AIMC Topic: Protein Interaction Mapping

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A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Computational methods including centrality and machine learning-based methods have been proposed to identify essential proteins for understanding the minimum requirements of the survival and evolution of a cell. In centrality methods, researchers are...
Transcriptome Intracellular Space Deep Learning Protein Interaction Maps Computational Biology Protein Interaction Mapping Saccharomyces cerevisiae Proteins
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Robust principal component analysis-based prediction of protein-protein interaction hot spots.

Proteins Feb 2, 2021
Proteins often exert their function by binding to other cellular partners. The hot spots are key residues for protein-protein binding. Their identification may shed light on the impact of disease associated mutations on protein complexes and help des...
ROC Curve Protein Binding Computational Biology Humans Machine Learning Models, Molecular Binding Sites Protein Interaction Mapping Proteins Protein Interaction Domains and Motifs Databases, Protein Principal Component Analysis
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Classification and prediction of protein-protein interaction interface using machine learning algorithm.

Scientific reports Jan 19, 2021
Structural insight of the protein-protein interaction (PPI) interface can provide knowledge about the kinetics, thermodynamics and molecular functions of the complex while elucidating its role in diseases and further enabling it as a potential therap...
Protein Interaction Mapping Models, Molecular Binding Sites Molecular Docking Simulation Thermodynamics Protein Interaction Maps Proteins Databases, Protein Protein Binding Support Vector Machine
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A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning.

Interdisciplinary sciences, computational life sciences Jan 12, 2021
The new type of corona virus (SARS-COV-2) emerging in Wuhan, China has spread rapidly to the world and has become a pandemic. In addition to having a significant impact on daily life, it also shows its effect in different areas, including public heal...
Amino Acids Genome, Viral Protein Interaction Mapping Algorithms Reproducibility of Results SARS-CoV-2 Deep Learning ROC Curve Protein Binding Humans COVID-19
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A network-based machine-learning framework to identify both functional modules and disease genes.

Human genetics Jan 7, 2021
Disease gene identification is a critical step towards uncovering the molecular mechanisms of diseases and systematically investigating complex disease phenotypes. Despite considerable efforts to develop powerful computing methods, candidate gene ide...
Humans Mental Disorders Neoplasms Metabolic Networks and Pathways Neurodegenerative Diseases Supervised Machine Learning Amino Acid Sequence Gene Regulatory Networks Computational Biology Predictive Value of Tests Gastrointestinal Diseases Protein Interaction Mapping Immune System Diseases Musculoskeletal Diseases Metabolic Diseases Terminology as Topic
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Graph embeddings on gene ontology annotations for protein-protein interaction prediction.

BMC bioinformatics Dec 16, 2020
BACKGROUND: Protein-protein interaction (PPI) prediction is an important task towards the understanding of many bioinformatics functions and applications, such as predicting protein functions, gene-disease associations and disease-drug associations. ...
Humans Animals Protein Interaction Mapping ROC Curve Saccharomyces cerevisiae Computational Biology Mice Molecular Sequence Annotation Area Under Curve Gene Ontology Task Performance and Analysis
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Ensembling of Gene Clusters Utilizing Deep Learning and Protein-Protein Interaction Information.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2020
Cluster ensemble techniques aim to combine the outputs of multiple clustering algorithms to obtain a single consensus partitioning. The current paper reports about the development of a cluster ensemble based technique combining the concepts of multio...
Multigene Family Protein Interaction Mapping Protein Interaction Maps Computational Biology Cluster Analysis Phylogeny Deep Learning
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Triage of documents containing protein interactions affected by mutations using an NLP based machine learning approach.

BMC genomics Nov 10, 2020
BACKGROUND: Information on protein-protein interactions affected by mutations is very useful for understanding the biological effect of mutations and for developing treatments targeting the interactions. In this study, we developed a natural language...
Protein Interaction Mapping Natural Language Processing Mutation Data Mining Machine Learning
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SPOTONE: Hot Spots on Protein Complexes with Extremely Randomized Trees via Sequence-Only Features.

International journal of molecular sciences Oct 1, 2020
Protein Hot-Spots (HS) are experimentally determined amino acids, key to small ligand binding and tend to be structural landmarks on protein-protein interactions. As such, they were extensively approached by structure-based Machine Learning (ML) pred...
Amino Acids Humans Amino Acid Sequence Binding Sites Computational Biology Machine Learning Protein Interaction Mapping Datasets as Topic Proteins Protein Binding Databases, Protein
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Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes.

International journal of molecular sciences Jul 6, 2020
Predicting protein-protein interactions (PPI) represents an important challenge in structural bioinformatics. Current computational methods display different degrees of accuracy when predicting these interactions. Different factors were proposed to h...
Databases, Protein Protein Interaction Mapping Sequence Analysis, Protein Computational Biology Artificial Intelligence Cluster Analysis Machine Learning Proteins Algorithms
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