AIMC Topic: Protein Interaction Maps

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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...
Computational Biology Protein Interaction Mapping Saccharomyces cerevisiae Proteins Transcriptome Intracellular Space Deep Learning Protein Interaction Maps
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Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease.

BMC cardiovascular disorders Jan 28, 2021
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia with poorly understood mechanisms. We aimed to investigate the biological mechanism of AF and to discover feature genes by analyzing multi-omics data and by applying a machine learnin...
Humans Middle Aged Gene Expression Profiling Transcriptome Case-Control Studies Machine Learning Female Male Atrial Fibrillation Heart Atria Proteomics Oligonucleotide Array Sequence Analysis Heart Valve Diseases Signal Transduction Protein Interaction Maps Databases, Genetic Gene Regulatory Networks Bayes Theorem Genetic Association Studies
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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...
Models, Molecular Molecular Docking Simulation Binding Sites Protein Interaction Maps Support Vector Machine Protein Binding Thermodynamics Proteins Protein Interaction Mapping Databases, Protein
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Characterization of Antiphospholipid Syndrome Atherothrombotic Risk by Unsupervised Integrated Transcriptomic Analyses.

Arteriosclerosis, thrombosis, and vascular biology Dec 24, 2020
OBJECTIVE: Our aim was to characterize distinctive clinical antiphospholipid syndrome phenotypes and identify novel microRNA (miRNA)-mRNA-intracellular signaling regulatory networks in monocytes linked to cardiovascular disease. Approach and Results:...
Cluster Analysis MicroRNAs Unsupervised Machine Learning Thrombosis Gene Expression Regulation Oligonucleotide Array Sequence Analysis Antiphospholipid Syndrome Cells, Cultured Protein Interaction Maps Female Gene Regulatory Networks Risk Factors Monocytes Signal Transduction Adult Gene Expression Profiling Male Humans Transcriptome Middle Aged Case-Control Studies Risk Assessment
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Inter-protein residue covariation information unravels physically interacting protein dimers.

BMC bioinformatics Dec 17, 2020
BACKGROUND: Predicting physical interaction between proteins is one of the greatest challenges in computational biology. There are considerable various protein interactions and a huge number of protein sequences and synthetic peptides with unknown in...
Proteins Databases, Protein Dimerization Protein Interaction Maps Support Vector Machine Evolution, Molecular
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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...
Cluster Analysis Multigene Family Protein Interaction Mapping Phylogeny Deep Learning Protein Interaction Maps Computational Biology
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Deep Learning Benchmarks on L1000 Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2020
Gene expression data can offer deep, physiological insights beyond the static coding of the genome alone. We believe that realizing this potential requires specialized, high-capacity machine learning methods capable of using underlying biological str...
Humans Algorithms Models, Genetic Deep Learning Gene Expression Profiling Databases, Genetic Protein Interaction Maps Transcriptome Cell Line Computational Biology
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DeepciRGO: functional prediction of circular RNAs through hierarchical deep neural networks using heterogeneous network features.

BMC bioinformatics Nov 12, 2020
BACKGROUND: Circular RNAs (circRNAs) are special noncoding RNA molecules with closed loop structures. Compared with the traditional linear RNA, circRNA is more stable and not easily degraded. Many studies have shown that circRNAs are involved in the ...
RNA, Circular Humans Genetic Loci Protein Interaction Maps Ubiquitin-Protein Ligases Neural Networks, Computer Cell Proliferation Gene Ontology Cell Line, Tumor DNA Helicases Cell Movement
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Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction.

BMC bioinformatics Nov 12, 2020
BACKGROUND: Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential r...
Carcinoma, Non-Small-Cell Lung Afatinib Mutation ErbB Receptors Humans Protein Kinase Inhibitors Cell Line, Tumor MAP Kinase Signaling System Neural Networks, Computer Lapatinib Quantitative Structure-Activity Relationship Protein Interaction Maps Precision Medicine Lung Neoplasms
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Matrix Factorization-based Technique for Drug Repurposing Predictions.

IEEE journal of biomedical and health informatics Nov 4, 2020
Classical drug design methodologies are hugely costly and time-consuming, with approximately 85% of the new proposed molecules failing in the first three phases of the FDA drug approval process. Thus, strategies to find alternative indications for al...
Protein Interaction Maps Proteins Humans Drug Repositioning Machine Learning Algorithms
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