AIMC Topic: Proteins
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Machine learning based predictive model for the analysis of sequence activity relationships using protein spectra and protein descriptors.
Journal of biomedical informatics
Feb 7, 2022
Accurately establishing the connection between a protein sequence and its function remains a focal point within the field of protein engineering, especially in the context of predicting the effects of mutations. From this, there has been a continued ...
End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins.
ACS biomaterials science & engineering
Feb 7, 2022
Structural proteins are the basis of many biomaterials and key construction and functional components of all life. Further, it is well-known that the diversity of proteins' function relies on their local structures derived from their primary amino ac...
De Novo Peptide and Protein Design Using Generative Adversarial Networks: An Update.
Journal of chemical information and modeling
Feb 7, 2022
Nowadays, machine learning and deep learning approaches are widely utilized for generative chemistry and computer-aided drug design and discovery such as de novo peptide and protein design, where target-specific peptide-based/protein-based therapeuti...
Has DeepMind's AlphaFold solved the protein folding problem?
BioTechniques
Feb 4, 2022
DeepMind released AlphaFold 2.0 in 2020, an artificial intelligence model to predict the structure of proteins, which could mean that proteins can be characterized without the need for tedious and costly lab analysis.
SPP-CPI: Predicting Compound-Protein Interactions Based On Neural Networks.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
Identifying interactions between compound and protein is a substantial part of the drug discovery process. Accurate prediction of interaction relationships can greatly reduce the time of drug development. The uniqueness of our method lies in three as...
Leveraging Sequential and Spatial Neighbors Information by Using CNNs Linked With GCNs for Paratope Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
Antibodies consisting of variable and constant regions, are a special type of proteins playing a vital role in immune system of the vertebrate. They have the remarkable ability to bind a large range of diverse antigens with extraordinary affinity and...
Predicting Local Protein 3D Structures Using Clustering Deep Recurrent Neural Network.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
Since protein 3D structure prediction is very important for biochemical study and drug design, researchers have developed many machine learning algorithms to predict protein 3D structures using the sequence information only. Understanding the sequenc...
GuiltyTargets: Prioritization of Novel Therapeutic Targets With Network Representation Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
The majority of clinical trials fail due to low efficacy of investigated drugs, often resulting from a poor choice of target protein. Existing computational approaches aim to support target selection either via genetic evidence or by putting potentia...
Boltzmann Machine Learning and Regularization Methods for Inferring Evolutionary Fields and Couplings From a Multiple Sequence Alignment.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
The inverse Potts problem to infer a Boltzmann distribution for homologous protein sequences from their single-site and pairwise amino acid frequencies recently attracts a great deal of attention in the studies of protein structure and evolution. We ...
Importance of interface and surface areas in protein-protein binding affinity prediction: A machine learning analysis based on linear regression and artificial neural network.
Biophysical chemistry
Feb 2, 2022
Protein-protein interaction plays an important role in all biological systems. The binding affinity between two protein binding partners reflects the strength of their association, which is crucial to the elucidation of the biological functions of th...
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