutionary information reveals functional modules in rhodopsin structure

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Graph Signal Processing on protein residue networks helps in studying its biophysical properties

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Erratum: Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix

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Graph Signal Processing on protein residue networks helps in studying its biophysical properties

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Geometric Graph Learning for Protein Mutation Effect Prediction

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Investigating the Changes in Amino Acid Properties in the Evolutionary and Multi-Scale Context

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Finding characteristic bands from protein sequences using wavelet packet transform and energy map

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PREDICTING PROTEIN STRUCTURAL FEATURES WITH WAVELET PACKET

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