AIMC Topic: Protein Interaction Mapping

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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...
Predictive Value of Tests Metabolic Networks and Pathways Neurodegenerative Diseases Supervised Machine Learning Neoplasms Gene Regulatory Networks Computational Biology Terminology as Topic Gastrointestinal Diseases Protein Interaction Mapping Immune System Diseases Amino Acid Sequence Musculoskeletal Diseases Metabolic Diseases Humans Mental Disorders
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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. ...
ROC Curve Task Performance and Analysis Mice Humans Computational Biology Saccharomyces cerevisiae Gene Ontology Animals Molecular Sequence Annotation Area Under Curve Protein Interaction Mapping
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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...
Protein Interaction Maps Computational Biology Cluster Analysis Multigene Family Phylogeny Deep Learning Protein Interaction Mapping
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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...
Machine Learning Natural Language Processing Mutation Data Mining Protein Interaction Mapping
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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...
Datasets as Topic Binding Sites Protein Interaction Mapping Machine Learning Protein Binding Computational Biology Amino Acids Amino Acid Sequence Proteins Databases, Protein Humans
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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...
Protein Interaction Mapping Algorithms Artificial Intelligence Sequence Analysis, Protein Computational Biology Machine Learning Cluster Analysis Proteins Databases, Protein
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Predicting protein subcellular location with network embedding and enrichment features.

Biochimica et biophysica acta. Proteins and proteomics Jun 25, 2020
The subcellular location of a protein is highly related to its function. Identifying the location of a given protein is an essential step for investigating its related problems. Traditional experimental methods can produce solid determination. Howeve...
Neural Networks, Computer Gene Ontology Protein Interaction Mapping Intracellular Space Computational Biology Algorithms Proteins Decision Trees Protein Interaction Maps Protein Transport Protein Binding
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Prediction of Protein-Protein Interactions with Local Weight-Sharing Mechanism in Deep Learning.

BioMed research international Jun 13, 2020
Protein-protein interactions (PPIs) are important for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. The experimental methods for identifying PPIs are always time-consuming and ex...
Protein Interaction Maps Escherichia coli Humans Protein Interaction Mapping Saccharomyces cerevisiae Mice Proteins Animals Caenorhabditis elegans Computational Biology Databases, Protein Deep Learning
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Identification of feature risk pathways of smoking-induced lung cancer based on SVM.

PloS one Jun 4, 2020
OBJECTIVE: The present study aims to explore the role of smoking factors in the risk of lung cancer and screen the feature risk pathways of smoking-induced lung cancer.
Lung Neoplasms Signal Transduction Support Vector Machine Databases, Genetic Humans Smoking Cluster Analysis Risk Factors Gene Ontology DNA, Neoplasm Area Under Curve Gene Expression Profiling Protein Interaction Mapping High-Throughput Nucleotide Sequencing ROC Curve
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BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale.

PLoS computational biology Apr 23, 2020
A massive number of biological entities, such as genes and mutations, are mentioned in the biomedical literature. The capturing of the semantic relatedness of biological entities is vital to many biological applications, such as protein-protein inter...
Publications Drug Interactions PubMed Protein Interaction Mapping Data Mining Semantics Deep Learning Computational Biology Databases, Protein Humans Algorithms Electronic Health Records
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